The spliceosome is a eukaryote-specific complex that is essential for the removal of introns from pre-mRNA. It consists of five small nuclear RNAs (snRNAs) and over a hundred proteins, making it one of the most complex molecular machineries. Most of this complexity has emerged during eukaryogenesis, a period that is characterised by a drastic increase in cellular and genomic complexity. Although not fully resolved, recent findings have started to shed some light on how and why the spliceosome originated.In this paper we review how the spliceosome has evolved and discuss its origin and subsequent evolution in light of different general hypotheses on the evolution of complexity. Comparative analyses have established that the catalytic core of this ribonucleoprotein (RNP) complex, as well as the spliceosomal introns, evolved from self-splicing group II introns. Most snRNAs evolved from intron fragments and the essential Prp8 protein originated from the protein that is encoded by group II introns. Proteins that functioned in other RNA processes were added to this core and extensive duplications of these proteins substantially increased the complexity of the spliceosome prior to the eukaryotic diversification. The splicing machinery became even more complex in animals and plants, yet was simplified in eukaryotes with streamlined genomes. Apparently, the spliceosome did not evolve its complexity gradually, but in rapid bursts, followed by stagnation or even simplification. We argue that although both adaptive and neutral evolution have been involved in the evolution of the spliceosome, especially the latter was responsible for the emergence of an enormously complex eukaryotic splicing machinery from simple self-splicing sequences.This article was reviewed by W. Ford Doolittle, Eugene V. Koonin and Vivek Anantharaman. Eukaryotic genes are in general composed of coding sequences interspersed by non-coding parts, the introns. Only after removal of these introns and splicing of the exons, a functional protein can be synthesised. The splicing reaction requires one of the most complex machines in the eukaryotic cell, the spliceosome, which consists of five snRNA molecules and over a hundred proteins , 2. Two The spliceosome is one of the numerous complex characteristics that emerged during eukaryogenesis. Eukaryotes are considered far more complex than prokaryotes, because of these evolved characteristics such as their larger genomes, cell sizes and intracellular compartmentalisation. However, some complex eukaryote-like features, such as large cells and internal membranes, have been observed in certain prokaryotes and some eukaryotes are less complex in organisation, cautioning for a too eukaryocentric view on complexity . It has The greater complexity of eukaryotes is additionally observed in the complexity of molecular machines, both for machines that are also present in prokaryotes  –11 and eMany steps were needed for the emergence of the complex spliceosome in the last eukaryotic common ancestor (LECA). The aim of this review is to reconstruct these steps and the subsequent changes in the complexity of the spliceosome in the distinct eukaryotic lineages, which is important for understanding why and how the complexity of this machine has evolved. This could additionally provide more insight into the evolution of other complex molecular machines. In this review we will focus on the snRNAs and main proteins of the major spliceosome.To separate the evolution of the spliceosome during eukaryogenesis from its evolution after the eukaryotic diversification, the spliceosome of LECA has to be reconstructed. The presence of spliceosomal components in all major eukaryotic lineages has revealed that LECA already had a complex major spliceosome, with five snRNAs and around eighty proteins . TherefoIt has become clear that this complex spliceosome had to remove numerous introns from LECA’s transcripts. Multiple approaches have been followed for reconstructing the introns in LECA . ThThe probable function of LECA’s spliceosomes can be inferred from experimental research on present-day spliceosomes, most of which has been performed in yeast, animals and plants. The main components of LECA’s major U2-type) spliceosome were the five small nuclear ribonucleoproteins (snRNPs), consisting of snRNAs and dozens of other associated proteins   proteins and heterogeneous nuclear RNPs (hnRNPs), present across eukaryotes , were inAlthough some earlier studies suggested otherwise , 27, addtrans-splicing, in which the SL RNA, which is carried by the SL snRNP, donates the first “exon” to the mRNA. This splicing mechanism is especially prevalent in some protist lineages, where it in some cases may account for all splicing events [trans-splicing can therefore not unambiguously be established.Most snRNPs of the major spliceosome are also involved in another related splicing reaction called spliced-leader (SL) g events . Based og events . Howeverg events  or recurg events –37. WhetLECA likely already possessed two spliceosome types to process two different kinds of introns. These spliceosomes were approximately as complex as the ones typically observed in present-day eukaryotes. This poses the question how the complex spliceosome evolved during eukaryogenesis. Where did the proteins come from, how were they recruited into the spliceosome and what functions