Cellulose is one of the most hydrophilic polymers with sufficient water holding capacity but it is unstable in aqueous conditions and it swells. Cellulose itself is not suitable for electrospun nanofibers’ formation due to high swelling, viscosity, and lower conductivity. Carboxymethyl cellulose (CMC) is also super hydrophilic polymer, however it has the same trend for nanofibers formation as that of cellulose. Due to the above-stated reasons, applications of CMC are quite limited in nanotechnology. In recent research, loading of CMC was optimized for electrospun tri-component polyvinyl alcohol (PVA), polyvinylpyrrolidone (PVP), and carboxymethyl cellulose (CMC) nanofibers aim at widening its area of applications. PVA is a water-soluble polymer with a wide range of applications in water filtration, biomedical, and environmental engineering, and with the advantage of easy process ability. However, it was observed that only PVA was not sufficient to produce PVA/CMC nanofibers via electrospinning. To increase spinnability of PVA/CMC nanofibers, PVP was selected as the best available option because of its higher conductivity and water solubility. Weight ratios of CMC and PVP were optimized to produce uniform nanofibers with continuous production as well. It was observed that at a weight ratio of PVP 12 and CMC 3 was at the highest possible loading to produce smooth nanofibers. Advancement in technologies, product, and system design have brought revolution in the lifestyle of mankind. However, continuous development is key to sustaining a developing society. Nanotechnology is one of the most advanced technologies, which covers a wide range of applications ,2,3. EleNatural, semi-synthetic, and synthetic polymers have a wide range of applications in materials science and engineering. However, sustainable development is a key consideration for modern research. Cellulose is one of the most useful natural polymers having number of applications in tissue engineering, water treatment, filters, food and packaging industry, and other areas of science as well ,22,23,24PVA is a polymer with the decreasing trend of viscosity as the temperature increase. The presence of hydroxyl groups on PVA create inter and intra molecular hydrogen bonding. Hydrogen bonding is the reason for the strong interaction between CMC and PVA. The mechanical properties of the blend are also very good. The blend possesses smooth morphology with no bead formation. However, there is bead formation as the concentration of CMC increase above 5%. The absorption rate of CMC may decrease by adding the PVA. To maintain the good absorption level, it is necessary to introduce the strong hydrophilic polymer to the blend ,32,33. PIn this research, PVP and PVA were selected as carriers for CMC. The main objective of this research was to obtain smooth nanofibers with continuous electrospinning. Addition of CMC can enhance some of the characteristic properties of nanofibers, which further widened the area of applications for PVA and PVP. CMC’s excellent water holding capacity, biocompatibility, biodegradability, and other characteristics can be used in a number of applications such as food packaging (nanofibers based), biomedical, and environmental engineering applications. This is a novel idea to load maximum possible amount of CMC on electrospinning to get uniform nanofibers that can be utilized in practical applications. In future, authors have plans to carry on this idea to further characterize tri-component nanofibers consisting of optimized ratios of PVA, PVP, and CMC for mechanical, biodegradability, and water holding capacity to specific application areas for the betterment of society.Polyvinylpyrrolidone (PVP) with an average molecular weight of 40,000 was purchased from Sigma-Aldrich , Polyvinyl alcohol (PVA) with an average molecular of 85,000–124,000 and 87–89% hydrolyzed was purchased from Sigma-Aldrich, and sodium carboxymethyl cellulose (Na-CMC) with an average molecular weight of 250,000 and degree of substitution of 1.2 was also purchased from Sigma-Aldrich chemicals. All materials were used as received without chemical or physical modification.w/w) while weight percentage of PVP and CMC were varied. PVP was added from 10 weight percent to 14 weight percent while CMC was added at the lowest from 1 percent to 3 weight percent as shown in Concentration of PVA in spinning solution was kept constant  was used to check the surface properties of nanofiber mats at the voltage of 10 kV. Average diameter was calculated by image analysis software  from 50 readings of random nanofibers of each of the samples. Water contact angle was investigated by using contact angle analyzer . Thermal analysis of PVA/CMC, PVA/PVP, and PVA/PVP/CMC composite nanofibers was examined by thermogravimetric analyzer Thermo-plus TG 8120 . TGA test was performed under ambient (air) atmosphere in static mode and heating rate was set to 10 °C/min and 25–500 °C temperature range for all specimen. Water contact angle (WCA) was measured using contact angle analyzer . The volume of water droplet was set to 2 µL while pictures were captured after 1 s (1000 milli seconds).To investigate the chemical reaction between CMC, PVP, and PVA, FTIR with an ATR prestige-21  was used. Fingerprints of ATR were recorded from 600 to 4000 cm−1, which was associated with the presence of hydroxyl groups in PVA and PVP main chains, however the same peak became sharper when the concentration of PVP and CMC was increased in composite nanofibers, i.e., a sharp peak was observed at 3402 cm−1, which is generic peak of the hydroxyl group. Further, in the results of the water contact angle, it was also confirmed that increasing percentage of CMC in composite nanofibers imparted super-hydrophilicity to the nanofibrous mats. Characteristic peaks of PVA were observed at 3200 to 3500 cm−1, which indicates the presence of hydroxyl group (–OH stretching) in PVA chains. A peak at 2900 cm−1 was also observed, which referred to (–CH2–) asymmetric and symmetric band [−1 can be associated with stretching vibration of the C=O in the pyrrolidone group, while CH stretching can be assigned to the absorption peaks around 2850 to 2980 cm−1. CH deformation bands can be associated to bands at 1430 and 1370 cm−1 (difference in peaks in red and black in given spectra). C–N bending vibration of pyrrolidone can be associated with the band at 1279 cm−1, however PVP did not show any significance peak at 3400–3500 cm−1, which are usually associated with the presence of amines [All three polymers used in this study are highly hydrophilic in nature, and the reason behind hydrophilicity is the presence of abundant hydroxyl groups in main chains of polymeric structures. FTIR-ATR spectra in ric band . In the f amines . It is hw/w). PVA/PVP nanofibers were also found to be smoother and finer. The addition of PVP in spinning solution provided support of conductivity and viscosity, which resulted smoother nanofibers in case of C1P10, C1P11, C1P12, and even C1P14. However, the addition of further CMC (weight ratio of 2) did not show the same trend as that of CMC1. Samples C2P10 and C2P11 nanofibers were not uniform and have some beads on the surface, while C2P13 and C2P14 nanofibers had uniform morphology. The ratio of CMC was further increased to a weight ratio of 3 to confirm the maximum loading capacity of CMC for smoother nanofibers. It was observed that for CMC-3, only the C3P12 sample exhibited smoother morphology while C3P10 and C3P11 samples had beads on the nanofibers’ surface; on the other hand, not a single nanofiber was observed in the case of C3P13 and C3P14. In conclusion of morphological characterization, it can be stated that maximum and optimum loading capacity for CMC is up to a weight ratio of 3 with respect to PVA and PVP, while the most suitable concentration for smoother and continuous nanofibers production without beads formation is PVA:PVP:CMC = 6:12:3.Morphological properties like surface structure and nanofibers’ diameter were observed by the scanning electron microscope (SEM). As it was also stated in the introduction section, CMC cannot be electrospun due to high viscosity and low conductivity. However, PVA is easily electrospun even at varying concentrations (6% to 10% is most suitable for smoother nanofibers). PVP is also very difficult to electrospin at lower concentrations due to lower viscosity. The addition of PVP lowers the viscosity of CMC solution as well as imparts conductivity to the spinning solution and makes it electrospinnable with good nanofiber formation. Diameters of nanofibers were measured by Image J. software by taking 50 random readings of nanofibers for each sample. The water-holding capacity of any substance is generally dependent on hydrophilic or hydrophobic nature . HydrophCMC is generally unstable above 280 °C, while PVA and PVP are thermally stable well above 300 °C. Considering the results and discussions of experimental section, it can be concluded that CMC is not suitable for electrospinning as a single component, however it can be processed by forming blends/composites with compatible polymers like PVA and PVP. It was observed that specific concentrations of CMC and PVP formed highly uniformed nanofibers without any bead formation. Processability was also observed to be smoother specifically for samples containing 12 wt.% PVP. There was no significance on thermal degradation due to addition of CMC. Water contact angle was further decreased to 0° with the addition of CMC in tri-component nanofibers. Nanofibers with smoother morphology will have potential applications in the field of biomedical, agriculture, and environmental engineering.


