Cardiovirus genus of Picornaviridaebecause: i) L protein of both strains is known to disrupt nucleocytoplasmictransport, including transport of polypyrimidine tract binding protein, anRNA-binding protein, ii) motor neurons and oligodendrocytes are targeted in bothTMEV infection and ALS. TDP-43 phosphorylation, cleavage, and cytoplasmicmislocalization to an aggresome were observed in wild type TMEV-infectedcultured cells, with predicted splicing abnormalities. In contrast, cellsinfected with DA and GDVII strains that have L deletion had rare TDP-43mislocalization and no aggresome formation. TDP-43 mislocalization was alsopresent in neural cells of TMEV acutely-infected mice. Of note, TDP-43 wasmislocalized six weeks after DA infection to the cytoplasm of oligodendrocytesand other glial cells in demyelinating lesions of spinal white matter. A recentstudy showed that TDP-43 knock down in oligodendrocytes in mice led todemyelination and death of this neural cell [TDP-43, an RNA-binding protein that is primarily nuclear and important insplicing and RNA metabolism, is mislocalized from the nucleus to the cytoplasmof neural cells in amyotrophic lateral sclerosis (ALS), and contributes todisease. We sought to investigate whether TDP-43 is mislocalized in infectionswith the acute neuronal GDVII strain and the persistent demyelinating DA strainof Theiler’s virus murine encephalomyelitis virus (TMEV), a member of theral cell , suggest TDP-43 is a widely expressed nuclear protein that shuttles between the nucleusand cytoplasm, and regulates many aspects of RNA processing, such as splicing,trafficking, stabilization, and miRNA production. In almost all cases of ALS,neuronal and glial TDP-43 is phosphorylated, cleaved, and mislocalized to thecytoplasm, where it aggregates into stress granules and insoluble inclusionbodies. Although the mechanisms involved in TDP-43 proteinopathy remain unclear,impaired nucleocytoplasmic trafficking is thought to play an important role.Here we investigated whether TDP-43 proteinopathy also occurs during TMEVinfection since TMEV L protein is known to perturb nucleocytoplasmic transport.We found evidence of TDP-43 proteinopathy in both TMEV-infected cultured cells,with predicted splicing abnormalities, as well as in neural and glial cells ofTMEV-infected mice. The findings suggest that TDP-43 may contribute to thepathogenesis of TMEV-induced diseases, including TMEV-induced immune-mediateddemyelination. Trans-activation response (TAR) DNA-binding protein of 43 kDa (TDP-43) is anRNA-binding protein (as well as DNA-binding protein) primarily present in thenucleus and important in RNA processing, mRNA transport/stability, and mRNAtranslation –4. A varCardiovirus genus of Picornaviridae, is knownto disrupt nucleocytoplasmic transport [TDP-43 proteinopathy has been described in a number of diseases in addition to ALS. Since transport , 13, we ransport . TMEV inransport .GDVII sHere we report that TMEV infection of cultured cells causes L-dependentmislocalization of TDP-43, and L-independent cleavage and phosphorylation of TDP-43along with splicing abnormalities. Mislocalization and phosphorylation of TDP-43also occurs in neuronal cells following early TMEV infection of mice, and inoligodendroglia and other glial cells in demyelinated areas 6 weeks after DA virusinfection. These results suggest that TDP-43 mislocalization occurs and presumablycontributes to cellular dysfunction and death in TMEV infections. An important rolefor TDP-43 mislocalization in TMEV-induced demyelinating disease is suggested byrecent findings that TDP-43 binds to mRNAs encoding myelin genes, and that aknockdown of TDP-43 in oligodendrocytes of mice leads to demyelination and the deathof this neural cell .In control mock-infected BHK-21 cells, expression of TDP-43 was primarilyrestricted to the nucleus . FollowiWe questioned whether other RNA-binding proteins were also mislocalized to thecytoplasm in TMEV-infected cells. For this reason, we investigated thelocalization in cells of i) fused in sarcoma (FUS), which like TDP-43 is a causeof familial ALS when mutated, and ii) polypyrimidine tract binding protein(PTB), which is known to be mislocalized in TMEV infections, where it plays arole in TMEV translation , 19. DASince TMEV L protein is known to disrupt nucleocytoplasmic trafficking, weinvestigated TDP-43 localization following infection with mutant TMEV that hadan L deletion. As predicted, DAΔL and GDVIIΔL infection failed to inducemislocalization of TDP-43 in VP1-positive cells , demonstIn order to confirm the cytoplasmic mislocalization of TDP-43 in TMEV-infectedcells, we separated the nucleus and cytoplasm of cultured cells infected withTMEV . The resAs noted above, the juxtanuclear location of TDP-43 seen following TMEV infectionhad a morphology typical of an aggresome. Vimentin surrounded these juxtanuclearstructures , as istAggresomes result from a remodeling of intracellular membranes to generate sitesof virus replication . Fig 3A In order to assess the importance of aggresomes in TMEV infection, we made use ofnocodazole, a microtubule inhibitor that interferes with aggresome formation.BHK-21 cells were exposed to nocodazole , and then infected with DAvirus. Compared to levels obtained with no nocodazole treatment, nocodazole ledto a 10-fold reduction in virus genome at an MOI of 1, and 100-fold reduction atan MOI of 0.25 . AsexpeSGs are mainly composed of stalled translation preinitiation complexes, markerssuch as G3BP1, eIF3A, and TIA1, and RNA-binding proteins including TDP-43. Thesestructures are cytoplasmic non-membranous structures that appear in cellsexposed to various stresses, including virus infections . CertainBorghese and Michiels previousTo determine whether TMEV infection induces cleavage of TDP-43, as in the case ofALS, we carried out Western blots on RIPA-soluble and insoluble (but ureasoluble) fractions extracted from TMEV-infected BHK-21 cell lysates at 8 HPI.Following infection with both wt and TMEVΔL virus, ~35-kDa and ~25-kDa bands aswell as the expected 43-kDa band of full-length TDP-43 were detected in theurea-soluble, but not RIPA-soluble fraction, of BHK-21 cell lysates . These fTDP-43 is known to have an important role in alternative splicing, includingcystic fibrosis transmembrane conductance regulator (CFTR) exon 9 skipping. In ordeIn the case of ALS and ALS/FTD, TDP-43 is depleted in nuclei of neural cells, andmislocalized and phosphorylated in inclusions in the cytoplasm . In ordeDA virus produces a biphasic disease in SJL mice with minimal or subclinicaldisease within the first two weeks post-infection, followed by progressiveparalysis from an inflammatory demyelination that peaks at 6 weekspost-infection. In the acute phase of DA virus infection, VP1-positive neuronsand axons were present in the CA2 region of the hippocampus ; howeverSix weeks after infection with DA virus, the ventral region of the thoracicspinal cord showed perivascular mononuclear cell infiltrates, , demyeliTDP-43 is a ubiquitously expressed RNA-binding protein that predominantly resides inthe nucleus, but shuttles across the nuclear membrane in association with mRNAs. A hallmEnterovirus genus of Picornaviridae, TDP-43 ismislocalized  and cleaved  [As is true of many pathogens, picornaviruses disrupt nucleocytoplasmic traffickingduring infection, leading to cellular dysfunction as well as the redistribution andhijacking of nuclear proteins into the cytoplasm for use during virus replication, 31. Forease 3C) . In CVB3ease 3C) .In ALS, TDP-43 is thought to shuttle into the cytoplasm initially into SGs, and thenremain aggregated in the cytoplasm. In the case of TMEV-infected BHK-21 and L929cells, we detected the normal markers for SGs  in aggresomesrather than SGs. Of note, SGs were present following TMEVΔL infections, suggestingthat L inhibits SG formation, as has been reported by others . The aggMislocalization and phosphorylation of TDP-43 occurred in TMEV-infected culturedcells as well as neuronal and glial cells of TMEV-infected mice. In DA virus-induceddemyelinated regions, TDP-43 and other RNA-binding proteins were mislocalized inglial cells, including oligodendrocytes. The fact that TDP-43 was not present in thecytoplasm following infection with TMEVΔL virus, suggests that L interfered withnucleocytoplasmic transport. TDP-43 mislocalization in neural cells may also beinfluenced by inflammatory stimuli since tumor necrosis factor-α can lead tomislocalization of TDP-43 . In addiThe mislocalization of RNA-binding proteins in TMEV infections may disrupt cellularsplicing and mRNA translation, thereby contributing to neuronal dysfunction anddeath in GDVII and DA early disease as well as oligodendrocyte dysfunction in thelate demyelinating disease of DA-infected mice. Our previous study suggested thepossibility that PTB mislocalization in TMEV-infected neurons played a role inneuronal dysfunction .The delThe study involving the analysis of human subjects was approved by The Universityof Chicago Institutional Review Board for Clinical Research. Informed writtenconsent for an autopsy was obtained from an immediate member of the deceased’sfamily. Animal use was approved by The University of Chicago InstitutionalAnimal Care and Use Committee (IACUC) under the Protocol Number 71772. Animalwork conducted at the University of Chicago complies with all applicableprovisions of the Animal Welfare Act (AWA) and the Public Health Service (PHS)Policy on Humane Care and Use of Laboratory Animals. The PHS Policy incorporatesthe standards in the Guide for the Care and Use of Laboratory Animals and theU.S. Government Principles for the Utilization and Care of Vertebrate AnimalsUsed in Testing, Research and Training and requires euthanasia be conductedaccording to the AVMA Guidelines for the Euthanasia of Animals. The Universityof Chicago Animal Care Program has an approved Assurance with the NationalInstitute of Health (NIH), is registered with the United States Department ofAgriculture (USDA) and is accredited by the Association for Assessment andAccreditation of Laboratory Animal Care International (AAALAC).DA and GDVII viruses were derived from a full-length infectious cDNA clone . DAΔL viInfections were carried out in BHK-21 , L929  orHeLa cells , usually with a multiplicity of infection (MOI) of 10.BHK-21 cells were used for plaque assays and the growth of virus stocks, aspreviously described .For the study of TDP-43 cleavage, cells were treated with 1μM of the proteasomeinhibitor MG-132  for 16hs prior toharvest. For induction of SGs, BHK-21 cells were treated for 45 min with 0.5mMsodium arsenite . In investigations of theaggresome, nocodazole (Sigma Aldrich), a microtubule inhibitor, was solubilizedin DMSO and added at varying concentrations to the culture medium for 1h priorto infection.pDAL and pGDVIIL, which are eukaryotic expression constructs of DA L and GDVII Lrespectively, with myc/His epitope tags at the carboxyl terminus , were trCells on coverslips were harvested 8hs post infection (HPI) or 48hs aftertransfection, fixed in 4% paraformaldehyde for 5 min, and then permeabilizedwith phosphate buffered saline (PBS) with 0.1% Triton X-100 for 20 min at roomtemperature. The coverslips were then incubated overnight at 4°C with primaryantibodies . After rCells were lysed 8 HPI with a radioimmunoprecipitation assay (RIPA) buffercontaining a protease inhibitor and phosphatase inhibitor cocktail . Lysates were centrifuged at 14,000 rpm for 30min at 4°C, and supernatants collected as RIPA buffer-soluble proteins. Thepellets were sonicated and centrifuged twice at 14,000 rpm for 30 min at 4°C toobtain RIPA buffer-insoluble pellets. Pellets were dissolved in urea buffer  and then sonicated again prior to electrophoresis.Ten μg of total protein quantified by a Pierce BCA Protein Assay Kit  was subjected to electrophoresis on 10% SDSpolyacrylamide gels, and then transferred to Amersham Hybond P 0.45 μm PVDFmembrane . The membrane was first blockedwith 5% non-fat skim milk in Tris-buffered saline (TBS) containing 0.05%Tween-20 for 30 min at room temperature, and then incubated for 1h at roomtemperature with a rabbit antibody directed against C-terminal TDP-43  or a mouse monoclonal antibody against TMEV VP1(1:2000), which was previously called GDVII mAb2 [DA RNA was extracted from BHK-21 