did their prokaryotic homologues, if present, execute?The function of the spliceosome is removing introns from pre-mRNA molecules. The question how the spliceosome originated cannot be decoupled from the origin of the introns they remove. Without introns the spliceosome would be functionless and without the spliceosome the introns would cause the production of aberrant proteins. Different hypotheses have been proposed for the origin of spliceosomal introns. These will shortly be discussed before we turn to the origin of the spliceosome. Both the spliceosomal core and the introns themselves are likely derived from the very same origin, namely self-splicing introns.The similarities between spliceosomal introns and group II self-splicing introns have been recognised for a long time. The latter are present in prokaryotes and in eukaryotic organelles. In mitochondria and plastids these introns are bona fide introns that lost their mobility potential, whereas in prokaryotes they are more properly regarded as retroelements , 39. GroThere is an overwhelming amount of evidence supporting the homology between spliceosomal introns and group II self-splicing introns. The splice site recognition, branching mechanism, stereochemical course of the splicing reaction and the presence of similar RNA domain structures and a homologue of the IEP in the spliceosome (see below) demonstrate the similarities between the two intron types , 50, 51.Since group II introns are especially abundant in alphaproteobacteria and present in certain mitochondria, the most accepted view, first suggested by Cavalier-Smith in 1991 , is thatAs demonstrated by relatively recent intron gains, not all spliceosomal introns in present-day eukaryotes are derived from group II introns. These introns have an endogenous origin and different sources have been suggested, such as transposable elements, internal gene duplications and intronisation of translatable sequences . AlthougLactococcus lactis demonstrated the potential for trans-splicing [Numerous studies have noted the striking similarities in function and structure between the snRNAs and the group II intron domains and especially U6 snRNA and domain V look very similar Fig.  39, 40,,40, 51. splicing . These oAs mentioned above a group II intron usually encodes an IEP. A homologous protein of IEP functions in the spliceosome, namely pre-mRNA processing protein 8 (Prp8), which is present in the U5 snRNP. Prp8 is present in the spliceosomal catalytic core and likely functions as an assembly platform , 69, 70.Group II introns can be classified based on RNA structures or phylogenetic groupings of IEP , 79–81. Each snRNA in the spliceosome is accompanied by a heteroheptameric ring consisting of either Sm or Lsm proteins, which are both members of the Sm family of proteins. For U6 snRNA it is an Lsm ring made up of Lsm2–8, whereas the ring surrounding the other snRNAs consists of SmB, −D3, −G, −E, −F, −D2 and –D1 , 82–85. Homologues of Sm and Lsm proteins are present in both bacteria and archaea. The bacterial homologue, Hfq, is encoded by a single-copy gene . Hfq proAlthough an earlier study was unable to confidently infer the deep phylogenetic relationship between the eukaryotic Sm and Lsm genes , a more Presumably, it started with a homoheptameric flexible Lsm-like ring Fig. . A firstThe ATP-dependent RNA helicases in the spliceosome are mainly from three families within the SFII superfamily, which is especially predominant in eukaryotes . One of Another protein in U5 snRNP is the aforementioned GTPase Snu114, which interacts with Brr2 and Prp8 and is located near the catalytic site. Snu114 was already present in LECA  and is hThe SR splicing regulator proteins are characterised by an RNA recognition motif, which is also present in multiple prokaryotes, especially cyanobacteria . A phyloThe evolutionary history of many other spliceosomal proteins has been clarified to a lesser extent. The exact source of each component, i.e. whether it was present in the archaeal host, the bacterial endosymbiont, was acquired later via HGT or was a unique eukaryotic invention, is obscure as well. The aforementioned examples demonstrate that duplicates of proteins active in other RNA processes in the first stages of eukaryogenesis supplemented the group II intron core in the emerging spliceosome. Subsequent expansions of these protein families resulting in many paralogues within the spliceosome contributed to the vast complexity of the machine Fig. .Fig. 3EvSeveral papers put forward a speculative order of events that led to the emergence of the spliceosome. The starting point for these scenarios is the presence of self-splicing group II introns, including their maturases, in the host genome. For example, Anantharaman et al.  proposed2+ concentration in eukaryotes may have posed a barrier to group II introns in eukaryotic genomes, including protein-coding genes [The timing of the decay of self-splicing introns to spliceosomal ones, on the other hand, differs in these scenarios. Since group II introns have not been detected in nuclear genomes, all introns were apparently converted to spliceosomal introns or completely lost at some point before LECA. Complications with the expression of the targeted gene that arise when a group II intron is integrated in a nuclear gene were suggested to have caused their disappearance , 98. Howng