Kaposi sarcoma (KS) is a cancer, characteristically manifesting as red or purple patches of abnormal tissue growing subcutaneously around the mouth, nose, and throat. Primary musculoskeletal KS is a never reported as skeletal muscles sarcomas are first differentials. Pertaining to the musculoskeletal system complicity of KS, African and classic KS lesions are inclined to manifest lesion in the peripheral skeleton. On the other hand AIDS-related KS routinely involves the maxillofacial bones and/or axial skeleton. KS distinguishably involves the tempo-parietal bones, paranasal sinus, hands and feet and other facial bones. Asymmetric involvement of the bones by KS is the rule. Though reported, involvement of the joints in KS is unusual. Skeletal muscle involvement has only sparingly been reported in AIDS-related KS patient. A primary KS of the skeletal muscle in an otherwise normal patient with no skin manifestations has never been reported thus far. The occurrence of KS in any atypical site may pose as difficulty to diagnose it. It is important for the radiologist to acquaintance with the spectrum of imaging manifestations of KS in various affected organs. Particularly in asymptomatic patients, lesions go unrecognized on routine imaging studies (e.g. KS on plain x-ray films) and clinicians are unwary of their existence. Awareness that KS can occur in any of these unusual locations may help avoid potential misdiagnosis with serious consequences  and/or mis-management. Primary musculoskeletal Kaposi sarcoma in a non-immunocompromised or a non-acquired immune deficiency syndrome (AIDS) patient has not been yet reported in literature.A 70 year old man of Indian origin presented to the outpatient department with complaints of pain, limited mobility and swelling over anterior aspects of the right leg, above the ankle for three months. He gave a history of recurrent ulcer over the same region. There was no history of loss of sensation, no history of trauma, no comorbid illness, no history of fever, no gastrointestinal/respiratory symptoms. Clinical examination of the right leg showed a well demarcated erythematous firm lesion with nodular surrounding areas and accompanying lymphedema of the distal foot. Thorough clinical examination of the entire body revealed no other lesion. There was no past history of similar lesions anywhere in the body. No other skin/oral lesions were identified. Additional investigations showed he was not immunocompromised or did not suffer from any sexually transmitted diseases. Plain radiograph of the leg  showed a lobulated soft tissue swelling in the anterior aspect of the lower one third of the leg with few calcific areas within and associated periosteal reaction the adjacent bones of the leg. Computerised tomography (CT) of the same patient shows areas of soft tissue edema, heterogeneous linear densities and few areas of faint calcification in the region of the lobulated skin lesion. Thick unicortical periosteal reaction of the tibia for a short segment; adjacent to the lesion was noted. Magnetic resonance imaging (MRI) showed findings similar to the CT findings and shows no bone marrow involvement. The lesion appeared iso to hypo intense on T1 weighted images and hyper intense on T2 weighted images and was located within the skeletal muscle. Surrounding perilesional edema was noted. There was no bone marrow involvement . A biopsMusculoskeletal involvement in KS is uncommon and if at all, occurs secondarily due to local extension from the skin surface lesion. All epidemiological forms of KS have been shown to involve the musculoskeletal system. They include AIDS-related KS, classic KS, African (endemic) KS, and infrequently transplanted-associated KS . The larClinically the differentials pertaining to dermatological examination were pyogenic granuloma, baciliary angiomatosis, acroangio dermatitis, hemangiomas and other melanocytic proliferations. The radiological differential diagnosis depending on imaging and history included a broad spectrum and were soft tissue sarcomas, osteomyelitis, bacillary angiomatosis which may also exhibit skin lesions, bone erosions, and soft-tissue masses, mycobacterial infections, pyogenic granuloma and lymphoma. The biopsy of the lesion was performed and was reported as features suggestive of low grade sarcoma-Kaposi sarcoma. The occurrence of KS in any of the above mentioned atypical sites may prove difficult to arrive at KS diagnosis, particularly if the patients are relatively asymptomatic, lesions can go unrecognized on routine imaging studies (e.g. on plain X-ray films osseous KS can be missed), and/or clinician's awareness of their existence . Being m


Vibrio vulnificus is a gram-negative bacterium that is pathogenic to humans and capable of causing wound infections and primary septicemia . Growth of C. elegans on pathogenic bacteria reduces their lifespan in a manner that recapitulates some aspects of the natural pathogenicity of many disease agents . C. elegans grown on V. vulnificus have reduced lifespans and this pathogenicity is diminished when worms are grown on V. vulnificus mutant strains defective in known virulence factors . We set out to use this host-parasite model to better understand the role of iron transport systems in V. vulnificus pathogenicity. Normal iron transport is required for full pathogenicity in mice due to the typically iron-limiting conditions in the host environment. V. vulnificus has three paralogs of the TonB iron transport system, known as the TonB1, TonB2, and TonB3 systems, and strains with deletion mutations in tonB1 and tonB2 (ΔtonB1 ΔtonB2) are defective in iron transport . We tested whether this double mutant V. vulnificus strain would have reduced pathogenicity in C. elegans, as it does in mice. We confirmed that C. elegans grown on wildtype V. vulnificus reduced the median lifespan of animals from 12 days to 9 days. However, animals grown on the ΔtonB1 ΔtonB2 strain also had a median lifespan of 9 days and there was no statistically significant increase in survival of worms grown on the mutant strain . It is possible that the iron transport systems were not essential for pathogenicity in these experiments because there was sufficient residual iron present despite the use of iron-limited CM9 plates. Further experiments with iron chelators introduced into the media are required to clarify whether the lack of dependence on iron transport is due to residual iron or a result of physiological differences between V. vulnificus infection of C. elegans intestine and its infection of the bloodstream of mice.V. vulnificus strain were normalized to an OD600 of 0.3, spread onto CM9 plates, and incubated for 24 hours at 35°C. OP50 experiments were done on standard MYOB plates. For each replicate, 10 L4 hermaphrodites were transferred onto each plate on day 0. fem-3 animals at the restrictive temperature of 25°C, which have been shown to have normal lifespan , were used so animals did not have to be transferred away from progeny. Plates incubated at 25°C were scored every 24hr for the number of remaining live worms. A worm was considered dead when it no longer responded to touch with a pick. Data was graphed using Prism software (Graphpad), and statistical significance was determined using the Log-Rank test with the assumption of proportional hazards maintained.Overnight broth cultures of each CM9 plates1.5% agar, 1x M9 salts , 0.2% Casamino Acids, 0.5% glucose, 10 μM CaCl2, 100 μM MgSO4, 100 µg/ml Ampicillin.MYOB plates2% agar, 0.55g Tris-Cl, 0.24g Tris-OH, 3.1g Peptone, 8mg cholesterol, 2gNaCl per liter.StrainsV. vulnificus Strains


Significant progress has been made toward the understanding of the effects of space environmental factors, e.g., microgravity, vacuum and radiation, on microorganisms exposed to real and simulated space conditions. Of extreme importance is not only knowledge of survival potential of space-exposed microorganisms, but also the determination of mechanisms of survival and adaptation of predominant species to the extreme space environment, i.e., revealing the molecular machinery, which elicit microbial survivability and adaptation. Advanced technologies in –omics research have permitted genome-scale studies of molecular alterations of space-exposed microorganisms. A variety of reports show that microorganisms grown in the space environment exhibited global alterations in metabolic functions and gene expression at the transcriptional and translational levels. Proteomic, metabolomic and especially metabolic modeling approaches as essential instruments of space microbiology, synthetic biology and metabolic engineering are rather underrepresented. Here we summarized the molecular space-induced alterations of exposed microorganisms in terms of understanding the molecular mechanisms of microbial survival and adaptation to drastic outer space environment.Since the dawn of space exploration, the survivability of terrestrial life in outer space conditions has attracted enormous attention. Space technology has enabled the development of advanced space exposure facilities to investigate  The outer space environment, which is characterized by a high vacuum and an intense radiation, provides hostile conditions to any form of life. With the upcoming long-term space explorations, it is becoming increasingly important to understand the molecular mechanisms of survival in outer space. Remarkably, a few extremophilic microbial species have been shown to withstand the drastic influence of the outer space factors , and numSystems biology is an interdisciplinary field that incorporates the results of genome-scale molecular analysis–omics techniques–such as genomics, transcriptomics, proteomics, and metabolomics and genome-scale metabolic and regulatory biomathematical models to reveal complex molecular interactions underlying molecular evolution, functional and phenotypical diversity and molecular adaptation , 2011a,bIn this review we focus on molecular mechanisms of microbial survivability in the outer space environment revealed with the help of global and integrative –omics approaches of systems biology that have been recently used to study microorganisms exposed to real and simulated space conditions. The use of –omics in space life sciences potentially has a pivotal role in the understanding of the molecular machineries implicated by microorganisms to tolerate the harsh conditions of space.Exposure to space environment strongly modifies the expression of genes and the abundance of proteins related to metabolism . Space pSerratia marcescens, Escherichia coli, and Klebsiella pneumoniae after a long-term flight on-board of the SHENZHOU-8 spacecraft exhibited a difference in carbon source utilization , while their morphology or growth patterns were not affected , which can be explained by the increased demand for additional carbon substrates during stress adaptability to the space environment  were differentially expressed during spaceflight  was significantly increased . Such discrepancies between different reports can be very well stated by the experimental set up of the studies. One group of the studies reported on molecular profiles during spaceflight, i.e., avoiding re-cultivation of returned samples  project showed the down-regulation of genes encoding lipid biosynthetic enzymes  involved in surfactant biosynthesis was found among the major virulence-associated genes of P. aeruginosa stimulated in spaceflight along with the accumulation of rhamnolipids under simulated microgravity conditions, which might be connected to low shear liquid sensing  triggers cellular integrity of space-exposed microorganisms, influencing numerous processes in membrane apparatus of microbial cell    , 2013. Cregulon) .A number of spaceflight induced alterations associated with cell envelope, e.g., a thickened cell envelope and intensive vesiculation , are quiS. typhimurium in proteomic response to cultivation aboard spacecraft  of the gene encoding for Flagellar hook-associated protein 2 (FliD filament cap protein)  . Genes otivation . Transcrceflight .The reported effects of simulated microgravity and spaceflight on the various physiological properties of microorganisms are associated with the potential disruption of the quiescent extracellular environment. The molecular components of bacterial motility and chemotaxis response are activated in microgravity-exposed microorganisms in order to gain a balanced connection between the cell and its environment. The induced flagellar action results in mixing of the local fluid surrounding of microbial cell and removal of the cell from its quiescent location. The induction of