and HeLa cell homogenates using an RNeasy Plusminikit (Qiagen). A region between nt 1485 and 1684 was amplified using forwardprimer TACTATGGCACCTCTCCTCTTGGA and reverse primer CAGCCGCAAGAACTTTATCCGTTG witha Superscript III Platinum two-step qRT-PCR kit with SYBR green (Invitrogen). Aregion between nt 182 and 721 of the murine β-actin gene, which was used fornormalization and determination of the quality of total mRNA, was amplifiedusing forward primer GTGGGCCGCTCTAGGCACCAA and reverse primerCTCTTTGATGTCACGCACGATTTC. qRT-PCR was conducted on a CFX96 Real-Time System(Bio-Rad). The ΔΔCT method of relative quantitation was used to calculate foldchange of DA with β-actin.In order to assess splicing in TMEV-infected cells, a cystic fibrosistransmembrane conductance regulator (CFTR) minigene construct designed toevaluate CFTR exon 9 splicing  wastraImmunohistochemical studies were performed on autopsied brain specimens of apatient with ALS.TMEV was inoculated intracerebrally in weanling SJL mice , and mice were sacrificed at 1, 2 or 6 weeks post infection (PI). Atthe time of sacrifice, mice were deeply anesthetized and perfused transcardiallyfirst with PBS, and then with 4% paraformaldehyde in 0.1 M phosphate buffer. CNStissues were fixed in 10% buffered formalin and processed into paraffin sections(5 μm thick). Deparaffinized sections were hydrated in ethanol and thenincubated with 0.3% hydrogen peroxide in absolute methanol for 30 min at roomtemperature to inhibit endogenous peroxidase. After rinsing with tap water,sections were washed twice using Tris–HCl with 0.1% Triton X-100 for 5 min, andthen with Tris–HCl for 5 min. Sections were then incubated at 4°C overnight withprimary antibody  diluted Paraffin sections were also used for immunofluorescent staining. Sections weredeparaffinized in xylene, rehydrated through an ethanol gradient, and thenincubated with primary antibody for 1h at room temperature. The followingantibodies were used: mouse monoclonal anti-VP1, rabbit anti-TDP-43, and rabbitanti-2',3'-cyclic nucleotide-3'-phosphodiesterase (CNPase) ;rabbit P-value of <0.05 was considered significant. The dataare presented as the mean ± standard deviation (S.D.).Statistical analysis was performed by an unpaired t-test or one-way ANOVA withTukey's multiple comparisons test using GraphPad Prism version 7.0a. AS1 FigImmunofluorescent staining for TDP-43 in BHK-21 cells at 6 and 12 HPI. TDP-43cytoplasmic mislocalization and aggregate formation induced by DA and GDVIIinfection are present by 6 HPI and persists for at least 12 HPI. Scale bars:10 μm.(TIF)Click here for additional data file.S2 FigDouble immunofluorescent staining for pTDP-43 and VP1 in BHK-21 cells at 8HPI. pTDP-43 is present in the cytoplasm of VP1-positive cells infected withDA or GDVII virus. Scale bars: 10 μm.(TIF)Click here for additional data file.S3 Figarrowheads)is present in pDAL- or pGDVIIL-transfected BHK-21, L929, and HeLa cells, Theexpression of L is indicated by Myc positivity. Scale bars: 10 μm.TDP-43 mislocalization and aggregate formation ((TIF)Click here for additional data file.S4 Fig(A) Representative images of immunofluorescence using anti-L antibody. L isexpressed in pDAL- or pGDVIIL-transfected BHK-21 cells (that are detected byMyc staining) and DA-infected BHK-21 cells (that are detected by VP1staining). (B) Intensity of immunofluorescence for L. The Intensity ofimmunofluorescence of L within each cell ) was measured by ImageJ in 20 cells in 5 random fieldsand was then plotted as a dot graph. The intensity of immunofluorescence incells from the three groups is not statistically significant. Scale bars: 10μm.(TIF)Click here for additional data file.S5 FigWestern blotting of nuclear (N) and cytoplasmic (C) fractions ofTMEV-infected BHK-21 cells. The nuclear and cytoplasmic fractions of BHK-21cells were separated by using NE-PER Nuclear and Cytoplasmic ExtractionReagents . In MOCK, DAΔL andGDVIIΔL-infected cells, TDP-43 is predominantly expressed in the nucleus(and transiently may enter the cytoplasm). In contrast, TDP-43 issignificantly mislocalized to the cytoplasm of DA- and GDVII-infected cells.The expression of LaminA/C, a nuclear envelope protein, is primarily in thenuclear fraction, while TMEV VP1 is present in the cytoplasmic fraction.(TIF)Click here for additional data file.S6 Figarrow). Scale bar: 5 μm.HeLa cells infected by DA virus at 12 HPI. Although TDP-43 is slightlymislocalized to the cytoplasm in VP1-positive cells, aggresomes are notobserved in this cell ((TIF)Click here for additional data file.S7 FigBHK-21 cells infected by DA and GDVII virus at 8 HPI. Both TDP-43 and VP1accumulate in the juxtanuclear aggresome. TDP-43 and VP1 are partlyco-localized within the aggresome shown in yellow. Scale bars: 5 μm.(TIF)Click here for additional data file.S8 Fig(A) The amount of DA virus genome at 6 HPI with two different MOIs in HeLacells that had been treated with nocodazole  for 1h priorto infection. The viral genome is only slightly decreased with the 30 μMnocodazole treatment. (B) Plaque assay of DA-infected BHK-21 cells treatedwith nocodazole treatment  shows a similarvirus titer compared to untreated cells.(TIF)Click here for additional data file.S9 Figarrowheads). Scale bars: 10 μm.(A-C) BHK-21 cells treated for 45 minutes with 0.5 mM sodium arsenite, a SGinducer, develop SGs that contain SG markers: G3BP1 (A), eIF3A and TIA1 (B).SG markers in mock-treated cells have homogeneous cytoplasmicimmunostaining. Following sodium arsenite treatment, SG markers are presentin small structures of the typical size of SGs. (C) Following sodiumarsenite treatment, TDP-43 and PTB1 partly move into the cytoplasm and mergewith TIA1 in SGs ((TIF)Click here for additional data file.S10 Figarrows). (C) L929 cells infected by DA virus at 8 HPI.Aggresomes containing G3BP1, eIF3A and TIA1 are observed in VP1-positivecells. Scale bars: 10 μmL929 (A) and HeLa (B) cells infected by DAΔL virus at 8 HPI. SGs containingG3BP1, eIF3A and TIA1 are present in the cytoplasm of VP1-positive cells((TIF)Click here for additional data file.S11 Figarrows) in CA2region two weeks after infection of DA virus. The frequency of TDP-43mislocalization in VP1-positive cells is ~70%, as shown in the graph bar (n= 3). (C) Representative image showing phosphorylation of TDP-43 inVP1-positive CA1 region neuron (arrow) two weeks afterinfection of DA virus. Higher magnification shows skein-like inclusion(arrows) which is immunopositive for pTDP-43(brown) in a VP1-positive cell (pink).The frequency of TDP-43 phosphorylation in VP1-positive cells is ~60%, asshown in the graph bar (n = 3). Scale bars: 10 μm. *P <0.0001. Double immunofluorescence for TDP-43 and VP1 in the hippocampus ofuninfected and TMEV-infected mice. (A) TDP-43 is predominantly localized tothe nucleus of CA1 region neurons in uninfected mice. In contrast, TDP-43 isdepleted in the nucleus, and mislocalized to the cytoplasm of VP1-positiveneurons in CA1 region 1 week after infection with GDVII virus. The frequencyof TDP-43 mislocalization in VP1-positive cells is ~80%, as shown in thegraph bar (n = 3). (B) TDP-43 is depleted in the nucleus and mislocalized tothe cytoplasm in VP1-positive neurons ((TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Problem posing, the generation of questions by learners, has been shown to be an effective instructional strategy for teaching–learning of complex materials in domains such as mathematics. In this paper, we demonstrate the potential of problem posing in two dimensions. Firstly, we present how problem posing can result in unfolding of knowledge and hence how it can be used as an instructional strategy. Then we present another problem posing-based activity as an assessment tool in an Introductory Programming course (CS1).To explore the potential of problem posing as an instructional strategy, we conducted field studies in the two CS application courses (Data Structures (DS) and Artificial Intelligence (AI)), in which we provided a semi-structured problem posing situation to students. We performed inductive qualitative research and development the questions generated by students using grounded theory-based qualitative data analysis technique. To explore the potential of problem posing as an assessment tool, we conducted a field study in CS1 wherein we employed another problem posing (PP)-based activity in a large class for assessing the learning of computational thinking concepts in an introductory programming course and analysed how performance in traditional assessment tools (quiz score) is related with performance in our non-traditional assessment tool .From the studies in DS and AI courses we found that students pose questions and unfold knowledge using seven strategies — Apply, Organize, Probe, Compare, Connect, Vary, and Implement. From the field study performed in the CS1 course we found that the quality of the problems posed (difficulty level) were mostly aligned to the traditional assessment results in the case of novice learners but not in the case of advanced learners. Problem posing (PP) refers to the generation of a new problem or a question by learners based on the given situation  when they want to clarify any muddy point related to the seed or any previous lecture, and (b) when they want to discover more knowledge related to or based on the contents of the seed instruction. We call this activity of question posing as “think” sub-phase.Share” sub-phase). Students are asked to review others’ questions and ensure that the question is not a repetition of their own question. Two students with similar questions were required to disambiguate the question set by removing one of the two similar questions. Students are not asked to discuss the answers with each other, as this would consume enormous amount of time.After each student has finished posing questions, they are asked to share their questions among each other : All the generated questions are collected, and the teacher answered each question one by one. While answering, the teacher is asked to answer “clarification” type questions first (“Clarify” sub-phase) and then answer “exploratory” type questions (“Explore” sub-phase). By “clarification questions,” we refer to all the questions which require reiteration of the content that has been explicitly been taught in the seed or in any other previous lectures in the course. By “exploratory questions,” we refer to the questions which lead to unfolding or construction of new knowledge. Clarification questions are addressed first because they could be the bottle-neck and pre-requisite for understanding the discussions about exploratory questions. During the “clarify” and “explore” sub-phases, the instructor has the liberty not to answer irrelevant and out-of-scope questions.We did a field study based on this preliminary design in an artificial intelligence (AI) course, and identified the required modifications in the strategy, which led to the revised design of the second DDR cycle.summarization” under phase 3. During the “summarization” sub-phase, the teacher summarizes and organizes all the concepts discussed during the “explore” and “clarify” sub-phases. The summarization is essential in order to enable students to make connections between the concepts discussed for a better learning  for the first DDR cycle was executed in artificial intelligence (AI) course, whereas the field studies  for the second and the third DDR cycles were administered in data structures classes. There were several types of data collected in each field study, but in this paper, the only data that we discuss is the questions generated by students during problem posing phases of field study 1 and field study 2, as the research focused on how much exploration-based learning took place.In the next sections, we discuss the final version of SQDL and the results obtained from the qualitative analysis of the questions.SQDL as a question posing-based teaching–learning strategy that enables students to regulate their learning by posing questions. Students’ pose questions based on the contents of an initial lecture (“Seed”) and determine which content/sub-topics that are conceptually related to the seed have to be taught next. After the last DDR cycle in the current version of SQDL, a single iteration of SQDL consists of three phases: (1) Initial Instruction Phase, (2) PP Phase, (3) Addressal (or next instruction) phase. Phase 2 is comprised of two sub-phases: (2.1) Think and Tag, (2.2) Share and tag. The third phase is comprised of three sub-phases: (3.1) Clarify, (3.2) Explore, (3.3) Summarize.We define In this sub-section we discuss the two implementations of SQDL (field study 1 and field study 2). We delimit our discussion to the collection and analysis of posed questions, with an objective of investigating how much exploration-based learning took place.We administered two PP sessions in a seventh semester engineering classroom of 35 students in an AI course. The first phase or the seed instruction phase was of 15 min. The topic covered in the seed lecture of the first AI session was “Comparison of Attributes of Intelligence in Utility based, Goal Based, and Simple Reflex agents”. The learning objective for the first session of the seed instruction was “By the end of the seed instruction student should be able to identify differences between simple-reflex, goal-based, and utility-based agents, with respect to the level and attributes of intelligence”.The topic covered in the seed lecture of the second AI session was “The architecture of learning agents”. Learning objective for this session of the seed instruction was “By the end of the seed instruction student should be able to identify the attributes of intelligence present in the learning agents”. The PP phases in the both sessions continued for 10 min. Students wrote their questions on paper slips and submitted to the TAs. Students were explicitly told about the types (clarification and exploratory) of questions that they could prefer to generate. We collected 25 distinct questions in the first session and 23 distinct questions in the second session.At the end of the AI session, students were asked to write down their feedback to the open-ended question, “How was today’s lecture different, good, and bad from other traditional lectures?” We received responses from 39 students.Similar to the AI session, we administered a PP session in a 4th semester engineering classroom of 60 students in a DS classroom. The instruction phase was executed for 15 min. Topics covered in the seed lecture were “Node Structure” and “Linking two nodes”. The learning objective of the seed instruction was “By the end of the seed instruction, student should be able to define, declare, construct, and access their own nodes and linkages between nodes using Java.” The PP phase continued for 10–15 min. Students were told to write their questions on paper slips, review the questions from their peers to remove the redundant questions, and submit the final question slips to the TAs. After discarding the irrelevant and remaining redundant questions, we were left with a corpus of 56 distinct questions.We have collected a total of 104 student questions from the two PP sessions. We first conducted an in-depth study of these question statements to find out what strategies students use to pose questions in the given semi-structured PP situation. We employed a grounded theory-based inductive qualitative research methodology. After the completion of the analysis, we found the answer to the more refined research question, “How do students use their prior knowledge/experience, and the knowledge from “seed” to generate a new question?” In this paper, we are not reporting the detailed analysis procedures and output, as it has been communicated for publication elsewhere. The result of the analysis was eight PP strategies that explain how students used prior, and the seed knowledge to come up with new questions.We further qualitatively analyzed each question to extract the knowledge type of the prior knowledge used to generate the question, knowledge type of the unfolded knowledge for any question, concept (topic/sub-topic) unfolded by any question.In this paper, we present a descriptive analysis of different PP strategies evident for the question set, the knowledge types of the information requested by the question set, and the amount of knowledge unfolded using PP. The next section contains the analysis results of the study.To analyze the open-ended responses from all students, we performed a content analysis of the text obtained from their feedback notes. We coded each response to answer three questions: (1) What are the advantages of the PP-based SQDL activity? (2) What are the disadvantages of the activity? (3) Reason behind advantage and/or disadvantages?Clarify’, all other seven strategies lead to knowledge unfolding. We are not reporting the analysis procedure, as it has been communicated for publication elsewhere.PP strategies emerged out of grounded theory-based inductive qualitative analysis of 104 questions are described in Table We found a range of topics/sub-topics from the traditional syllabus has been unfolded by the PP activities. The concept map of the concepts unfolded in the DS session is shown in Fig. The grey nodes represent the concepts which were taught in the instruction phase , while the red border around a node denotes that there were some clarification questions generated related to that particular concept. The green nodes show the concepts which were unfolded, i.e., they were not taught to students before. The green node with a dotted border is an unfolded concept which is out of the scope of traditional DS syllabus. The concepts denoted by the yellow nodes are the prior knowledge within the domain which was used during PP.We found that all of the 39 responses suggest that the activity was helpful in learning and creating interest. Students predominantly perceived that the activity was helpful to learning due to the following reasons: (a) The activity helped them to clarify their muddy points and learning basic details. (b) Due to the activity, students came across critical questions. (c) The activity covers all necessary topics. (d) It was better to explore topics more from students point of view. (e) It removed fear and hesitation of participating in the class, and increased active learning. The disadvantage of the activity as perceived by the students was that the activity was very much time-consuming. It would be interesting to study in our future research how much time does the traditional lecture require as compared to the time required by the SQDL approach to cover the same set of topics.RQ1: How can student-generated questions be used to assess the learning of Computer Programming concepts?RQ2: How does the quality of question(s) generated by a student relate to the score achieved by him/her in the traditional assessment?We conducted an in situ field study in the CS101 course. The main objective of the study was to investigate the effect of a 2-week scratch intervention on students’ learning and transitioning to C++. We aided the study with a PP-based nontraditional assessment tool. We designed a PP-based assessment activity, to investigate the learning of computational thinking concepts of introductory programming. The research questions that this study answered were:The PP situation of this activity was completely different than that described in the “After teaching CS1 for 4 weeks using Scratch and C++ as the programming languages, we conducted a traditional assessment in the form of a quiz. In the fifth week, during the lab sessions, each student was asked to generate two practice questions for the coming mid-term exam on which other students could work Fig. . Since PA team of TAs was assigned to talk to students and motivate them to brainstorm and generate questions that may lead to deeper application of the concepts taught in the class. There were 90 students per lab session, and there was one TA per 10 students. TAs were told to intervene whenever they found any student stuck in the activity, or sitting idle for long time, or busy doing some out-of-context work. It was the responsibility of a senior TA to coordinate with junior TAs to manage all the logistics in the lab session.The generated questions were analyzed qualitatively to answer our research questions. We analyzed the questions based on five different qualitative analysis themes, viz., creativity of the problem poser, difficulty of the problem, cognitive level of the problem, problem type, programming concepts Table .Table 4PWe designed qualitative rubrics to define different levels of creativity and difficulty of generated problems. This rubric  scores of the fourth week quiz using stratified attribute tracking diagrams  that they request and hence unfold, we found that students were able to unfold a large number of topics in a single iteration of SQDL. The benefits of PP activity are found to be twofold: (a) potential of addressing muddy points through the generation of clarification questions and (b) knowledge unfolding capability through generation of exploratory questions. As far as the extent of knowledge unfolding is concerned, it was evident that there were large numbers of concepts unfolded during SQDL sessions; still there is no metric to determine what should be called as “adequate” or “acceptable” coverage. This could be an interesting future research objective. The responses of the students to the open-ended feedback question “How was today’s activity helpful?” in the class confirm the above. Some of the responses are given below:SQDL is helpful in student-driven unfolding of course contents which are conceptually related to the seed instruction. However, we do not expect students to ask questions and unfold topics which are conceptually unrelated to the seed concepts. Therefore, in addition to AI and DS, SQDL is suitable for all domains which has a large number of conceptually related topics. The types and distribution PP strategies employed may vary according to the nature of different domains. We believe that there exists potentially interesting research objective to investigate the variations in nature of questions posed across different domains.The second PP situation (PPE activity) was designed to explore the potential of problem posing as an assessment tool. We found that PP can be used to assess the learning of computational thinking concepts by students in the CS1 course. In the PPE activity, students generate questions and they also provide solutions/answers to them. This ensures that the concepts which are required to answer a question are understood by the students. We aggregated all these concepts that emerged from the generated questions and determined the frequency distribution of various concepts learned by the students. It should be noted that we did not assess the learning of any individual student on the topics around which (s)he has not generated questions. Though, PPE can be used to assess the learning of different concepts by the class, as a whole. We also attempted to study the relation of “understanding of programming”  with question quality . We found that for novice learners, the higher the score in the quiz, the lesser was the probability of generating low difficulty question. Interestingly, in the case of advance learners, we found a high probability of generating low difficulty questions by high quiz performers. This shows that the difficulty level can be used to assess the learning of novices, but not of advanced learners. Moreover, it is also possible that in addition to “understanding of programming” the “difficulty level” of the generated question might be affected by other factors. Although the results in the paper show some relation between the traditional assessment scores and PPE-based assessment, we do not claim any statistical correlation.With content analysis of questions for the concepts that any question relates to, PPE can be used in other domains for assessing the conceptual understanding. As far as the difficulty level and other quality parameters are concerned, different domains may need different rubrics for analysis. The use of PPE as an assessment tool shows that different qualitative aspects of questions can reveal a lot about different aspects of learning, and other cognitive and affective parameters. For example, the account of creativity shows how much students are able to relate the concepts to their prior  experiences. More of these aspects are to be identified to make PP useful for assessing a wide range of objectives.