genes , it doesng genes , 98. TheEvidently, much research has focused on the many steps leading to the complex nature of the spliceosome in LECA. Nevertheless, the lack of access to intermediate stages poses a challenge to precisely reconstruct the evolution of the spliceosome. The wide diversity of eukaryotic spliceosomes provides a rich source of complementary data that show both further complexification as well as simplification of the spliceosome Fig. . The occIn at least two lineages the spliceosome has become more complex. The most prominent complexification is the expansion of splicing regulator proteins, which are involved in the recognition of exons and introns, in plants and animals. The SR family has expanded in multicellular eukaryotes, especially in plants , 101. AnAlthough the high number of alternative splicing events in animals relative to other eukaryotes could be related to the expansion of the splicing regulator repertoire in these organisms , this isIn many other eukaryotic lineages the evolution of the spliceosome is characterised by simplification. Both the loss of some subunits and the complete loss of the spliceosome have occurred. Based on draft genomes, introns and spliceosomal genes seem to be completely absent in a few microsporidia species , 106 andCaenorhabditis elegans [In contrast with the aforementioned loss of both the major and minor spliceosome and corresponding introns, the loss of only the latter has been more common. The minor spliceosome is present in representatives of all eukaryotic supergroups, but has at least 9 times been lost during eukaryotic evolution , 30. Thi elegans . Losses  elegans .Saccharomyces cerevisiae [Giardia lamblia have characteristics of both major and minor spliceosomal snRNAs and therefore the reduced spliceosome of this organism is suggested to be a hybrid [Cyanidioschyzon merolae [C. merolae seems to perform splicing without a U1 snRNP, as both U1 snRNA and U1 snRNP-specific proteins appear to be missing [In addition to the complete loss of either the minor spliceosome or both types of spliceosomes, reduced spliceosomes have been observed and more thoroughly analysed in at least three lineages. This loss of spliceosomal subunits is associated with a lower number of introns –112. Numrevisiae , 102. Evrevisiae , 90. Thea hybrid , 113. Maa hybrid . A similNumerous scenarios for the evolution of the spliceosome have been suggested. Usually this concerns a description of what happened, but to truly comprehend the evolution of the spliceosome a transition has to be made from a mere description to addressing the evolutionary forces that shaped this complex machine. A number of hypotheses concerning these forces have been proposed, as mentioned in the introduction. They propose that either the addition or loss of each component of a complex is an adaptation or that solely neutral processes are responsible for the shifts in complexity.Since the establishment of the power of natural selection, adaptive explanations for biological observations have been the most prominent and widely accepted. Many biological papers propose an adaptive explanation for their observations, albeit often implicitly. Such explanations can in many cases be criticised as being just-so stories that lack proper evidence . The rolIn the constructive neutral evolution model the increase in complexity can be seen as a ‘drunkard’s walk’ into the more complex possibilities of a system . The con+-ATPase ring and suggested that this could have been the case in other multi-paralogue complexes as well. As the spliceosome comprises multiple paralogues, such as the Sm proteins and helicases [A well-established example of a similar neutral process resulting in increased complexity is subfunctionalisation of paralogues after gene duplication. A combination of constructive neutral evolution and subfunctionalisation may explain the formation of a heteromeric protein complex from a homomeric state. Finnigan et al.  demonstrelicases , 90, 93,It should be noted that it is difficult to classify an increase in complexity as neutral. As pointed out by Lynch , each emtrans-acting RNAs. These primordial snRNAs and an IEP that acts as a general maturase, which does not only assist splicing of its own intron, would have made the RNA domains of the introns and a dedicated IEP redundant. In this way previously deleterious mutations in the introns are now presuppressed by the action of this trans-acting RNP complex, resulting in the loss of self-splicing features. This primordial spliceosome would also allow the spread of inactive group II introns and intronised sequences unrelated to group II introns in the genome. The already established nucleus would have prevented aberrant protein synthesis upon invasion of the introns into protein-coding genes. The emergence of introns in genes would have made the eukaryotic lineage dependent on the spliceosome.In a neutral scenario the spliceosome would have evolved from the addition of new RNAs and proteins that do not improve the efficacy of the splicing reaction to the catalytic core inherited from the group II intron ancestor. Moreover, at some point the structural RNA elements in the group II introns were replaced by fragments of other group II introns that acted as Numerous proteins were added to the spliceosomal core during eukaryogenesis. Many of these are