molecular machinery responsible for motility and chemotaxis can locally influence the correct redistribution and availability of nutrients, substrates, solutes and other biologically active molecules at the extracellular environment level.B. pumilus spores long-termly exposed to a variety of real space conditions at the ISS in the EXPOSE facility revealed the up-regulation of the alpha-ketoglutarate decarboxylase enzyme which is associated with menaquinone biosynthesis and involved in the membrane-associated electron transport system  (hydN gene encoding Fe-S center-bearing protein responsible for electron transport from formate to hydrogen together with a set of S. typhimurium genes involved in the formation of the Hyc hydrogenase (respiratory enzyme of H2-uptake) were differentially expressed in response to spaceflight cultivation  . The hydtivation . The gen. rubrum . The subceflight . The dowceflight . This cynditions . The aut nitrite .Microbial adaptation to spaceflight conditions may lead to alterations associated with energy sources utilization. Hereby, a corresponding molecular pull of energy-converting enzymes responsible for a switch from one energy source to another is affected in conditions of spaceflight and simulated microgravity. Energy management also facilitates the survival of outer space exposed microorganisms by modulating electron transfer proteins.fur gene autoregulation  clusters. Bacteria and Archaea enormously depend on these two classes of cofactors for their energy metabolism. Iron availability influences the expression of bacterial genes encoding high-affinity iron uptake pathways and, in pathogenic microorganisms, virulence determinants . The metgulation .Salmonella ground-based LSMMG  and down regulated  by LSMMG, as indicated by whole genome microarray analysis  and those not earlier described as Fur regulated , superoxide dismutase (Rru_A1760) and bacterioferritin bfr (Rru_A2195) were induced  and translation initiation factors IF-1 and IF-3 were down-regulated in transcriptomic response to spaceflight cultivation , which is implicated in metabolism of carbohydrates triggered in majority of space exposed microorganisms  and DNA polymerase III alpha-subunit 3 (dnaE) were 3- to 14-fold up-regulated in space-exposed and simulated Mars-exposed B. subtilis spores  encoding Y-family DNA polymerase, responsible for translesion bypass DNA repair in space-exposed B. subtilis spores . The abundances of the proteins (recQ and ruvABC) responsible for recombinational DNA repair and the Mrr restriction system protein were also significantly increased , and to provide microorganisms the ability to recover from the stress they experience. Overexpression of stress response genes was observed by real-time-PCR in nditions , in protacecraft  and in mogravity , 2013  radical, provides an efficient antioxidant defense in conditions of outer space. In opposite to its bacterial counterpart under the long-term influence of real space factors, SOD from spaceflight microgravity-exposed yeast S. cerevisiae along with the other oxidative stress protein peroxiredoxin was down-regulated in proteomic analysis after short-time space flight , and redox active proteins  induced in “real” space-exposed spores of ceflight   that increase the osmotolerance serve as a microbial strategy to cope with outer space environmental stressors.R. rubrum sent to the ISS in frames of MELiSSA project and in conditions of modeled microgravity indicated an enhanced expression of genes involved in tellurium resistance in transcriptomic analysis , and contribute to the preservation of the intracellular reducing environment, probably by directly reversing disulfide bonds   . One of Experimental parameters during space exposure affect microbial survival rates and may lead to certain discrepancies in –omics assisted analysis of returned/exposed microorganisms. The composition of cultivation medium influences the microbial space response , for insIn addition to the proteotranscriptomic profiling, we propose that new space experiments should include a detailed metabolomic analysis of exposed microorganisms. This novel approach provides a rich source of new findings of fine molecular network regulating the space response , 2019a,bBoth authors conceived the review, conducted the literature search, created the figures, wrote and revised the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Temperature dependent (300 K–400 K) electrical characterization of fibers was carried out in frequency range of ~20 Hz–2 MHz. The complex impedance analysis showed contribution from bulk and intergranular parts of nanofibers in conduction. Moreover, analysis of the Cole-Cole plot confirmed the space charge dependent behavior of BiSiO nanofibers. Two types of relaxation phenomena were observed through Modulus analysis. In ac conductivity curve, step like feature of plateau and dispersive regions were described by Maxwell-Wagner effect while the dc part obeyed the Arrhenius law. However, frequency dependent ac conductivity revealed the presence of conduction mechanism in diverse regions that was ascribed to large polaron tunneling model. Detailed analysis of complex Impedance and ac conductivity measurement showed negative temperature coefficient of resistance for the BiSiO nanofibers. Current-voltage (IV) characteristics represented ohmic conduction; followed by space charge limited current conduction at intermediate voltages. Results from both ac and dc measurements were in good agreement with each other.This work represents the nature of conduction mechanism in bismuth silicate (BiSiO) nanofibers as a function of temperature and frequency. Scanning electron micrographs and X-rays diffraction patterns exhibited the formation of cubic phases of Bi High thermal stability, chemical durability, dielectric strength and interesting structure of BiSiO type materials are proved to be promising for electrical properties. This diversity of physical effects makes researchers to grow bismuth silicate from bulk to nanoscale. Different techniques have been adopted to synthesize bismuth silicate nanostructures such as solution phase synthesis3, hydrothermal, interfacial polymerization method and electrospinning5. Nanoscale materials have exclusive properties depending on their low dimensions and large surface area as compared to their bulk equivalents6. Among all reported nanostructured materials; one dimensional (1D) nanofibers are most common in electric device fabrications due to their large surface to volume ratio and relatively high crystallinity7. These 1D nanofibers are now frequently used in sensors, nano-electronics tissue engineering, photo-voltaic, nano-photocatalysts and nano-filtration8.The ac and dc conductivity of the bulk BiSiO materials have been reported9. The conductivity in these bulk materials is because of ionic conduction mechanism and governed by the mobility of bismuth (Bi) ions10. Effect of calcination on structural properties and consequently on the electrical properties for bulk BiSiO materials have been reported earlier12.Synthesis of bismuth silicate (BiSiO) nanostructuresTo report possible conduction mechanism along with dielectric properties of BiSiO type materials, scientists need to pay attention to the most probable causes of the change in its electrical behavior due to change in calcination temperature in ambient air. The main goal of the current work is to present an inclusive summary of electrical properties as ac and dc conductivity accompanied by electric modulus variation in BiSiO nanofibers as a function of frequency (1 Hz–2 MHz) and temperature (300 K–400 K). This type of comparison between ac and dc conduction transport on BiSiO nanofibers is rarely been found in literature.w = 130k), Tetraethoxysilane (TEOS), N, N-Dimethylformamide (DMF), Bismuth Acetate (Bi(C2H3O2)3), Acetic acid (CH3COOH), and ethanol (C2H5OH) were obtained from Sigma Aldrich and used as precursor materials. Polymer solution was prepared by adding 1 g PVP/10 ml ethanol and 2 ml TEOS/1 ml acetic acid. The mixture was stirred for 15 minutes, followed by the gradual addition of 1.0 g of bismuth acetate [Bi(C2H3O2)3] dissolved in 1 ml of DMF. The whole solution was stirred for about 90 minutes in a capped beaker. The final solution was loaded into a syringe and a voltage of 10 kV was applied between the tip of the needle and collector plate14. As spun PVP/ bismuth silicate nanofibers were collected on a copper plate. The as prepared nanofibers were heat-treated at 600 °C for 6 h in air furnace.The BiSiO nanofibers used to study the electrical (ac and dc) properties were fabricated using electrospinning method.. Polyvinylpyrrolidone  followed nickel (Ni) on a glass substrate to improve the adhesion of Ni to the glass substrate. The suspension of BiSiO nanofibers in isopropanol were prepared by using ultrasonic agitation bath. The nanofibers were then deposited on the device using drop casting method. Figure The device of BiSiO was fabricated for the electrical properties measurements. For this purpose, 100 nm4(SiO4)3 nanofibers. Maximum peaks were indexed with JCPDS card number 01-080-159615, whereas, few peaks were indexed with the JCPDS card number 00-037-0485 and are attributed to Bi12SiO20 phase. This may be due to high temperature heat treatment i.e. 600 °C. Texture coefficient (Tc(hkl)) of the sample was calculated to check the random or preferential growth of the Bi4(SiO4)3 phase using the formula 1 given below16. The intensity of peaks related to Bi12SiO20 phase is very low. Therefore, it is very difficult to estimate the preferential growth direction.The morphological studies of the BiSO nanofibers were carried out using Scanning electron micrographs (SEM) and X-ray diffraction Analysis (XRD) as shown in Fig. Ihkl shows the intensities in XRD spectra of nanofiber mats and n is the number of diffraction peaks selected for the calculation of Tc(hkl). Ir(hkl) is the intensity of the reference pattern (JCPDs card). The deviation from unity or higher values of Tc(hkl) shows the preferred orientation. Growth in preferred orientation along the particular plane shows the maximum number of grains along that plane15.It is reported that an increase in texture co-efficient from 1 shows a higher degree of preferred orientation along the particular plane. Moreover, the higher or lower values of texture co-efficient from unity relates the increase or decrease in planar density beside a specific crystal plane16. The texture analysis of BiSiO nanofibers shows that the fibers are highly textured along (321) and (532) plane with planar density as shown in Table i.e. 300 K–400 K) for BiSiO nanofibers and results are illustrated in Fig. Z″ vs. Z′) which provides data in the form of arcs with relaxation time . Arrows point towards increasing temperature. The Z″ vs. Z′ arcs for all particular temperatures have depressed semicircles indicating that there are multiple relaxations present in our material. These multiple relaxations are confirmed by fitting the data with Z-View software with fitting error <5%. Scattered points in the Fig. Rb and Rgb), pseudocapacitance (Cb and Cgb)and n parameters nb and ngb are shown in Table Z′) and imaginary (Z″) part of impedance17:Z′) axis. These intercepts give the values of the bulk (Rg) and grain boundaries (Rgb) influences in resistance. The maxima of arcs provide the frequency ωmax for each RC element and is represented by τ’ and ‘fmax’ are independent of sample geometry and are the intrinsic properties of RC element18. Bulk capacitance is calculated by the formula.Impedance analysis were done at a temperature range  behavior same as present in semiconductors20.entclass1pt{minimaZ′ and Z″ was carried out to understand the crossover from resistive to conductive behavior less than the cut-off frequency fo. Figure Z′) as a function of frequency at different temperatures. At low frequency region, a decrease in Z′ values is observed with temperature. This behavior represents the existence of a negative temperature coefficient of resistance (NTCR) in BiSiO nanofibers23. It is also observed that all spectrums merged into a single spectra at relatively high frequencies (0.01 MHz) independent of temperature change, which exhibited clear indication of space charge dependent behavior of the BiSiO nanofibers24. Essentially, the charges accumulated near boundaries have enough energy to overcome the barrier; consequently leading to an improvement in conductivity. The active distance between junctions in BiSiO nanofibers has defined the specific length of the conductive network. This length is probed when it is equivalent to ac modulation