In this paper we report upon the preparation and characterization of electrospun nanofibers of doped polyaniline (PANI)/poly(methyl methacrylate) (PMMA)/amino-functionalized graphene (Am-rGO) by electrospinning technique. The successful functionalization of rGO with amino groups is examined by Fourier transforms infrared (FTIR), X-ray photoelectron spectroscopy (XPS) and Raman microspectrometer. The strong electric field enables the liquid jet to be ejected faster and also contributes to the improved thermal and morphological homogeneity of PANI/PMMA/Am-rGO. This results in a decrease in the average diameter of the produced fibers and shows that these fibers can find promising uses in many applications such as sensors, flexible electronics, etc. Electrospinning is an efficient, relatively simple and low-cost process used to produce continuous nanofibers on a large scale, where the fiber diameter can be adjusted from nanometers to microns by applying a high voltage to a polymer solution from a micro-syringe pump ,2,3,4,5.Polyaniline (PANI) is one of the most conductive polymers, that has been used in many electronic, optical and electrochemical applications, due to its low cost, good environmental stability, redox reversibility, and electrical conductivity ,10. HoweGraphene is a potential nanofiller that can efficiently enhance the mechanical, thermal and electrical properties of polymer-based nanocomposites at a very low loading, useful for various novel applications due to its high thermal conductivity, superior mechanical strength, high specific surface area, excellent mobility of charge carriers and high chemical stability ,20,21. H2–(CH2)2–NH2) was utilized to functionalize graphene surfaces, which produced stitched graphene owing to the presence of two amine (–NH2) functionalities on both sides of the ethylene moiety [Herein, the ethylenediamine  Mw ~ 100,000 g·mol−1, camphor-10-sulfonic acid , N,N dimethylformamide , chloroform , ethylenediamine , were all purchased from Sigma-Aldrich, . Deionized (DI) water was used for all the experiments.Graphene oxide (GO), poly(methyl methacrylate) (PMMA) −1, and kept at 400 °C for 30 min under an argon (Ar) gas flow of 80 mL·min−1; secondly, the temperature was increased from 400 to 650 °C at a rate of 5 °C·min−1, and kept at 650 °C for 30 min under an Ar gas flow of 80 mL·min−1. Finally, the reduced GO samples were naturally cooled to room temperature without argon.Commercial graphene oxide (GO) was reduced by thermal annealing treatment . First, The rGO made in the previous step, where 150 mg of rGO was mixed with 10 mL of EDA, in a vessel under vigorous stirring. The reaction was continued for 24 h under reflux at 80 °C. Afterwards, the aminated-rGO (Am-rGO) was centrifuged at 10,000 rpm for 1 h and was thoroughly washed with deionized water, filtered, and dried in a vacuum oven at 80 °C for 24 h .10 mg of the Am-rGO was dispersed in 2.96 g of DMF by sonication for 1 h. 100 mg of PANI was mixed with 130 mg of HCSA to dope it and dissolving it in 14.78 g of chloroform. The solution was stirred constantly for 6 h and subsequently filtered using Whatman Puradisk PTFE syringe filter  to remove the particulate matter. Then, the Am-rGO solution was mixed with PANI solution and subsequently 85 mg of PMMA (as a carrier polymer) was added to the solution and stirred for 24 h to form the solution for electrospinning see . The PAN−1 resolution. The spectra of the samples were recorded over a wavenumber range of 4000–650 cm−1. Raman microspectrometer and the electron diffraction (SAED) patterns were utilized to investigate the structural changes of GO, rGO, and Am-rGO. Characterization of graphene specimens were performed by Raman microspectrometer with a Renishaw InVia Raman microscope  at an excitation laser wavelength of 514 nm. Raman spectroscopy is a powerful non-destructive tool for studying disorder and defects in crystal structure, it is often used to characterize microstructure of carbon materials. All specimens were deposited on glass slides in powder form without any solvent. For SAED patterns characterization, the graphene specimens were scooped onto a transmission electron microscopy (TEM) copper grid with supporting carbon film  directly. The dispersion characteristics of rGO and Am-rGO were measured by ultraviolet visible (UV–Vis) spectrophotometer at ambient temperature utilizing Infinite 200 PRO  cuvette reader. The chemical composition of the samples were determined by X-ray photoelectron spectroscopic (XPS) analysis using a VG Scientific ESCALAB 3 MK II X-ray photoelectron spectrometer  using an Mg Kα source .In order to ensure the presence of functional groups that should be present from the successful reduction of GO to rGO and functionalization of rGO with amino group, the Fourier transform infrared (FTIR) spectroscopy analysis was undertaken using Perkin Elmer 65 FTIR-ATR instrument . A total of 128 scans were accumulated for signal averaging of each IR spectral measurement with a 4 cm−1.The scanning electron microscope  at an operational voltage of 2 kV was used to study the morphology of electrospun fibers. Fiber diameters were calculated using Image-Pro Plus® software by taking an average of about 300 fibers. To confirm the presence of graphene sheets in the nanofibers of PANI/PMMA/Am-rGO, transmission electron microscopy  was used. For TEM observation, fibers were directly deposited onto a TEM copper grid with supporting carbon film . Thermogravimetric analysis (TGA) was conducted under nitrogen atmosphere using Q5000 TGA  in the temperature range of 20–900 °C, with a heating ramp of 10 °C·min3/DMF (5:1). As shown in 3/DMF in the presence of amino groups  stretching at 1601 cm−1; the C–O (epoxy) stretching at 1040 cm−1 and the C–O (phenolic) stretching at 1213 cm−1 [−1 is ascribed to the skeletal vibration of unoxidized sp2 graphitic domains. After the thermal reduction of GO, the skeletal vibration of sp2 graphitic domain still remains shifts to 1573 cm−1. Besides, some residual presence of bands at 1710, 1150, and 1280 cm−1 were detected providing evidence of the different types of oxygen functionalities in the rGO and their decreases in intensity and others vanished due to thermal reduction [−1; the C–N stretching vibrations at 1180 and 1120 cm−1; and the C=O stretching vibrations of carboxyl group at 1725 cm−1. Furthermore, the Am-rGO has peaks of the C–H stretch of alkyl chain at 2918 and 2854 cm−1; and the C–O stretching in hydroxyl groups at 1015 cm−1. The FTIR spectroscopy results indicate that the chemically functionalized graphene (Am-rGO) was successfully synthesized. Similar results for functionalization of graphene with amino groups have been previously reported in literature [FTIR spectroscopy was performed on GO, rGO and Am-rGO in order to ensure the presence of functional groups that should be present from the successful reduction of GO to rGO and functionalization of rGO with amino groups see a. Differ213 cm−1 ,30. The eduction ,30. In tterature ,30.2 carbon forms system, and it is obtained from the first order Raman scattering [−1 owing to the oxygenation of graphite, which results in the formation of sp3 while, the D band is presented at 1350 cm−1 because of the reduction in size of the sp2 domains by the creation of defects, and distortions during oxidation [−1 and the D band positions remained unchanged at 1350 cm−1, respectively. The G band appears in lower frequency due to the increased number of sp2 carbon atoms following reduction of GO. The intensity ratio of D and G band ID/IG is slightly increased from (0.89) in GO to (0.93) in rGO, demonstrating a decrease in the size of the in-plane sp2 domains after reduction, and can be explained that the thermal redaction creates many new graphitic domains, that are more numerous in number and smaller in size [D/IG intensity ratio (0.97) than the rGO, which is attributed to the formation of the chemical bond between amino groups and basal planes of the rGO. This corresponds to other results reported for functional graphene [Raman spectra was employed to analysis the graphitic structures of of GO, rGO, Am-rGO, as shown in attering ,32, and attering ,32. As exidation . Moreove in size ,34. Whergraphene .2) at 399.7 eV, (C–N–C) at 400.4 eV, and (C–N+–C) at 401.6 eV  at terature .The morphology and microstructure of the GO, rGO and Am-rGO and the electron diffraction (SAED) patterns in the selected area were analyzed by TEM see a–f. The SEM was used to characterize the fabricated PANI/PMMA and PANI/PMMA/Am-rGO nanofibers see a–d. It iTEM was conducted to confirm the presence of the graphene filler in the nanofibers. 2 atmosphere in temperature range between 20 and 900 °C, with a heating ramp of 10 °C·min−1. GO is thermally unstable resulting in three stages of weight loss. In the first stage, a rapid weight loss occurs at about 173 °C, mostly attributed to the removal of the trapped water molecules and epoxy oxygen functional groups. The second stage occurs at 515 °C which can be attributed to the removal of phenolic groups and decomposition of sp3 hybridized carbon atoms located at the defect site of GO. These results were congruent with other studies presented in literature [TGA was performed to observe the thermal stability of the rGO, Am-rGO and electrospun PANI/PMMA and PANI/PMMA/Am-rGO nanofiber mat see a,b, respterature ,37. On tterature ,37. TherIncorporating a small amount of Am-rGO in PANI nanofibers improves its thermal stability. As shown in In this study, Am-rGO was successfully prepared and electrospun nanofibers of PANI/PMMA with amino-functionalized graphene were prepared by a simple electrospinning technique. The FTIR, XPS and Raman spectroscopy analysis confirmed the successful functionalization of the graphene with amino groups, while the TEM observation demonstrated that the addition of amino-functional groups to graphene generated less damage to the graphitic structure of the graphene. SEM micrographs indicated the formation of PANI/PMMA/Am-rGO nanofibers with a diameter ranging between 35 and 133 nm, with a general uniform thickness along the nanofibers. TGA measurements show an improvement of the thermal stability of the PANI in the presence of graphene. In conclusion, the resulting non-woven porous mats with amino-functionalized graphene result in electrospun nanofibers that can be used in future technological applications in various fields.