period, therefore allowing the transportation of charges from one junction to another along the BiSiO nanofibers. Below f0, the charge carriers penetrate at greater distances andare analogous to the scale of whole nanofibers network in the low frequency region. In this range, the impedance is formally corresponding to the dc resistance. For frequencies greater than f0, the carriers permeate at a smaller distance into each ac phase with charge carriers only inclining to travel within nanofibers. The changeover from extended range transport to localized carrier confinement is described by f0 in Z′. The term f0 is also associated with maximum peaks in Z″  calculated from the relaxation frequency that is obtained from fitting results of the complex impedance plots as a function of frequency. This plot follows the Arrhenius relation as25:Figure τo is the pre-exponential factor called characteristic relaxation time, T is the absolute temperature, Ea is the activation energy of the relaxation process, estimated from the slope of ln τ vs. 1000/T, and kB is the Boltzmann constant. Ea values for the BiSiO nanofibers are found to be 2.64 eV and 1.07 eV for bulk part and 2.27 eV and 0.64 eV for intergranular part respectively. Ea values are found to be elevated at low temperatures and decreased at relatively higher temperatures region for both bulk and intergranular interferences.Where, 26. Figure M′′). We can see two dielectric relaxations. The activation energies (Ea) for two relaxation processes corresponding to grain and intergranular are calculated using Arrhenius equation  two plateau regions and (ii) one dispersion region. The second plateau region appeared at intermediate frequencies. The size of the second plateau is decreased with an increase in temperature. It is very common in heterogeneous nanofibers. This additional plateau is attributed to difference in conductivity of bismuth and silicate network. This type of conduction mechanism is also represented for former heterogeneous nanofibers and bulk counterparts27. The increase in electrical conductivity of BiSiO nanofibers with temperature might be due to increase in drift mobility of thermally triggered charge carriers29.The entire ac conductivity (σ‘(ω)) of BiSiO nanofibers recorded in temperature range of 300 K–400 K and frequency range of 20 Hz to 2 MHz is represented in Fig. 29.σ0 is dc conductivity, A is the pre-exponential factor and s is the frequency exponent (0–2)30. The values of dc conductivity and s are presented in tabular form  with increase in temperature and frequency. These two variations explained either the conduction mechanism due to classical hoping of charge carrier above barrier or the quantum mechanical tunneling (QMT) or overlapping the large polaron tunneling27. However, in presently studied heterogeneous nanofibers, no frequency dependent of s is observed in the chosen frequency range. Therefore, the overall conduction mechanism is based on the temperature dependent s component. In this work, for low frequency regions where s < 1 the hopping involves a translational motion with an unexpected hopping; however for high frequency region where s > 1, the motion implicates localized hopping deprived of the species leaving the locality28. The variation of s as a function of temperature predicts the origin of conduction mechanism. For low frequency region the value of s increases with increase in temperature which can be explained by the large polaron QMT model19.Conduction mechanism in BiSiO nanofibers is further analyzed by investigating the deviation of frequency exponent  T < 360 K and (2) T > 360 K that give the values of Ea ~ 2.66 eV and 0.83 eV correspondingly as shown in Fig. Ea = 2.66 eV indicates the restriction in generation of the oxygen vacancies and formation of other types of defects such as space charge electrons. It can be supported by the interpretation of IV curves in the next section. While the Ea = 0.83 eV shows short range hopping motion of doubly ionized oxygen vacancies. For region 2, the Ea value is 1.49 eV. This phenomenon is also observed in ZrTiO3 as reported by Zhang et al.32. Furthermore, the Ea values estimated from conductivity are very close, which recommends that the electrical conductivity and the relaxation process may be endorsed by sort of similar charge carriers18.Arrhenius relation is used here to calculate the IV) characteristics were performed in the temperature range of 300 K–400 K for BiSiO nanofibers. Figure IV curves showing semiconducting behavior (Nonlinear). The typical IV characteristics show diode-like behavior33. Different factors can affect the IV characteristics e.g. device fabrication, surface density, nature of contact, temperature, applied field, nanostructure type and material etc. Different types of contact and bulk limited conduction mechanisms can occur in device. The rectifying diode-like behavior34 can be further investigated using ln-ln plot. In order to investigate the possible conduction mechanism, we have plotted the IV curves on ln-ln scale as shown in Fig. 33. This region shows that our nanofibers and electrical contact material have negligible work function difference. However, at higher voltages the slope of IV curves changes and charge injection region can be seen which may be followed by space charge limited conduction at higher voltages. This type of conduction can be seen in our previous research reports published elsewhere14. The increase in slope and absence of ohmic region indicates the charge injection region . The charge injection region occurs due to difference of injected carriers and carriers present inside material (BiSiO nanofibers) which may lead to the space charge limited current conduction.Current- Voltage  and (280 K–140 K). Moreover, the conduction mechanism was elucidated by large polaron QMT model followed by Maxwell-Wagner effect. The overall analysis of electrical measurements showed the NTCR character of the nanofibers. The IV characteristics exhibited space charge limited current conduction at intermediate voltage which was in agreement with impedance data.In summary, the BiSiO nanofibers were synthesized using electrospinning technique followed by heat treatment at 600 °C in an air furnace. The structural, complex impedance, conductivity and


In radiomics studies, researchers usually need to develop a supervised machine learning model to map image features onto the clinical conclusion. A classical machine learning pipeline consists of several steps, including normalization, feature selection, and classification. It is often tedious to find an optimal pipeline with appropriate combinations. We designed an open-source software package named FeAture Explorer (FAE). It was programmed with Python and used NumPy, pandas, and scikit-learning modules. FAE can be used to extract image features, preprocess the feature matrix, develop different models automatically, and evaluate them with common clinical statistics. FAE features a user-friendly graphical user interface that can be used by radiologists and researchers to build many different pipelines, and to compare their results visually. To prove the effectiveness of FAE, we developed a candidate model to classify the clinical-significant prostate cancer (CS PCa) and non-CS PCa using the PROSTATEx dataset. We used FAE to try out different combinations of feature selectors and classifiers, compare the area under the receiver operating characteristic curve of different models on the validation dataset, and evaluate the model using independent test data. The final model with the analysis of variance as the feature selector and linear discriminate analysis as the classifier was selected and evaluated conveniently by FAE. The area under the receiver operating characteristic curve on the training, validation, and test dataset achieved results of 0.838, 0.814, and 0.824, respectively. FAE allows researchers to build radiomics models and evaluate them using an independent testing dataset. It also provides easy model comparison and result visualization. We believe FAE can be a convenient tool for radiomics studies and other medical studies involving supervised machine learning. Radiomics extracts a large number of quantitative features from the regions of interest (ROIs) in medical images and maps them to clinical conclusions with machine learning (ML) , 2. RadiEstablishing radiomics models involves supervised learning, which is a subclass of machine learning. Most works of radiomics belong to a binary classification problem , which iIn the above process, there are many candidate algorithms in each step. To find the optimal model, researchers often need to explore different combinations of algorithms, which can be tedious and may require expertise in machine learning. To address this problem, we designed an open-source software package called FeAture Explorer, which can be used in radiomic studies. Researchers can use FAE to develop models with different combinations of feature normalization methods, feature selection algorithms, and classifiers. FAE can automatically try out all specified combinations of different algorithms and compare the performances of the established models on the validation dataset. Further, in radiomics studies, researchers usually focus on the interpretation of the features in the final built model. FAE also provides common clinical statistics and visualization of models, which helps to facilitate the comparison of different models.FAE has four major functions: Feature Extraction, Data Preparation, Model Development, and Results Inspection .Pyradiomics, an open-source module for radiomics feature extraction, was used in FAE . Users nTo use FAE, one must prepare a comma-separated values (CSV) file containing a feature matrix in the following format : 1) EachFAE can help develop a radiomics pipeline that includes the following steps: data normalization, dimension reduction, feature selection, and classifier. Available options for all the components are listed in FAE lists common clinical statistics and displays typical figures for model evaluation . The stahttps://python.org) and a Qt framework. Most algorithms in FAE were implemented with scikit-learn 0.19 (https://scikit-learn.org)  whosGLVDWI), interquartile range of the histogram from DWI (IRDWI), autocorrelation of the gray level cooccurrence matrix (GLCM) from DWI (ACDWI), and 10% percentage point of the histogram from ADC (10PerADC).Features selected by FAE were the gray level variance of the gray level size zone matrix (GLSZM) from DWI  and compared their AUCs on the validation dataset to find the optimal model. Then, FAE was used to find a more robust model that used four features but achieved a comparable AUC. We used an independent testing dataset to evaluate the performance of the final model. The AUC of 0.824 on the test dataset is comparable to that in the work of L. Wang . The AUCFAE can be used not only for radiomics studies but also for supervised binary classification problems. Since all processors  in the FAE pipeline are independent of each other, researchers can add their own algorithms to construct specific pipelines. In addition, since FAE saves all intermediate results in the pipelines, researchers can process these intermediate results with other software. For instance, researchers often compare the model built with only clinical features and the model with image features. FAE can build the radiomics model and export selected radiomics features. Then we can combine them with the clinical features for model development . MoreoveWe used pyradiomics in FAE to extract image features. However, we did not integrate a UI for ROI labeling. ROI labeling requires real time interaction and is often compute-intensive when semi-automatic segmentation algorithms are involved, where C and C++ programs are more suitable. Some free  or commercial  software packages can be used for ROI labeling. While some of them can also be used for feature extraction, FAE is more efficient because it can extract all desired features from all cases and combine them into a feature matrix in one click.There are several limitations of FAE as follows: 1) In machine learning, the hyperparameters of the feature selection and classifiers have an important effect on the performance of the model . While FFAE provides a convenient way to develop radiomics models. Radiologists can use FAE to clean the feature matrix, develop different models, compare the performance, and visualize the results for their own radiomics studies. We opened the source code of FAE, and researchers can use it freely and extend it to test new ideas and algorithms at will.


Redox‐active molecular junctions have attracted considerable attention because redox‐active molecules provide accessible energy levels enabling electronic function at the molecular length scales, such as, rectification, conductance switching, or molecular transistors. Unlike charge transfer in wet electrochemical environments, it is still challenging to understand how redox‐processes proceed in solid‐state molecular junctions which lack counterions and solvent molecules to stabilize the charge on the molecules. In this minireview, we first introduce molecular junctions based on redox‐active molecules and discuss their properties from both a chemistry and nanoelectronics point of view, and then discuss briefly the mechanisms of charge transport in solid‐state redox‐junctions followed by examples where redox‐molecules generate new electronic function. We conclude with challenges that need to be addressed and interesting future directions from a chemical engineering and molecular design perspectives. In recent years, redox‐active molecules have contributed significantly to the development of functional molecular junctions including molecular diodes, molecular memory and molecular transistors. This minireview gives an overview of recent progresses in functional redox‐active molecular junctions and introduces the underlying operating mechanisms of the different types of functional molecular junctions. Consequently, there is virtually no information available on the chemical and supramolecular organization of single‐molecule junctions. Although single‐molecule junctions are assumed to be “single‐molecule”, neighboring molecules are present , which are usually ignored. Thus, it is important to realize that in analysis of data obtained from single‐molecule junctions usually a “perfect” junction structure is assumed without experimental verification.Molecular junctions can be categorized into single‐molecule junctions Figure a where oe. g., Au, Ag, or Pt).in situ optical methods  where excitation of molecular vibration modes,EF, under applied voltage bias, V. In the weak coupling limit, the charge carriers can interact strongly with molecules resulting in formal redox‐reactions inside the junctions and the mechanism of charge transport is incoherent tunnelling . In the strong coupling limit, the charge carriers interact weakly with the molecules. Consequently, redox‐reactions cannot occur and coherent tunnelling dominates the mechanism of charge transport. Although different redox‐states of molecules are readily stabilized under wet‐electrochemical conditions by solvent molecules and counterions, these stabilization mechanisms are not present in solid‐state molecular junctions, and, instead, charges on the molecule induce image charges in the electrodes.[β . To fully appreciate the differences between redox‐processes under wet‐electrochemical conditions and in solid‐state junctions, we introduce briefly the single‐level Landauer theory for coherent tunnelling,Incorporating redox‐active molecules in molecular junctions Figure c is an aRecently, reviews have appeared which give a broad overview of the field of molecular electronics, the type of electronic functions that can be achieved, and how molecular junctions are fabricated.1e, 1f2Broadly speaking, the mechanisms of charge transport can be categorized as coherent and incoherent tunnelling which are described by the Landauer and Marcus theory, respectively, both of which rely on a number of assumptions. In reality, however, molecular junctions often show more complex behavior which cannot be fully understood within the framework of either theory and therefore a large number of extensions, alternatives, and combined theories have been proposed.9, 16 2.1EHOMO), or lowest unoccupied molecular orbitals (ELUMO), with respect to EF defines the tunnelling barrier height , and the molecular length defines the tunnelling barrier width d. In case the molecular frontier orbitals fall outside the conduction window , the mechanism of charge transport is off‐resonant coherent tunnelling , resonant tunnelling dominates where the charge carriers can tunnel through this level, which increases the measured currents considerably. In this case, depending on how the charge carrier interacts with the molecules, the mechanism of charge transport can be coherent or incoherent tunelling.kET of incoherent charge transfer processes usually encountered under wet‐electrochemical conditions where the redox‐molecules undergo formal oxidation or reduction which are accompanied by structural reorganization within the molecule and solvent molecules given by re‐organization energy λ.+. Although Marcus theory usually describes solution based redox‐processes, below we discuss examples in solid‐state junctions.Figure g Figure a. Howeve2.2I, through metal‐oxide barriers. In the low bias regime, I is given by:Off‐resonant tunnelling is usually described by the Simmons theory18 whiche is the electron charge, me is the effective mass of the electron, α is a parameter to modify the tunnelling barrier shape , and ħ is reduced Planck's constant. In this framework, the charge carrier tunnels across a potential barrier with the tunnel barrier height δEME,H or δEME,L and width d defined by the molecules. The role of image charge effects  and the meaning of effective electron mass in the context of molecular tunnel junctions are both unclear. Thus, a major shortcoming of this analysis is that image charge effects, effective electron mass, and the tunnelling barrier heights are usually treated as fitting parameters. Assuming linear potential drops, Equation 1 can be simplified to the “general tunnel equation”[where β, and J0 is a pre‐exponential factor .which defines the tunnelling decay coefficient 2.3T of a charge carrier from one macroscopic electrode to another separated by a mesoscopic quantum mechanical scatter (here the molecule), and is given byTunnelling through molecular orbitals can be described by the Landauer‐Büttiker formalism22 whereE is the energy of the charge carrier, f(E) is the Fermi‐Dirac distribution of the electrodes given by Equation T is the transmission function given by Equation where T is absolute temperature, and kB is the Boltzmann's constant, ΓL and ΓR denote the coupling with the left and right electrodes  is the energy offset between molecular energy level and EF under applied bias V, which is given by Equation where s Figure a, δEME β and also decreases exponentially with molecular length  but with significantly smaller values of β (<0.1 Å−1)This framework accounts, unlike the Simmons equation, for molecule‐electrode interactions and associated broadening of molecular energy levels. Also, in this framework, charge transport is nearly independent of the applied temperature, but a thermal broadening of the Fermi‐levels can cause a small temperature dependency.2.4+ in solution where the Gibbs free energy of the reaction, ΔG0, is defined (curve 1). For an exothermic reaction with an energetically favourable electron transfer reaction where M+ has a lower energy than M  defined by the intersecting parabolas. Assuming the Frank‐Condon principle holds,[+. This distortion of M is the transition state and requires energy. The Gibbs free energy of the formation of the transition state involves the re‐organization energy λ which is also defined in Figure kET is given byFigure HMM+ is the electronic coupling strength between M and M+. This equation has the same form as the Arrhenius equation (note J is used instead of kET for straightforward comparison with Equation 2) where Ea and the pre‐exponential factor J0.but, importantly, the Marcus theory provides a quantitative description of the activation energy T. Consequently, temperature‐dependent charge transport measurements are normally used to discriminate between the two processes. Charge transfer rates (or currents) dominated by coherent off‐resonant processes are very sensitive to the molecular length [i. e., very low β values).i. e., small β values).[Ea=0 eV yet the charge transfer process is incoherent. Thermal broadening of the Fermi level (Equation 4) also results in a small thermally activated component in case of coherent tunnelling which could be mistakenly attributed to hopping. In case ΔG0 increases further, the charge transfer reaction slows down again due to the presence of an activation barrier (curve 3). This decrease in the electron transfer rate with increasing ΔG0 is called the inverted Marcus region. Although a reduction of kET with increasing ΔG0 has been observed in solution,Ea in the inverted region, resulting in activationless charge transport[Normally, incoherent tunnelling involves redox‐processes that are thermally activated while coherent tunnelling is essentially independent of β values)21 while2.5et al.+ are expressed as: Coherent (Eqs. 1–6) and incoherent tunnelling (Eqs. 7 and 8) represent the two extremes to describe the mechanism of the charge transport. As mentioned earlier, molecular tunnel junctions, on the other hand, can operate in between these two regimes depending on the molecule‐electrode coupling strength, the availability of molecular energy levels and vibrational modes that resemble the transition of the redox reaction.28 AlthoΓ(E) is Fermi's golden rule charge transfer rate between the molecule energy level and electrode. Figure + inside the junctions where it is important to note that points M and M+ represent different points on the reaction coordinate, rc, rather than a tunnelling distance. The energy difference (ΔE) between the energy of M (EM) and M+ (EM+) surface is given by ΔE=EMrcM-EM+rcM++EFwhere rcM and rcM+ indicate the respective points on rc.where et al.G0 changes due to changes of EF under the action of applied V by, for instance, intramolecular orbital gating.+ on the reaction coordinate. In the situation where EF crosses M  is the time dependent phononic correlation function, and the subscripts ox and red denote oxidation and reduction processes. The current is given in the following expression: where where the super scripts L and R denote the left and right electrode. This model also bridges the Marcus theory and the Landauer formalism, but this framework is especially useful to extract the vibrational reorganization energy (Section 3.4).33.1β for aliphatic or conjugated molecules are relatively high mainly due to large values of δEME. In contrast, redox‐active molecules have the EHOMO or ELUMO close in energy to EF and, consequently, low δEME and small β[Γ is large enough which is usually the case in single molecule junctions. Extremely low β values have been reported for junctions with redox‐active molecules.[et al.β=0.04 Å−1 for oligo‐porphyrin wires compound 1 . The energetically low‐lying LUMO of the viologen (which is −4.5 eV) falls in between the Fermi levels of the Au (−5.1 eV) and Ti (−4.1 eV) electrodes, along with a large Γ induced by the covalent Au−C bond, both point to a resonant tunnelling process across these molecular junctions.As mentioned in Sections 2.2 and 2.4, normally the values of et al.T is close to 1, Equation 5) charge transport across ferrocene (Fc) oligomers compound 3 with n=1, 2 and 3 in scanning tunnelling microscope (STM) break junctions . A similarly high conductance with G=0.7 G0 has also been observed by Getty et al.4) in single‐molecule junctions  tip as the top electrode with varying length of 1.5 to 7.3 nm by changing the number of OPI repeat units n from 1 to 10. Figure β=0.3 Å−1 is much larger for small values of n <5, than that for junctions with large values of n >5 with β=0.09 Å−1. Consequently, charge transport is activationless for n <5, and is thermally activated with Ea=280 meV for n >5  ‐ pyromellitic diimide (PMDI) oligoimine  as shown in Figure et al.d<8 nm, activated hoping for d>16 nm and activationless field induced ionization for d=8 to 22 nm. In contrast, Chen et al.Coherent tunnelling always dominates the mechanism of charge transport for sufficiently small values of  large d.32 There3.3e. g., electrochemical STM based break junctions, electromigrated break junctions, or junctions with scanning electrochemical microscopes.et al.7) based junction where NDI is an electron acceptor which can be reduced via two consecutive one‐electron steps. This change of the redox‐state from neutral NDI to the dianion results in a factor of 10 change in the conductance of the junction  derivatives, a distinct gating effect on the conductance was observed which is related to the reduction ability of the molecule tuned by the substituents  based single‐molecule junctions  as the acceptor where charge can hop from the donor to acceptor as indicated by the Marcus parabolas in Figure Ea to a maximum value when both parabolas have the same energy after which Ea decreases again until the parabolas intersect at their minimum as the system approaches the inverted Marcus region beyond which Ea remains 0 meV as explained earlier (Section 2.5). Yuan et al.Eavs. V curve  along the molecule is essential for rectification which is given by the potential division parameter η=VL/(VL+VR). When η≈1, the HOMO closely follows the changes in EF,R while the opposite is true for η≈0  where the redox active Fc units (at which the HOMO is centered) are in close contact with the right electrode but separated from the left electrode by the long alkyl chain resulting in η≈1.Ea=77 meV) while at positive bias the mechanism of charge transport is activationless.et al.R to 1000 at ±1.0 V. A similar change in the mechanism of charge transport has been also reported by Luo et al.14 with R of 30 at ±1.0 V  which was first demonstrated in Fc (compound 15) based molecular diodes shown in Figure et al.16) as the donor and anthraquinone  as the acceptor. Chen et al.R=6.3×105 at ±3 V  in only one bias direction  with a Mo redox centre. The junctions suffered from poor reproducibility and were divided in 2 groups based on their performance: group 1 had current on/off ratios ranging from 1.5 to 20 while group 2 had current on/off ratios of up to 1000  and I(t) measurements  in Fc‐based molecular junctions at 77 K.Molecular switches can toggle between two different conductance states under the action of external stimuli, such as, light, magnetic field, changes in pH or electrical filed.3d, 56II) bis‐acetylthiophenylterpyridine complex 20 with M=Fe, Ru, Co. The threshold voltage measured over 50 devices for each complex is 1.5–1.9 V for Fe, 1.7–2.1 V for Ru, and 1.9–2.3 V for Co  SAMs based junction with a current on/off ratio of 6 which was attributed to the modulation of the bond topology through reduction/oxidation of the TCNAQ molecules . However, MC spontaneously thermalizes back to SP. By exposing MC to acid, MCH+ is formed which blocks the reverse reaction resulting in devices with stable on‐states  with high current on/off ratios of 6.7×103 and rectification ratios of 2.5×104. This combined diode (D) and variable resistor (R) functionality is called 1D‐1R memory which is promising to reduce power consumption in cross‐bar arrays.Tunnel junctions naturally operate in extremely high electric fields of 0.1–1 GV/m. Therefore, it is challenging to stabilize different redox‐states of the molecules inside the junctions by relying solely on the re‐organization energy 4.311 ,[The disadvantage of single molecule junctions over large‐area junctions is that they suffer from large junction‐to‐junction variations due to uncertainties in the atomistic configuration of the junction (eometry),1e, 1g3−Au junctions . He obtained his Ph.D. degree from the University of Twente in 2006  under the supervision of Prof. David N. Reinhoudt and Prof. Jurriaan Huskens and then started (2007) a post‐doctoral fellowship in the group of Professor George M. Whitesides. After receiving the National research foundation (NRF) research fellowship of Singapore in 2010, he started his group at NUS. His current research interests include molecular electronics, quantum plasmonics, nanofabrication, self‐assembly and surface science.