A properly strained graphene monolayer or bilayer is expected to harbour periodic pseudo-magnetic fields with high symmetry, yet to date, a convincing demonstration of such pseudo-magnetic fields has been lacking, especially for bilayer graphene. Here, we report a definitive experimental proof for the existence of large-area, periodic pseudo-magnetic fields, as manifested by vortex lattices in commensurability with the moiré patterns of low-angle twisted bilayer graphene. The pseudo-magnetic fields are strong enough to confine the massive Dirac electrons into circularly localized pseudo-Landau levels, as observed by scanning tunneling microscopy/spectroscopy, and also corroborated by tight-binding calculations. We further demonstrate that the geometry, amplitude, and periodicity of the pseudo-magnetic fields can be fine-tuned by both the rotation angle and heterostrain. Collectively, the present study substantially enriches twisted bilayer graphene as a powerful enabling platform for exploration of new and exotic physical phenomena, including quantum valley Hall effects and quantum anomalous Hall effects. Precisely strained graphene layers can enable observation of periodic pseudo-magnetic fields with high symmetry. Here, the authors report experimental tuning of large area periodic pseudo-magnetic fields within twisted bilayer graphene and massive Dirac electrons having circularly localized pseudo-Landau levels. In particular, it has been predicted that a non-uniform strain distribution imposed on graphene arising from either external stress2 or interfacial coupling4 can induce a strong gauge potential that in turn can act as a pseudo-magnetic field (PMF) on the Dirac electrons. Indeed, it has been demonstrated experimentally that locally strained graphene in the form of nanobubbles can induce PMFs, as manifested by the emergent pseudo-Landau levels observed using the scanning tunneling microscopy/spectroscopy (STM/S)6. More recently, existence of large-area, spatially distributed PMFs has also been reported for single-layer graphene on a black phosphorus substrate, which provides strain textures due to the mismatched symmetries and lattice constants of the heterostructure7. Separately, intensive theoretical and experimental studies have demonstrated that low-angle twisted bilayer graphene (TBG) can exhibit a variety of exotic phenomena, including superconductivity and quantum phase transitions19. In addition, it has been reported that a small uniaxial heterostrain in low-angle TBG can suppress Dirac cones and lead to the emergence of a zero energy resonance20. In practice, low-angle TBG itself possesses large-scale, natural, and periodic strains due to the incommensurate moiré superstructures21. Such strain has been theoretically studied to significantly affect the electronic properties of the large-scale moiré pattern23. However, yet to date, experimental explorations of such natural and intrinsic strain effects arising from lattice relaxations in the strongly coupled homostructural system, especially the pseudo-magnetic behaviors, are still lacking25.Strain in graphene can be served as an effective tuning parameter in tailoring its exotic properties reflected by different degrees of freedom such as spin and valleyk-space, and can be further tuned, together with the PMFs, by the twist angle and uniaxial heterostrain in the bilayer system. Indeed, the existence of periodic PMFs in such hexagon-structured system provides a possible platform to further explore quantum anomalous Hall effects if a tiny external magnetic field is applied to break the time-reversal symmetry26.In this letter, by combining STM/S experiments and large-scale tight-binding calculations, we study the electronic properties of TBG with extremely small twist angles , the result reproduces the energy peaks that appear in the measured spectra , and their effects on the electronic properties remain to be fully explored.Collectively, the central findings achieved here may have important far-reaching implications. First of all, the existence of PMFs in TBG systems may finally offer testing grounds for observing quantum anomalous Hall effects as originally proposedThe bilayer graphene samples were prepared by chemical vapor deposition on Cu–Ni alloy substrates using 20, and has been shown to reproduce accurately the differential conductance d = 1.42 Å is the nearest carbon-carbon distance, h = 3.349 Å is the interlayer distance, −1, and 34. To reach a precision in energy of 3.5 meV, we have computed 10,000 steps in the continued fraction built in a super-cell of 15 millions of orbitals with periodic boundary conditions.The full tight-binding model by considering Supplementary InformationPeer Review File


The results demonstrated that the MoS2/graphene-coated separator is contributing to inhibit the shuttling phenomenon of polysulfides and improve the integrity of sulfur electrode. The initial discharge capacity of the battery using MoS2/graphene-coated separator at 0.2 C was up to 1516 mAh g−1. After 100 cycles, a reversible capacity of 880 mAh g−1 and a coulombic efficiency of 98.7% were obtained. The improved electrochemical behavior can be due to the nanostructure and Mo-S bond of the MoS2/graphene composite, which can combine physical shielding and chemisorption to prohibit the shuttle effect of polysulfides. The results prove that the MoS2/graphene-coated separator has the potential for feasible application in Li-S batteries to enhance their electrochemical performance.Lithium-sulfur (Li-S) batteries are the most prospective energy storage devices. Nevertheless, the poor conductivity of sulfur and the shuttling phenomenon of polysulfides hinder its application. In this paper, flower-like MoS Then 1 2/graphene-modified separator, a slurry was prepared with MoS2/graphene composite, carbon black and poly(vinylidene fluoride) (PVDF) in N-methylpyrrolidone (NMP) with a mass ratio of 8:1:1. The homogenous slurry was then pasted on a microporous membrane (Celgard 2400) which was employed here to provide mechanical strength. After drying at 70 °C under vacuum for 12 h, the MoS2/graphene-modified separator was stamped into round pieces with the size of 19 mm in diameter. The mass loading of the MoS2/graphene was 0.80 mg cm−2.To fabricate MoSTo prepare the S/graphene cathode material, 50 mL GO suspension was sealed in a 100 mL Teflon-lined autoclave and maintained at 180 °C for 12 h. After cooling to room temperature, the as-prepared RGO suspension was freeze-dried in vacuum overnight to evaporate the water solvent. Afterwards, the black precipitate was ground into powder and then RGO was obtained. Then, RGO and sublimed sulfur were mixed in the weight ratio of 75:25 using ball milling method. Finally, the mixture was then transferred into a 10 mL Teflon-lined autoclave and further maintained at 155 °C for 12 h to obtain the S/graphene composite.2/graphene-modified separator before and after cycling. The morphology of the samples was explored by transmission electron microscopy  and scanning electronic microscope  equipped with an energy dispersive spectroscopy (EDS) system. The dynamic mechanical analysis  was used to measure the tensile strain of the separators.The phase components of the composites were observed with X-ray diffraction  measurement. The X-ray photoelectron spectroscopy  was employed to investigate the compositions of the MoS3 dissolved in the mixture of dioxolane (DOL) and 1,2-dimethoxyethane (DME) (1:1 ratio vol%) were employed. The MoS2/graphene-modified separator was inserted between the cathode and the lithium foil with the MoS2/graphene coated side of the separator facing the cathode. The pristine Celgard 2400 was also used for comparison. The galvanostatic cycling experiments were conducted on a battery cycler  with a cut-off potential of 1.7–2.8 V (vs. Li+/Li). Cyclic voltammetry (CV) was tested on a CHI611C potentiostat  within the voltage range of 1.7–2.8 V with a scan rate of 0.1 mV s−1. Electrochemical impedance spectroscopy (EIS) was performed on a CHI611C potentiostat in the frequency range of 100 kHz–0.01 Hz.The cathode was prepared as follows. The sulfur/graphene composite, carbon black and PVDF (8:1:1 wt ratio) were mixed with NMP as the solvent. After grinding for 60 min, the resultant slurry was tape-cased onto aluminum foil. After drying at 60 °C under vacuum for 10 h, the obtained composite covered electrode was stamped into disks with diameter of 14 mm. The evaluation of electrochemical performance was carried out in CR2032-type coin cells and the assembly of cells was finished in an Ar-filled glovebox . The lithium foils served as the counter electrodes. For the electrolyte, 1 M lithium bis(trifluorometha-nesulfone)imide (LiTFSI) and 0.1 M LiNO−1, which correspond with the D band and G band of graphene, respectively. Moreover, D band is corresponding to the disordered sp3 structure and G band is assigned to the sp2 hybridized graphitic structure. The ID/IG value of S/graphene is 1.17, indicating a highly defective graphite structure, which is beneficial to fast electron transfer [−1, indicating the inclusion of sulfur in the composite [Raman characterization of S/graphene composite was shown in transfer . Moreoveomposite .2 and MoS2/graphene composite were characterized using X-ray diffraction (XRD). There are five similar diffraction peaks observed in two samples. According to the standard Powder Diffraction File (PDF) files of #75-1539, conspicuous peaks at 14.0°, 33.4°, 36.2°, 43.6° and 58.1° are indexed to (002), (100), (102), (103) and (110) planes of crystalline MoS2 respectively, indicating that the crystal structure of MoS2 was efficiently retained in the spray drying process. The peak of graphene was not obtained. As presented in 2 has been coated by graphene, which was further demonstrated by SEM and TEM results.XPS measurements were performed to investigate the surface chemical composition of the composite. The full spectrum in 2 and MoS2/graphene composite is revealed by SEM images and energy dispersive X-ray spectroscopy (EDS) mapping. As presented in 2 exhibits a flower-like structure with the average size of around 1.1 μm in diameter. The flower-like structure consisted of nanosheets with the thickness of around 30 nm. 2 nanospheres were effectively wrapped by graphene, and the three-dimensional flower-like structure was remained in MoS2/graphene composite. However, the diameter of the MoS2/graphene sphere is about 3.2 μm, which is much larger than that of MoS2. EDS mapping of Mo, S and C elements in 2 and graphene are tightly bonded.The morphology of as-prepared MoS2. The flower-like structure is clearly observed from the wrinkles. The inset of 2. 2/graphene composite, revealing that some nanospheres of MoS2 are well wrapped by thin graphene sheets. As illustrated by the HRTEM image in the inset of 2 and (200) planar spacing of graphene, respectively. The results indicate a strong interfacial bonding between graphene and MoS2, which can shorten electron/ion transport passage and supply more adsorption surfaces.The insight into inner structure of the samples was provided by transmission electron microscopy (TEM) analysis. 2/graphene-coated separators are investigated by SEM. As presented in 2/graphene-coated separator. Uniform MoS2/graphene spheres with the average size of 3.6 μm in diameter were observed. The contact angle of the MoS2/graphene-coated separator is 0° as shown in the inset in 2/graphene-coated separator with tiled and folded state are exhibited in 2/graphene-coated separator . The lower resistance of the batteries with MoS2/graphene-coated separator results from decreased insulating materials deposited on the surface of the electrode, leading to an excellent cycling stability.To study the kinetics process, EIS measurements for the batteries with pristine separator and MoS2/graphene-coated separator and the pristine separator were characterized. The batteries were rested for 72 h after the 10th cycle at 0.2 C. 2/graphene-modified separator shows a small attenuation from 2.3 to 2.26 V during the rest time, indicating the effective suppression of the self-discharge by the composite separator. 