A series of polycarboxylate superplasticizer (PCE) polymers were synthesized from acrylic acid (AA) and isoprenyloxy polyethylene glycol ether (IPEG) at the mole ratios of 3.0, 4.2, 5.0 and 6.0. In this study, the molecular weight properties of PCE polymers were recorded by size exclusion chromatography with the time interval of 1 h. Mini slump test was used to detect the dispersing effectiveness of PCE polymer in cement paste. The results indicated that the reaction rate of monomers, conversion of 52IPEG macromonomer and molecular weight of PCE polymers increased with the general adding ratio of AA to IPEG macromonomers while the side chain density of PCE polymers decreased. PCE polymers possessed molecular weight around 30,000 g/mol with low side chain density, and long main chain length presented high initial dispersing effectiveness at the low dosage around 0.12%. The majority of effective PCE polymers were formed during the adding period of acrylic acid in the first 3 h. M] but inversely proportional to the square root of initiator concentration [I]. The kinetic chain length ν would vary with the monomer concentration [M] exclusively under the fixed initiator concentration and reaction temperature. Here, dk, pk and tk are designated as chain initiation rate constant, chain propagation rate constant and chain termination rate constant, respectively.Polycarboxylate superplasticizers (PCE) provide concrete high fluidity, strength and excellent durability at low content, which efficiently promotes the development of construction industry ,2,3. TheF in polymer is affected by the mole ratio f and reactivity ratio r of monomers in binary copolymerization according to Formula (2). The reaction of PCE is non-ideal copolymerization, for the reactivity ratio of unsaturated carboxylic acid r1 is greater than 1 while the reactivity ratio of polyethylene glycol macromonomer r2 is less than 1. Additionally, the steric hindrance effect caused by the high content of ethylene glycol in macromonomer decreases the reaction rate of polymerization, which causes the major isoprenyloxy polyethylene glycol ether (IPEG) macromonomer synthesized via comopolymerization rather than homopolymerization. Therefore, all the IPEG macromonomer is added into the reaction system at the beginning while unsaturated carboxylic acid is dropped added in a typical synthesis of PCE. Thus, the concentration ratio of IPEG macromonomer to acrylic acid decreased because of the successive consumption of macromonomer and adding of unsaturated carboxylic acid. PCE polymers with diverse molecular weight and side chain density formed as the transformation of dissociative monomer concentration and instantaneous completion of free radical copolymerization process [The monomer composition  process ,16,17,18A/E value). The molecular weights, mass fraction of polymers, transformation of side chain density and main chain length of PCE polymers were all derived by size exclusion chromatography (SEC) data. Apparently, the molecular structures of PCE samples have obvious correlation with the general monomer ratios added as well as their feeding speed. PCE polymers with high A/E value showed higher content of acrylic acid and molecular weight. The molecular weight of polymers decreased as the feeding of acrylic acid. The conversion of macromonomer increased with the A/E ratio. The effective PCE polymers were produced in the first 3 h. The influence of molecular properties of PCE polymers on the dispersing effectiveness in cement paste was also discussed in this study. Thus, PCE polymers with different molecular structures and dispersing effectiveness could be optimized.It was a goal of the study to distinguish the differences of molecular properties and reaction rates of PCE polymers with different feeding ratio of monomers. A series of PCE samples were synthesized from acrylic acid and isoprenyloxy polyethylene glycol ether via aqueous free radical copolymerization at different mole ratios (The isoprenyloxy polyethylene glycol ether containing 52 ethylene oxide (EO) units with the molecular weight around 2400 g/mol (52IPEG) was provided by Oxiranchem, Liaoning, China. IPEG containing long chain were adopted in this study for the short type was too sensitive to the mole ratios of unsaturated carboxylic acid to IPEG macromonomers. Acrylic acid (AA), ammonium persulfate (APS) and 3-mercaptopropionic acid (3-MPA) were all purchased from Sigma-Aldrich Chemie GmbH, Milwaukee, Germany.The cement CEM I 52.5 used for the mini slump test was supplied by Heidelberg Cement, Germany. The phase composition detected by quantitative X-ray diffraction including Rietveld refinement (Bruker axs D8) is shown in 52IPEG series PCE polymers were synthesized by acrylic acid and 52IPEG macromonomer at the mole ratios of 3.0, 4.2, 5.0 and 6.0 via aqueous free radical copolymerization. The mole ratio of the reactants in 52IPEG3.0 sample 52IPEG: AA: APS: 3-MPA was 1.0:3.0:0.17:0.26. A typical preparation method of 52IPEG3.0 was described as following: 52IPEG solution was placed in a flask immersed in a water bath at the temperature of 60 °C. AA and 3-MPA was dissolved by deionized (DI) water and designated as solution A, while APS was dissolved by DI water and designated as solution B. Solutions A and B were dropped into the flask continuously for 3 h and 2 h preservation were still needed after the feeding of solutions. Finally, the reaction system was cooled down to 45 °C and adjusted to around pH 7.5 by base solution. 52IPEG3.0 at a solid content of 39.5% was obtained.TM columns 120, 250 and 500 from Waters, Eschborn, Germany. The molecular weight, polydispersity index and hydrodynamic radius of 52IPEG series PCE were detected by a three-angle static light scattering detector from Wyatt Technology Corp., Santa Barbara, USA. Meanwhile, the concentrations of different compositions were measured by a differential refractive index (RI 2424) detector from Waters, Eschborn, Germany. The 52IPEG series PCE was dissolved to the testing concentration of 10 g/L by DI water. A 0.1 N NaNO3 solution at the pH of 12.0 was used as the eluent. The dn/dc value (refractive index increment) of polyethylene glycol (0.135 mL/g) was fixed as the value of 52IPEG series PCE.52IPEG series PCE polymers with different sizes were separated by a 2695 Separation Module with three UltrahydrogelThe fluidity of cement paste added PCE was carried out according to DIN EN 1015 at a w/c of 0.3. The dosages of PCE were recorded when the fluidity of cement paste achieved 26 ± 0.5 cm to compare the dispersing effectiveness. The vicat cone mold filling the cement paste was 40 mm height, 70 mm top diameter and 80 mm bottom diameter.A/E among 3.0 and 6.0 exhibited in A/E increased the final conversion of 52IPEG macromonomer.There was no obvious split and show narrow molecular weight distribution for the final products of 52IPEG series PCE polymers in the SEC spectra with A/E [Generally, the molecular weight of 52IPEG series PCE polymers decreased during the adding of acrylic acid in the first 3 h and was followed by steady curves for the last 2 h as shown in A/E ,21. It cThe concentration of monomers has been changing all through the reaction, which brings the continuous variation of polymer structures. The molecular weight of polymer climbed rapidly in the first 3 h before the feeding of AA finished according to The molecular weight properties of 52IPEGs were recorded by SEC spectra with the time interval of 1 h. Here, the samples were not separated from the polymers produced before. The polymer SEC spectra revealed the variation of reaction rate of 52IPEG3.0 in different periods in A higher reaction rate of 52IPEG4.2 was presented in An extremely high mass fraction (52.2%) of polymers in 52IPEG5.0 was detected for the 1st hour in A/E was higher than 5.0. A/E improved the molecular weight of PCE polymers with a higher value according to The amounts of produced PCE polymer and consumed IPEG macromonomer of 52IPEG6.0 were slightly higher than that of 52IPEG5.0 and their mass fraction curves almost coincided in W and i, respectively. The mass average molecular weights of 52IPEGs polymers produced each hour could be calculated based on Formula (3)  . The resA/E 6.0 and the lowest A/E 3.0 showed greater fluctuation for the molecular weights in different time intervals. The high A/E value increased the side density of polymers as well as its molecular weights during the adding of AA. Whereas there were few macromonomers left in the reaction system (except 52IPEG3.0) after 3 h, the target products should already have gained in the first 3 h. It would be energy conservation modification in the actual production once it was confirmed in application.Generally, the molecular weight of polymers with a time interval of 1 h decreased in the first 3 h, which agreed with the trend in A/E of dissociative monomers during the copolymerization. In this case, more acrylic acid should be added every half or 1 h on the decrease. The general molecular weights of polymers in 52IPEG4.2 in different time intervals were quite similar but possessed a decreasing side chain density. Take 52IPEG4.2, for example; its side chain density would increase if the adding amount of acrylic acid reduced in the 2nd h. The optimal polymers can be obtained after a series of trial and error.The ideal way to get a relatively uniform side chain density and main chain length PCE sample was to try to keep the constant The mass fraction of polymers with different molecular weights was presented in A/E of IPEG3.0 and its molecular weight were much lower than other samples in the entire process. The dispersing effectiveness of 52IPEG3.0 polymers with particular structures could be deduced with the conclusion above and flow spread of cement paste [According to the analysis of the molecular weight properties of nt paste ,27. The The cement pasted added 52IPEG3.0 at an extremely high dosage of 0.26% by the weight of cement (bwc) kept high fluidity more than 5 h with the required initial 26 ± 0.5 cm flow spread according to 52IPEG4.2, 52IPEG5.0 and 52IPEG6.0 achieved the flow spread of 26 ± 0.5 cm at the dosage around 0.12% bwc. There were two types of