2/graphene-coated separator exhibited a decline rate of 13.52%.Since the self-discharge is one of the major defects of Li-S batteries, the self-discharge behavior of the electrodes with the MoS2/graphene-coated separator after 100 cycles at 0.2 C is detected and the results are exhibited in 2/graphene composite still remain uniform distribution on the surface, indicating that the coating is flexible and tightly coated to avoid dropping out from the separator during cycles. No obvious cluster was observed and the diameter of the MoS2/graphene sphere is about 4 μm. The corresponding EDS elemental maps (The morphology of the MoStal maps c further2/graphene-coated separator after 100 cycles at 0.2 C was presented in 2/graphene-modified separator. Here the peaks between 169.8 and 168.7 eV are assigned to the sulfates, which can be attributed to brief air exposure of the sample in the XPS loading process. Furthermore, the peaks at 163.0 and 161.7 eV prove the existence of polysulfides in the MoS2/graphene-modified separator, consistent with the previous SEM results. Therefore, we believe that the migrating polysulfide species can diffuse through the MoS2/graphene-modified separator and be effectively captured during cycling.XPS S 2p spectrum of the MoS2/graphene composite is synthesized on the routine separator via slurry coating process to substantially enhance the electrochemical capability of Li-S battery. The MoS2/graphene-coated separator serves as a high efficiency ionic sieve that can block the transportation of the polysulfide anions and effectively decreases the shuttle effect. In addition, the introduction of MoS2/graphene-coated separator possessed higher sulfur utilization as a result of the recycling of entrapped active materials. These advantages can significantly improve the specific capacity and cycling stability of battery, with an initial discharge capacity of 1516 mAh g−1 and a higher reversible capacity of 880 mAh g−1 with coulombic efficiency of 98.7% after 100 cycles at 0.2 C. Therefore, the separator modification by MoS2/graphene composite will provide an effective method to suppress the shuttling phenomenon and enhance the electrochemical capability of Li-S batteries.In summary, a multi-functional separator modified by MoS


The hierarchical structure of the communities is studied by the Infomap method, and most of the irreducible communities are found to be at the second level. The composition of some of the major communities, including overexpressions regarding their industrial or regional nature, and the connections that exist between the communities are studied in detail. The findings obtained here cause us to question the validity and accuracy of using the conventional input-output analysis, which is expected to be useful when firms in the same sectors are highly connected to each other.This paper studies the structure of the Japanese production network, which includes one million firms and five million supplier-customer links. This study finds that this network forms a tightly-knit structure with a core giant strongly connected component (GSCC) surrounded by IN and OUT components constituting two half-shells of the GSCC, which we call a A macro economy is the aggregation of the the dynamic behaviour of agents who interact with each other under diverse external (non-economic) conditions. Economic agents are numerous and include consumers, workers, firms, financial institutions, government agencies, and countries. The interactions of these agents result in the creation of economic networks, where nodes are economic agents, and links (edges) connect agents that interact with each other. Therefore, there are various kinds of economic networks depending on the nature of the interactions, which form an overlapping multi-level network of networks. Thus, any evidence-based scientific investigation of the macro economy must be based on an understanding of the real nature of these interactions and the economic network of networks that they form. This concept also applies to the micro-level perspective of economic agents: without knowing who a firm trades with, how can anyone hope to determine the future of that firm? Therefore, it is highly important to use actual network information when studying economic dynamics with either agent-based modelling/simulations or other means of systematic studies such as determining the debt-rank of an economic agent –5. Witho“walnut” structure. This type of structure is quite different from what is expected because of the existence of the IN-giant strongly connected component (GSCC)-OUT components: In the trade network, the flow of materials and goods begins with imported/mined/harvested raw materials such as oil, iron, other metals and food. Firms who engage in this business form the IN components. These compnoents are then processed to become various products such as semiconductors or powdered food by firms, which are considered to be GSCC components, before they are made into consumer goods by firms, which are considered to be the OUT components. One might think that the existence of IN-GSCC-OUT components is similar to a web network that has a bow-tie structure [In this paper, we study the structure of one of the most important networks, the production network, which is formed by firms (as nodes) and trade relationships (as links) –9. In thtructure . Howevertructure , 12.In previous studies , 8, the In our paper, we conduct a level-by-level analysis and identify both communities and “irreducible” communities (communities that are not decomposed into subcommunities at the lower level). We also study the overexpression of some of the major communities to identify both the industrial sector and the regional decomposition. The complex nature of the links that exist between the communities are also studied. A discussion and the conclusion as well as suggestions for future research are provided at the end. Some of the supporting materials are included as Appendices.Our data for the production network are based on a survey conducted by Tokyo Shoko Research (TSR), one of the leading credit research agencies in Tokyo, and was supplied to us through the Research Institute of Economy, Trade and Industry (RIETI). The data were collected by TSR by means of inquiry from firms who represent the top five suppliers and the top five customers. Although the large firms that have many suppliers and customers submitted replies that are incomplete, these data are supplemented with data on the other side of trade: smaller firms submit replies that include data on large firms, who are important trade partners. By combining all the submissions from both side of trade into one database, large firms are connected to numerous smaller firms, which provides a good approximation of the real complete picture. One might worry because some of the trades last for only a short time and sometimes they only occur once, such as when a firm seeks a good deal for just one particular occasion, and thus cast doubt on the definition of the trade network. The form of data collection used for this study solves this problem: it is most implausible that replies containing data on a one-time trade are included, instead, data on firms that maintain a certain trade frequency are likely to be listed. In this study, we use two datasets: ‘TSR Kigyo Jouhou’ (firm information), which contains basic financial information on more than a million firms, and ‘TSR Kigyo Soukan Jouhou’ (firm correlation information), which includes several million supplier-customer and ownership links and a list of bankruptcies. Both of these datasets were compiled in July 2016. (Some of the earlier studies on the production network include ).i → j denotes a supplier-customer link, where firm i is a supplier for another firm j, or equivalently, j is a customer of i. We extracted only the supplier-customer links for pairs of “active” firms and excluded inactive and failed firms by using an indicator flag for them when we retrieved the basic information. We eliminated self-loops and parallel edges (duplicate links recorded in the data), to create a network of firms (as nodes) and supplier-customer links (as edges). The network has the largest connected component when it is viewed as an undirected graph, which is the giant weakly connected component (GWCC) that includes 1,066,037 nodes  and 4,974,802 edges.In this study, This study not only analyzes the network but considers several attributes of each node: the financial information in terms of firm size, which is measured as sales, profit, number of employees and the firm’s growth; the major and minor classifications of industrial sectors, details regarding the firm’s products, the firm’s main banks, the principal shareholders, and miscellaneous other information including geographical location. For the purpose of our study, we focus on two attributes of each firm, namely the industrial sector and the geographical location of the head office.The industrial sectors are hierarchically categorized into 20 divisions, 99 major groups, 529 minor groups and 1,455 industries . See Table A in In terms of the flow of goods and services (and money in the reverse direction), the firms are classified in three categories: the “IN” component, the “GSCC”, and the “OUT” component. This structure is called “bow-tie” in a well-known study on the Internet . The GWCGWCC the giant weakly connected component: the largest connected component when the network is viewed as an undirected graph. An undirected path exists for each arbitrary pair of firms in the component.GSCC the giant strongly connected component: the largest connected component when the network is viewed as a directed graph. A directed path exists for each arbitrary pair of firms in the component.IN The firms through which the GSCC is reached via a direct path.OUT The firms that are reachable from the GSCC via a direct path.TE “Tendrils”; the remainder of the GWCCIt follows from the definitions thatWe, however, find it far more appropriate to call this structure a “Walnut” structure, as “IN” and “OUT” components are not as separated as in the two wings of a “bow-tie” but are more like the two halves of a walnut shell, surrounding the central GSCC core. This can be explained as follows. The number of firms in each component of the GSCC, IN, OUT and TE is shown in In contrast with the well-known “bow-tie structure” in the study conducted by   measures the per step average description length of the dynamics of a random walker migrating through the links between the nodes of a network with a given node partition C = {C1, ⋯, Cℓ} that consists of two parts. The first term arises from the movements of the random walker across communities, where H(C) is the average description length of the community index codewords given by the Shannon entropy. The second term arises from the movements of the random walker within the communities, where Ci, and i.The map equation method  is anothL(C).If the network has densely connected parts in which a random walker stays a long time, one can compress the description length of the random walk dynamics in a network by using a two-level codebook for nodes adapted to such a community structure; this is similar to geographical maps in which different cities recycle the same street names such as “main street’ . TherefoIn regard to the resolution limit problem, any two-level community detection algorithms including the map equation are not able to eliminate the limitation. However, the map equation significantly mitigates the problem as has been shown by a recent theoretical analysis . In prachttp://www.mapequation.org.Recently, the original map equation method has been extended to networks with multi-scale inhomogeneity. A network is decomposed into modules that include their submodules and then their subsubmodules and so forth. The hierarchical map equation  recursivNote that this study exclusively considers the community identification for nodes in our network. That is, each node belongs to a unique community at every hierarchical level. However, such community assignment may be too restrictive for a small number of giant conglomerate firms such as Hitachi and Toshiba because of the diversity of their businesses. The map equation is so flexible that it can detect the overlapping community structure of a network in which any node can be a member of multiple communities . HoweverMost real-world networks have a community structure . Such coH is used to measure the probability that X randomly selected nodes in community C of size NC will have attribute Q. The hypergeometric distribution H can be written asNQ is the total number of elements in the system with attribute Q. Further, one can associate a p valuep with NC,Q nodes, having attribute Q in community C with H by the following relation:We follow the procedure used in  to deterQ is overexpressed within community C if p is found to be lower than some threshold value pc. As we use a multiple-hypothesis test, we need to choose pc appropriately to exclude false positives. We assume that pc = 0.01/NA, as specified in [NA represents the total number of different attributes  for all the nodes of the system.The attribute ified in , which iified in . Here, NBy using the Infomap method , 12, we We visualize the hierarchical decomposition of the whole network into communities and their subcommunities in 1”. At the lower levels, the rank of the size is added after ‘:’. For example, community “C1:5” is the fifth largest 2nd level community among all the 2nd-level communities that belong to the largest top-level community C1.For the purpose of making the following discussion of communities transparent, let us adopt the following indexing convention: At the top modular level of the hierarchical tree structure, the communities are indexed by their rank in size (the number of firms in the community). Thus, the largest community at the top level is denoted as “CD(s) indicates the fraction of communities at the top level having a size of at least s, as shown in The complementary cumulative function Aij is the total number of links spanning from communities i to j and Aji and that of the opposite links. If the linkage between communities i and j is completely polarized, then Pij becomes ±1 depending on its direction; if the linkage is evenly balanced, then Pij = 0. If we assume that the links have no preference with respect to their direction as a null hypothesis, then the null model predicts that the polarization ratio for the connections between communities i and j fluctuates around 0 with the standard deviation σ given byLij = Aij + Aji is the total number of links between the two communities. If we focus on intercommunity linkages with Lij ≥ 100, we see that the ones whose direction is polarized in a statistically meaningful way occupy 86.7% of their total. The corresponding share of intercommunity linkages is 70.1% for Lij ≥ 10. Most of the connections between communities with more than 100 links are significantly polarized in reference to the random orientation model for intercommunity links.The map equation is a method that can be used to divide a directed network into communities in which nodes are tightly connected in both directions. Due to the nature of the network, the flows across communities thus detected should be biased in an either direction. We find the overexpression of the attributes in 1st level communities to determine the factors that play a crucial role in the formation of such communities. Our study considers both the location and the sector attributes. The location attributes are divided into 9 regions, and the sector attributes are categorized in 20 divisions. The details about the sixth largest 1st level communities and the overexpressed attributes within it are tabulated in The largest community: Manufacturing sectorsThe second largest community: Food sectorsThe third largest community: Construction sectorsThe fourth largest community: Wholesale and retail tradeThe fifth largest community: IT sector and scientific research, primarily based in TokyoThe sixth largest community: Medical and health careThe positions of the communities on the horizontal line clearly reflect their characteristics in terms of the walnut structure, as shown in At the 2nd level, some of the top level communities are decomposed to several subcommunities as shown in Tables D and E in D(s) ∼ sγ+1− with γ = 2.50 ± 0.02. The results indicate that the size of the communities is highly heterogeneous and spans over several orders of magnitude.The cumulative distribution of the community size at this level is plotted in C2:1, transport and postal activities, accommodations, eating and drinking services, living related and personal services, and amusement services dominate the overexpressed sectors, which are mainly based in urban regions (Tokyo and Chubu). The manufacturing, wholesale and retail trades in Tokyo and the Kansai region are overexpressed in C2:2. Wholesale and retail trade dominate the overexpressed attribute in C2:3, C2:4 and C2:5. A detailed account of the results is provided in We also analyzed the overexpressions of selected subcommunities. In terms of subcommunities, we observe wholesale and retail trade is the dominate overexpress attribute of the five largest subcommunities of the largest community. The Kansai region is the only overexpressed region in the 2nd largest subcommunity of the largest community. In The network diagram in x1, x2, and x3, respectively. The walnut composition of the community is described by point  on the plane of x1 + x2 + x3 = 1 in three-dimensional space. One can thereby establish one-to-one correspondence between a point inside an equilateral triangle and a composition of the three walnut components. The averaged composition of all the firms in the selected communities  is given by Although the IN components tend to to merge with the GSCC, we can see the large circle at the vertex of As is mentioned in the Introduction Section, detecting communities in the supply-chain network is crucial for understanding the agglomerative behavior of firms. This type of research is important because the detected communities are densely connected, and it is plausible that these firms affect each other through the links.On the other hand, industrial sectors commonly label firms, and these labels are widely used in the economics literature. If there is no difference between the detected communities and the industrial sectors, then there is no reason to make an effort to detect these communities. Therefore, in this section, we show how the detected communities are different from industrial sectors in terms of the interconnections between the groups.Although different classifications are used for industrial sectors, we discuss the one used in the input-output table . We use As previously mentioned, there are 209 communities in the 1st level and 66,133 communities in the 2nd level. On the other hand, the input-output tables have 13, 37, 108, 190, and 397 sectoral classifications, which are nested. We choose to compare 209 communities and 190 industrial sectors because these numbers are comparable.First, we counted the number of links between the communities and the industrial sectors. If the intra-links within the groups are dominant, then the diagonal elements of these matrices should have high density. As is shown in We can conclude that the detected communities in this paper explicitly illustrate the agglomeration of firms based on supply-chain networks rather than industrial sectors, which is more commonly used to categorize firms. This result also tells us that communities with densely connected firms consist of various industrial sectors, and they have their own economies, i.e., small universes.In this paper, we do not weight the links of the network. However, obviously, each transaction has a value, and there is a diversity of transactions. We can estimate the weights by using the sales of the firms. If we have totally different results with the results we have obtained here, a further analysis might be necessary. However, the additional analyses based on weighting the links in the networks do not show any significant difference. The details of these results are shown in We analyze the overall structure and hierarchical communities embedded in the production network of one million firms and five million links that represent trade relationships in Japan in 2016, with the aim of simulating the macro/micro level dynamics of the economy.For the former, we find that the IN and OUT components (20% and 26% of the firms) form tight shells (semi-spheres) around the GSCC component, which we call a “walnut” structure rather than a “bow-tie” structure, which is well-known for representing web networks and other type of networks that have loose wings made of IN and OUT components.For the latter, we use the Infomap method to detect a hierarchy that includes 5 layers of communities, of which most of the irreducible (those that do not have any lower level subcommunities) belong to the 2nd level. Furthermore, the size distribution of the 2nd level communities show clear power-law behavior at the large end. In addition to the large number of irreducible communities made primarily of GSCC components and those that exist in IN shells or Out shells, there is a fair number of communities made of IN and GSCC components, GSCC and OUT components, and even IN and OUT components. These communities are expected due to the walnut shape of the overall structure: IN and OUT components are not far from each other as they are in the bow-tie structure, but they form tight shells, whose ends are closely woven with each other. Furthermore, we examine the overexpression of the major communities in terms of industrial sectors and prefectures and find that they are not formed within a sector but span several sectors and prefectures. These communities have various shapes: in some cases, they are formed around goods and services related to a particular item, such as food. Sometimes these communities are made of small firms connected with a major hub such as a large construction company in a particular prefecture or a medical insurance agency.These findings have major implications for the study of the macro economy: Consider an economic crisis. Once this crisis starts, whether it is due to a natural disaster in a particular region of a country or a major failure of a large company, it is expected that it initially affects the community in which this region or company is located. Then the effects of this crisis will spread to other neighboring communities. This analysis is very different from input-output analysis and is expected to be useful because an input-output analysis is based on the assumption that firms in the same sectors are well-connected with each other. In contrast, what we find is that the effects of a crisis will spread throughout communities rather than industries. The hierarchical community structure studied in this paper can be immediately applied to the analysis of large-scale modelling and simulation: the macro economy of a country or countries is an aggregation of products that economically affect the trade network as well as a multitude of networks of networks. Constructing models that span all the networks would be an interesting but exhaustive elaboration of this work. Instead, we may study one community at a time and then connect the results to obtain an overall picture. Research in this direction has already begun and will appear in the near future , 31, 32), 3231, 3S1 Appendix(PDF)Click here for additional data file.