polymers with different structures contained in the 3 PCE samples. One type presented high molecular weight, high side chain density and short main chain length, which was produced earlier, providing the slump retention of cement paste; another type presented low molecular weight, low side chain density and long main chain length, providing high initial flow spread. It was obvious that PCE polymers with low side chain density provide initial dispersing effectiveness, and polymers with high side chain density offer the later retention ability.A/E value of 3.0, 4.2, 5.0 and 6.0 were studied. The molecular weight, main chain length and reaction rate of PCE polymers as well as the conversion of macromonomers increased with the general adding ratio of acrylic acid to 52IPEG macromonomers. Polymers with a mass fraction of 53.8% were detected in 52IPEG6.0 after 1 h, and it was even higher than that of polymers of 52IPEG3.0 produced in the first 2 h.The structures of PCE polymers synthesized at the A/E value during the reaction process in a certain PCE sample. The continuous feeding of AA during the reaction was the reason that lowered the side chain density of polymers. PCE polymers produced in the 1st hour possessed the highest side chain density and molecular weight. It was the key period for the structure control of PCE polymers especially for high A/E value ones. The major effective polymers were produced during the adding of acrylic acid in the first 3 h.The side chain density of polymers decreased with the general High dosage of 0.26% for 52IPEG3.0 was needed to reach the required initial cement paste flow spread of 26 ± 0.5 cm, yet it exhibited excellent retention ability. Around only 0.12% dosages were needed for other PCE polymers, but their retention properties were not that good. 52IPEG4.2 possessed a molecular weight of around 30,000 g/mol and moderate side chain density; main chain length was a proper choice for the application. The structure of PCE polymers with certain properties could be designed based on influence factors.


Agricultural residues are major potential resources for biomass and for material production. In this work, rice straw residues were used to isolate cellulose nanofibers of different degree of oxidation. Firstly, bleached rice fibers were produced from the rice straw residues following chemical extraction and bleaching processes. Oxidation of rice fibers mediated by radical 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO) at pH 10 was then applied to extract rice cellulose nanofibers, with diameters of 3–11 nm from morphological analysis. The strengthening capacity of rice nanofibers was tested by casting nanocomposite films with poly polymer. The same formulations with eucalyptus nanofibers were produced as comparison. Their thermal and mechanical performance was evaluated using thermogravimetry, differential scanning calorimetry, dynamic mechanical analysis and tensile testing. The glass transition of nanocomposites was shifted to higher temperatures with respect to the pure polymer by the addition of rice cellulose nanofibers. Rice nanofibers also acted as a nucleating agent for the polymer matrix. More flexible eucalyptus nanofibers did not show these two phenomena on the matrix. Instead, both types of nanofibers gave similar stiffening (as Young’s modulus) to the matrix reinforced up to 5 wt.%. The ultimate tensile strength of nanocomposite films revealed significant enhancing capacity for rice nanofibers, although this effect was somehow higher for eucalyptus nanofibers. In fact−1, and this value could increase by 1.3 Pg dry matter yr−1 considering the current progress towards highly intensive agriculture [Crop residues are defined as the nonedible plant parts that are left in the field after harvesting. Global production of residues from the six main crops  is estimated to be of around 3.7 Pg dry matter yrThe lignocellulosic character of agricultural residues makes them suitable as source of cellulose fibers, which are the most abundant biopolymers on earth. The hierarchical structure of cellulose fibers is unique, with linear β-1,4-glucan chains forming microfibrils of 3–4 nm diameter (about 30–40 chains), that bond together in bundles resulting in microfibers that intermix with hemicelluloses at the secondary and primary layers of the plant cell wall, with lignin mainly at the primary layer and middle lamella . The extNanocomposites are materials made up of at least two different phases where one component has some dimension in the nano range, typically below 100 nm or even below 50 nm. Structurally, nanocomposites are materials that involve nanosized filler particles (dispersed phase), a matrix (dispersion phase), and an interfacial region. The main advantage of nanocomposites compared to conventional ones is their unique characteristics due to their large surface area to volume ratio . TherefoPoly (PVA) is the largest synthetic water soluble polymer produced in the world ,11. It iIn this work, cellulose nanofibers from rice straw residues are obtained and used for the production nanocomposite materials. The performance of rice nanofibers will be compared to other well-known cellulose nanofibers from common sources like wood. Rice straw was first submitted to a chemical bleaching process to obtain rice cellulose fibers, followed by an oxidation mediated by radical 2,2,6,6-Tetramethylpiperidine 1-oxyl (TEMPO) as pretreatment to further extract rice cellulose nanofibers. Nanocellulose fibers from rice straw are tested as reinforcing element of poly polymer matrix. The hydrophilic character of the matrix is chosen as model for a fully favorable nanofiber–matrix interface in order to analyze the potential of rice cellulose nanofibers. The nanocomposites were prepared by casting to ensure proper dispersion and distribution of the nanofibers into the polymer. The thermal and mechanical properties of the nanocomposites are analyzed and compared to other currently used cellulose nanofibers.Oryza sativa species and of the appellation “Arroz de Valencia”, was used as the raw material to extract cellulose nanofibers for the further preparation of composite materials. Rice straw was air-dried for over 24 h and then cut into lengths of about 3–5 cm. Characterization of the raw material was performed according to the Tappi test methods : hot water extractives (T 207 cm-99), benzene-ethanol extractives (Tappi 204 cm-97), α-cellulose (Tappi 203 om-93), and Klason lignin content (Tappi T222 om-98). The holocellulose was determined by treating the extracted rice straw with NaClO2 solution. For comparison, cellulose nanofibers from eucalyptus were also used as polymer reinforcement.Rice straw from the Poly (PVA) from Sigma Aldrich  was used as the polymer matrix. PVA, supplied as white powder, had a molecular weight of around 70000 g/mol and was 87–90% hydrolyzed.2) and acetic acid (CH3COOH). Further oxidation reaction of rice straw fibers was carried out using the radical 2,2,6,6-Tetramethylpiperidine 1-oxyl (TEMPO), sodium bromide (NaBr), sodium hypochlorite solution (NaClO) 15% w/v, sodium hydroxide (NaOH) and hydrogen chloride (HCl). For the evaluation of carboxyl groups, methylene blue in powder was used with a buffer solution made from boric acid (H3BO3) and potassium chloride (KCl). Finally, for the viscosimetric analysis, cupriethylenediamine (C2H6CuN2) was used as cellulose solvent. All chemical reagents were supplied by Sigma Aldrich and used as received.For solvent extraction, ethanol, benzene and toluene were used. Bleaching of rice straw was performed with sodium chlorite (NaClO2) and 5 g of acetic acid (CH3COOH) in 1 L of distillate water. Stirring was maintained for 4 h at 80 °C. Rice fibers were afterwards thoroughly rinsed with distillate water. A second bleaching step was performed under the same chemical conditions for 2 h at room temperature. After proper rinsing, the rice fibers were kept at 4 °C in the fridge. The mean fiber length and diameter of the obtained rice straw fibers were analyzed by means of a MorFi Compact fiber analyzer from TECHPAP . For this purpose, a dilute suspension of fibers (25 mg/L) was analyzed using an optics and flow cell measurement. Data of more than 3000 fibers were analyzed and the fiber length distribution, diameter distribution, as well as the mean values, were obtained.Rice straw was chopped using knives, milled, and meshed with a 40-mesh (400 μm) screen. The retained matter was submitted to solvent extraction with ethanol/toluene (40/60) for 24 h to remove pectin, waxes, and fats. After drying at atmosphere conditions, rice straw fibers were bleached as follows: 50 g of rice fibers were immersed in a solution containing 5 g of sodium chlorite (NaClOTEMPO-mediated oxidation at basic conditions was used as pretreatment for the extraction of cellulose nanofibers. Rice straw fibers (1 g) were suspended in water (100 mL) in the presence of TEMPO radical  and sodium bromide . Sodium hypochlorite solution (NaClO) of 15% w/v was added in the suspension and the pH was adjusted to 10 by adding hydrogen chloride 0.1 M. Magnetic stirring was applied to the suspension in order to assure good dispersion of all the substances. The oxidation reaction started when the desired amount of NaClO was added into the system. In this case, different oxidation degrees were tested by adding 3, 5, 8, or 12 mmol of NaClO per gram of cellulose fiber. The addition was dropwise at room temperature with constant stirring of about 500 rpm. The pH was maintained constant at 10 by continuous addition of sodium chloride. The reaction finished when the pH was constant ,19.After oxidation, the cellulose fibers were centrifuged at 10,000 rpm for 10 min, to remove all the chemical reagents. The supernatant was discarded and the solids were resuspended in distillate water and centrifuged again. The process was repeated five times. The final suspension was 1% by weight. This suspension was disintegrated using and Ultraturrax IKA T24 digital working at 20.000 rpm during 5 min. The final appearance was a transparent gel-like suspension that was kept at 4 °C in the fridge for further use. This rice cellulose nanofibers were named r-CNF.The TEMPO-mediated oxidation of cellulose fibers from eucalyptus fibers was carried out at neutral pH conditions according to methodology reported elsewhere . The euc−1 optical resolution within the range 600–4000 cm−1. The samples were cut in about 5 × 5 cm and were immersed for 5 s in an HCl 0.1 M solution with the aim of acidifying the carboxylate groups.Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy was performed on a Mattson Satellite spectrometer  equipped with a MKII Golden Gate Reflection ATR System. Spectra of the different oxidized rice cellulose nanofibers were recorded by co-adding 64 scans at 4 cmna is the amount of nonadsorbed methylene blue (mg) and w is the dry weight of the sample (g).The carboxyl content of oxidized fibers was measured by UV-visible spectroscopy with the methylene blue method ,22. Herew is the wet weight (g) and Wd the dry weight (g).The water retention value (WRV) was measured by separating a determined volume of cellulose nanofibers gel into two equal portions, which were then centrifuged in a Sigma Laborzentrifugen model 6 K15 at 2400 rpm for 30 min to eliminate nonbonded water. In order to retain the NFC, a nitrocellulose membrane with a pore diameter of 0.65 μm was used at the bottom of the centrifuge bottles. Once centrifuged, only the NFC in contact with the membrane was removed, weighed, and then dried at 105 ± 2 °C for 24 h in containers of previously measured weight. This methodology is based on Tappi um 256. The average WRV value was then calculated according to the next equation:The degree of polymerization (DP) was determined from intrinsic viscosity measurements, according to UNE 57-039-92 (which agrees with ISO 5351-1:1981) using cupriethylenediamine as solvent. The correlation between the intrinsic viscosity DP > 950 ,24.Original fibers were observed by scanning electron microscopy. For this, the used microscope was ZEISS DSM 960  operating at 25 kV. Specimens were previously coated by sputtering 10 Nm gold at the surface. On the other hand, cellulose nanofibers were observed using transmission electron microscopy (TEM) by means of a ZEISS EM 910 Transmission-Electron Microscope . Samples were prepared by diluting the gel suspensions 10 times in distilled water. Later, 8 μL of the diluted nanocellulose suspensions were deposited on the membrane grid and, after drying, it was dyed with a 1% solution of uranyl acetate for 3 min. The surplus was removed with absorbent paper for the observation.For the preparation of nanocomposites, 12.5 g of poly (PVA) were dissolved in 250 mL of water at 10 °C in high magnetic stirring. The gel of cellulose nanofibers was diluted until 0.1 wt.%. Different amounts of cellulose nanofibers, from rice straw (r-CNF) or from eucalyptus (h-CNF), were mixed with the polymer solution in order to obtain nanocomposites comprising 0.5, 1, 2.5, and 5 wt.% of nanofiber reinforcement. Nanocomposite suspensions of 2 g dry weight were prepared. The PVA-nanocellulose suspensions were homogenized by stirring for 1 h, and cast in petri dishes afterwards. The suspensions were dried in an oven at 37 °C for four to five days. A transparent film was obtained from where the specimens were cut for material characterization. A scheme illustrating the production process of the PVA-CNF nanocomposites is presented in g), melting temperature (Tm), melting enthalpy (ΔHm), and degree of crystallinity (Xc) were deduced from DSC analysis. Two heating/cooling procedures were applied.Thermal characterization of the nanocomposites was conducted from differential scanning calorimetry (DSC) tests using Mettler Toledo DSC822 equipment . Around 7–9 mg of sample was placed in the 40 μL aluminum capsule. The temperature ramp was from 30 to 240 °C at a 10°/min heating rate under nitrogen flow of 40 μL/min. Values of glass-transition temperature  was also performed using Mettler Toledo TGA851 equipment . For this, samples of around 10–15 mg were disposed in a 70 μL aluminum capsule. The assay was carried out from 30 to 650 °C at a 10°/min heating rate and under nitrogen flow of 40 μL/min. The degradation temperatures were obtained from the first derivative of the mass loss curve (DTG).Prior to mechanical characterization, the specimens were conditioned in a Dycometal  climatic chamber at 23 °C and 50% relative humidity for 48 h before the tensile test and the dynamic mechanical analysis, according to ASTM D618 standard. Nanocomposite samples were mechanically tested in a universal testing machine Hounsfield model 42  equipped with a 2.5 kN load cell. Sample dimensions were 5 mm wide and 45 mm long, and had a thickness of 0.2–0.3 mm. Preload was 0.1 N and cross-head speed was 5 mm/min. The results obtained were the average of at least five tested samples and data scattering within the range of 5–9%.Dynamic mechanical analyses (DMA) of conditioned samples were performed using a Mettler Toledo DMA/SDTA861 instrument . The DMA measurements were done operating at tensile mode, at constant frequency of 1 Hz, amplitude of 20 μm and temperature range from −50 to 130 °C at a heating rate of 5°/min. The specimen dimensions were 5 mm width and 22.5 mm length, with thickness of 0.2–0.3 mm.The valorization of agricultural wastes from rice crops is proposed in this study. In particular, we investigate the use of rice straw as potential raw material for cellulose nanofiber production. The chemical composition of the rice straw used in this study is shown in α-cellulose and pentosans) of rice straw residue is 60.7%. In general, the chemical composition is comparable to literature values, including other straw residues [These residues can be considered an interesting resource of cellulose fibers complementary to the other types of sources, mainly wood. The use of industrial residues or low-value byproducts as raw materials for the production of materials with high value, such as cellulose nanofibers, has been described in the literature by other authors ,26,27. Iresidues ,5,27, wiresidues . Given tresidues . In the Cellulose fibers and nanofibers from wood are often used in comparison with the behavior of other natural fibers . For theDifferent oxidation degrees were used on the preparation of cellulose nanofibers from rice straw. −1 wavelength, associated to carbonyl groups. From the magnification of the ATR-FTIR spectra between 1680 and 1800 cm−1, rice fibers did not present any absorption band, while a peak appears after the oxidation reaction, more intense for higher extension reaction. In all the cases, the rest of the bands correspond to characteristic cellulose absorption peaks, as follows: –OH broad band between 3600 and 3200 cm−1 as well as the peaks at 1335 and 1205 cm−1; C–O–C bond at 1160 cm−1; CH2 stretching and bending vibrations at 2918, 3851, 1427 and 1315 cm−1; and finally bending vibration for CH at 1360 and 1280 cm−1.FTIR is a rapid and nondestructive technique for the qualitative and quantitative determination of biomass components . MoreoveThe extent of the oxidation reaction impacted on the number of carboxylic groups on the cellulose surface . In the The combination of rice cellulose nanofibers with poly (PVA) allows PVA–rice nanocomposites to be obtained. Since both components are either water-soluble (polymer) or water-dispersible (rice nanofibers), casting in water was the chosen methodology to ensure proper distribution and dispersion of the reinforcing nanofibers into the polymer matrix and to avoid nanofiber aggregation. One important advantage of using PVA is the polar affinity of the polymer chains with cellulose fibers and nanofibers. It is therefore used as model system in order to analyze the reinforcing effect without side effects due to interface compatibility. Moreover, water-based procedures will avoid nanofiber aggregation during nanocomposite formation, which is one of the main issues in this field. In order to be able to compare the performance of rice nanofibers with others commonly used, PVA nanocomposites reinforced with cellulose nanofibers from eucalyptus (hardwood) were also analyzed.The thermal characteristics as well as the crystallinity level of the polymer in nanocomposites are summarized in Glass transition temperature was determined from the second heating process applied to the samples. In the first heating process, the peak collided with the presence of water in the sample. Water integration gave 1.48% of water in the PVA sample, and between 0.31 and 0.35% of water in the biocomposites. Only the dry weight of the samples was used in further DSC calculations. In all cases, the addition of either nanofiber into the matrix moved the glass transition towards slightly higher temperature values. The same occurred with maximum melting temperature: biocomposites showed higher melting temperature than unreinforced matrix. This was more evident from the second heating step. In regard to the degree of crystallinity, the nanofibers did not act as nucleating agent, at least from the sample preparation  matrix by casting. For comparison, eucalyptus nanofibers were also used to produce nanocomposites. The reinforcing capacity of rice nanofibers was proved, increasing by 3.5 times the Young’s modulus of the polymer. Similar stiffening was found for eucalyptus nanofibers. Instead, eucalyptus nanofibers were more favorable in strengthening, with ultimate tensile strengths 2.3 times higher than that from rice nanofibers, with ultimate strength 1.8 times that of the matrix, all values for 5 wt.% nanofiber content. The different morphology of both nanofibers behaved differently with polymer deformation or polymer crystallinity. Higher flexibility for eucalyptus nanofibers resulted in higher biocomposite deformation, but less ability to act as nucleating agent for crystal growing. Conversely, rice nanofibers acted distinctly as a nucleating agent for polymer crystal growing. Similarly, at DMA tests, rice nanofibers were more favorable to keep the storage modulus at a rubbery state, and clearly increased the Tg much more, as determined from the loss modulus peak.All theses findings should encourage the use of agricultural residues as biomass for added-value materials and help in recommending better solutions for crop waste.