At low temperatures, however, it was found that the carbon diffusion rate (CDR) on the metal catalyst surface has a greater impact on the number and uniformity of graphene layers compared with that of the carbon solid solubility. The CDR decreases rapidly with decreasing temperatures, resulting in inhomogeneous and multilayer graphene. In the present work, a Ni–Cu alloy sacrificial layer was used as the catalyst based on the following properties. Cu was selected to increase the CDR, while Ni was used to provide high catalytic activity. By plasma-enhanced CVD, graphene was grown on the surface of Ni–Cu alloy under low pressure using methane as the carbon source. The optimal composition of the Ni–Cu alloy, 1:2, was selected through experiments. In addition, the plasma power was optimized to improve the graphene quality. On the basis of the parameter optimization, together with our previously-reported, in-situ, sacrificial metal-layer etching technique, relatively homogeneous wafer-size patterned graphene was obtained directly on a 2-inch SiO Graphene, since its “discovery” in 2004, has attracted worldwide attention because of its excellent properties, such as high carrier mobility, high mechanical strength and high transmittance ,2. SeverIn this work, we studied the growth of graphene by plasma enhanced CVD at a low temperature (~600 °C). Thin films of Ni–Cu alloy were chosen as catalysts. Cu was used to increase the carbon diffusion rate (CDR), while Ni was used to provide high catalytic activity. The plasma power was optimized, since it was found to have a significant impact on the graphene quality. We found that at a low temperature, the CDR, instead of the carbon solubility, played the dominant role in determining the number of graphene layers and uniformity. The CDR sharply decreased at decreasing temperature, leading to inhomogeneous and multilayer graphene formation. Nevertheless, relatively homogeneous, wafer-sized patterned graphene was still achieved after process parameter optimization. Our findings will be useful for further growth optimization, especially at low temperatures, because the information available in literature that can serve as guidelines for low temperature graphene growth is very limited.2. The equipment used for the deposition of Ni and Cu films was a Denton Vacuum sputtering platform. Radio frequency source was used for the sputtering. Ni–Cu alloy was prepared by depositing Ni and Cu films successively, followed by annealing at 600 °C for 40 min in a high-vacuum annealing furnace to make them alloy and grow the grains. When sputtering, the substrate was kept at 30 °C. The sputtering power of Ni and Cu is 300 W, the corresponding direct-current biases are 142 V for Ni and 188 V for Cu; the sputtering rate of Ni is about 1.6 Å/s; and the rate of Cu is about 3 Å/s. The total metal thickness was 300 nm. The compositions of Ni–Cu alloy are controlled by adjusting the thickness of Ni and Cu films. For example, the ratio of Ni to Cu 1:10 can be obtained by setting the thickness of Ni film to be 30 nm and the thickness of Cu film to be 270 nm.The substrate we used was heavily doped Si with 300 nm SiO2 atmosphere. The pressure was controlled to be 15 mbar. Then, 960 sccm Ar, 20 sccm H2 and 5 sccm CH4 were introduced into the chamber and the plasma  was ignited at the same time. The plasma was maintained for 5 min to grow graphene. Finally, the furnace was cooled down at 200 °C/min. The whole growth process (including heating and cooling) took approximately 15 min. The schematic illustrations of the growth equipment and growth process are shown in The growth equipment was a vertical, cold wall CVD furnace . First, the temperature rose to 600 °C at a rate of 200 °C/min in HWe measured the roughness of the Cu–Ni films by a stylus profiler . Before annealing, the average roughness and the root-mean-square roughness of the films were Ra = 3.03 nm and Rq = 3.76 nm, respectively. After annealing and graphene growth, the average roughness and the root-mean-square roughness of the films were Ra = 4.41 nm and Rq = 5.62 nm, respectively. On the whole, the surface roughness of the Ni–Cu alloy film did not change much, due to the relatively low annealing and growth temperature.4:HCl:H2O = 10 g:50 mL:50 mL) for about 35 min. The thickness of PMMA was about 100 nm. After the etching of the metal, the sample was immersed in deionized water for 15 min and blown dry. Then, the sample was baked at 150 °C in air for 10 min to improve the graphene-substrate adhesion. In the end, the PMMA was removed by acetone.First, the PMMA (poly(methyl methacrylate)) supporting layer was spun on the substrate ; that was followed by baking the substrate at 150 °C for 5 min. Then, the sample was immersed in a Ni–Cu alloy etchant  alloy should be much less than that of bilayer graphene. However, atomic force microscopy (AFM) measurements show that the maximum thickness of the graphene grown on the alloy was about 88 nm  and Ni2Cu1 (high Ni composition) alloys. As shown in ®, <www.thermocalc.se>, version 2019a, using the MOBCU2 atomic mobility database. As shown in −12 m2/s and 3 × 10−14 m2/s respectively, which are about two orders of magnitude different. In −13 m2/s is needed to ensure the uniformity of graphene layers. We also calculated the bulk CDR at 800 °C , in which D0 (the frequency factor) is approximately temperature-independent. Q is the diffusion activation energy, kB is the Boltzmann constant and T is the absolute temperature in Kelvin. We see that D0 depends on the crystal lattice. In the present case, Cu has a larger D0 value, mainly due to a larger lattice constant than Ni. The activation energy Q sitting in the exponent function should have a stronger impact on D, in comparison with D0 which is proportional to D. The high diffusivity in Cu can, therefore, be attributed to two factors: (1) a larger lattice constant, and (2) a lower diffusion barrier which can be further interpreted based on the filling status of the d electron shell. Hu et al. [The high CDR in/on Cu relative to that of Ni is attributed to the following factors. The diffusion coefficient is given as D = Du et al.  studied Thus, the performances of Ni–Cu alloys at low-temperature growth are dramatically different from the previous reports at high temperatures ,24,25,26This work also gave us inspiration for our follow-up work. We can further explore alloys with higher catalytic activity and higher CDR on its surface simultaneously, in order to obtain even more uniform and higher quality graphene at low temperatures. The selection of new alloys must meet the following requirements: (1) high catalytic activity, (2) fast CDR in the metal and (3) forming a homogenous single-phase solid solution alloy. We screened CDR in various metals  and the We also studied the influence of plasma on the quality of graphene. The purpose of applying plasma during the growth is mainly to accelerate the low temperature cracking of methane. Interestingly, we found that plasma is also very important to improving the quality of graphene. In fact, graphene can also be grown on the surface of Cu–Ni alloys at 600 °C even without plasma. It was found that the lowest growth temperature catalyzed by pure Ni without plasma is around 450 °C . HoweverThe growth equipment we used included a vertical, cold wall graphene growth system . As shown in 2/Si substrate.One of the applications of low temperature growth is the combination with direct growth technology, which makes it possible to directly grow graphene on a variety of substrates that cannot withstand very high temperatures. We combined this 600 °C graphene growth method with our previously-reported in situ growth technique ,29 and o2/Si and sapphire. The graphene is grown on the metal surface. After that, a PMMA supporting layer is spun on the sample. Therefore, the metal sacrificial layer is completely covered by the PMMA/graphene films. Interestingly, we find that when the sample is immersed in the metal etchant, the etchant can efficiently penetrate the PMMA and graphene to accomplish the metal etching (First, we need to give a brief introduction of our in situ growth technology. This method uses a sacrificial metal layer to assist growth. The essence of the growth method is the etching mechanism of the metal sacrificial layer. As shown in  etching b. As sho2/Si substrate. The plasma power was selected to be 50 W; the ratio of methane to hydrogen was 5 sccm/20 sccm; and the growth time was 5 min. D/IG lies in the range of 0.12–0.69. G/I2D of typically 0.97–3.6.Using this method, a patterned graphene film was grown directly on a 2-inch SiO2/Si substrate at 600 °C with relatively good quality and uniformity. Low temperature growth can expand the range of substrate choices and reduce the effect of temperature on substrates, which is a future direction for the development of direct graphene growth. We expect the work presented here will promote the application of directly grown graphene at low temperatures.In this work, the effect of CDR on the thickness and uniformity of graphene in low temperature growth has been revealed for the first time. The uniformity and quality of graphene can be improved by proper selection of the alloy compositions. Ni–Cu alloy was used in our work, where Cu acted to increase the CDR, while Ni provided high catalytic activity. Meanwhile, we found that the plasma power can have great influence on the quality of graphene. Finally, based on optimizing the growth parameters and combining them with the in-situ growth method, we obtained a wafer-scale graphene film directly on SiO


Graphene is an ideal material in the reinforcement of metal-matrix composites owing to its outstanding mechanical and physical properties. Herein, we have investigated the surface enhancement of iron via a computational nanoindentation process using molecular dynamics simulations. The findings of our study show that graphene can enhance the critical yield strength, hardness and elastic modulus of the composite to different degrees with the change of the number of graphene layers. In the six tested models, the composite with trilayer graphene on the surface produces the strongest reinforcement, with an increased magnitude of 432.1% and 169.5% in the hardness and elastic modulus, respectively, compared with pure iron. Furthermore, it is revealed that high temperature could weaken the elastic bearing capacity of the graphene, resulting in a decrease on the elastic mechanical properties of the graphene/Fe composite. Since its discovery , graphenExtensive studies have been conducted on metal matrix composites, including Fe, Al, Cu, Mg and Ni ,11,12,13Nanoindentation is an approach widely used to measure elastic modulus and hardness of nanocomposites ,16. In tThe MD method was used to examine the influence of graphene in the graphene/Fe composite at the atomic level. The large-scale atomic/molecular massively parallel simulator (LAMMPS) software was employed to calculate the MD simulations. The simulation cells are shown in The graphene/Fe composite models are shown in ijREBOE term describes the short-ranged interactions (r < 2 Å) between carbon atoms, the EijLJ term adds longer-ranged interactions (2 Å < r < cutoff) using a form similar to the standard Lennard Jones potential, and the EkijlTORSION term describes various dihedral angle preferences in hydrocarbon configurations, which is an explicit 4-body potential.The accuracy of the MD simulation results is determined by the selection of potential function. We used the Brenner-generation reactive empirical bond-order potential to model the C-C bonded interaction . The C-CiE of an atom i is specified asαF is the embedding energy which is a function of the atomic electron density βρ. αβΦ is the pair potential interaction between atoms I and J, as a function of the distance ijr between atom I and atom J. α and β are atomic element types. The C-Fe interaction between iron and carbon atoms of both diamond indenter and graphene layers was described by the classical Lennard Jones (LJ) potential, as shown in Equation (3)cr is the cutoff distance. The σ and ε for the C-Fe interaction are 2.221 Å and 0.043 eV [The embedded-atom method (EAM) potential was used to compute pairwise interactions between iron atoms . The totWe set a downward velocity of 30 m/s on the balls and kept the temperature at 300 K by the Nose-Hoover algorithm . After tf is the final displacement of the plastic unloading process. R is defined by R = (1/R1 + 1/R2)−1, where R1 is the radius of diamond indenter, R2 is the radius of the spherical hole in the surface of the substrate [r is given by [E and ν are Elastic modulus (Young’s modulus) and Poisson’s ratio of the composite matrix, iE and iν are the same parameters of the diamond indenter. The hardness is defined bymaxP is the max force at the initial unloading point, and cA is the contact area of spherically curved surface [The Hertzian contact analysis theory guided our model. To understand the influence of graphene sheets on the hardness and elastic modulus of the iron matrix, the load-displacement data was recorded for analysis. The load-displacement relation is described by (4)P=43Rubstrate . The indgiven by (5)1Er=( surface .The results of the simulated nanoindentation process are revealed by the load-displacement curves. The mechanical properties of multiple graphene have received growing interest in recent years ,28. To iTo investigate the influence of loading speed and temperature on the nanoindentation process of the graphene/Fe composite, we explored the nanoindentation simulation of the composite with monolayer graphene on surface at varied loading speeds and at different temperatures, as shown in The simulation results reveal the change of hardness and elastic modulus of iron matrix composites with the graphene of the different number of layers, which is well consistent with previous studies on metal-matrix composites reinforced by graphene ,31. BothTo conclude, we have investigated the mechanical properties change of graphene/Fe composites with different number of graphene layers on the surface and in the superficial zone by using the MD simulation method to model the nanoindentation process. The results from the loading-displacement curves show that the graphene layers have a significant effect on the critical yield strength, hardness and elastic modulus of iron matrix in different degrees due to its remarkable loading bearing capacity. The degree of reinforcement on iron matrix increases with the number of graphene layers, both in surface and superficial zone cases. It was demonstrated that the enhancement in hardness and elastic modulus of composite in the surface cases is slightly stronger than that in superficial zone cases with graphene of the same number of layers on account of the production of the local stress fields in the superficial situations. Finally, the loading speeds have a small effect on the simulation of the composite nanoindentation process, and the simulation results of different temperatures reveal that high temperature can effectively reduce the mechanical properties of the graphene/Fe composite by softening lattice rigidity.