clearly derived from proteins that already had an RNA-binding function , 86, 93.Giardia has resulted in a significant loss of introns and spliceosomal components [The lack of clear direct benefits of a complex splicing machinery in the early eukaryotes is a strong argument against an adaptive scenario for its evolution. The only plausible direct benefits are compensations for maladaptive features. In light of the small effective population size inferred to have been present during eukaryogenesis based on the fixation of introns , 38 or pmponents , 113. ClThe scenario we infer corresponds to a biphasic pattern of evolution, in which a short explosive innovation phase is followed by a much longer reductive phase , 21. MosThe spliceosome is a complex molecular machine that arose during eukaryogenesis and removes introns from pre-mRNAs, which is required to prevent the production of aberrant proteins. The spliceosome consists of five snRNPs, each comprised of an snRNA and proteins, and additional proteins. There is ample evidence that both the spliceosomal core and the spliceosomal introns originated from self-splicing group II introns, which are widely believed to have been transferred from the mitochondrial endosymbionts to the host DNA. The snRNAs, at least U2, U5 and U6, are likely derived from fragmented group II introns and the U5-snRNP-specific protein Prp8 evolved from the IEP of these introns. Sm proteins, helicases and other proteins were at some point recruited to the spliceosomal core. This addition and the extensive expansion of especially Sm proteins and helicases have drastically increased the complexity of the spliceosome during eukaryogenesis. Apparently, all group II introns in the nucleus were either lost or converted to spliceosomal introns before LECA. During eukaryotic evolution a pronounced increase in spliceosomal complexity occurred in plants and animals, which mainly involved the regulatory proteins. In other lineages the spliceosome simplified, with U2 and U5 snRNP proteins being the least affected, and concomitantly the number of introns decreased.trans-splicing complexes from self-splicing group II introns, as they are less complex and have evolved more recently. Splicing facilitated by general maturases and other protein factors in plant organelles [trans-acting RNA and protein factors in the plastids of the green alga Chlamydomonas reinhardtii [Euglena [The spliceosome-like machineries involved in group II intron splicing in some eukaryotic plastids and mitochondria could be an interesting model for the evolution of ganelles  and by anhardtii , and sug[Euglena  are inteThe spliceosome is one of the most complex machines that emerged during eukaryogenesis. Other complex features that originated in the eukaryotic lineage are for example the nuclear pore complex, an elaborate endomembrane system, the RNA interference machinery and the kinetochore –126, to Reviewer comments:There is much detailed information here about the evolutionary history and likely prokaryotic origins of many components of the eukaryotic spliceosome. I assume that it is up-to-date and correct. We seem now to know quite a bit about this, and have little doubt that the last eukaryotic common ancestor (LECA) already had a modern-type splicing apparatus and many introns requiring its services . Nobody now seems to question the notion first mooted by Cavalier-Smith , that introns entered eukaryotic nuclear genomes as transfers of group II introns from the alpha-proteobacterial endosymbionts that became mitochondria, and, as RNAs, broke down into something like the “five easy pieces” described by Sharp (authors’ reference 66). My “introns early” hypothesis , appealing as it might have appeared in the late 1970s, is dead and buried.We thank the reviewer for the references he put forward on the historical embedding of this topic and we have added these, if not present yet, in the main manuscript. Although the alphaproteobacterial ancestry (viathe endosymbiont) of the spliceosomal introns is widely believed, we would like to caution that is based on circumstantial evidence. Alternative scenarios in which group II introns were already present in the Asgard-related host before the endosymbiosis event or were transferred from another donor after this event are also plausible. The inferred HGT events of organellar group II introns among organelles, between different eukaryotic groups and between bacteria and eukaryotes [weaken the link between mitochondrial group II introns and spliceosomal introns, as their presence in LECA’s mitochondria is not evident. This does not preclude the proposed effect of the mitochondrial endosymbionts on the available amount of energy and effective population size, which may have resulted in massive intron proliferation and the origin of the complex spliceosome.Authors’ response: karyotes , 79 weakBut there are many questions still to be answered, I think. For instance, why, if invasion of the nuclear genome by Group II introns from mitochondria happened before LECA, and eukaryotic nuclear genomes provide a wealth of targets (non-protein coding regions) where it could happen again, has it not? Inferred genetic and physiological barriers seem  too weak to explain total absence.This is indeed an important remaining question and we have included some additional sentences on this aspect in the manuscript. We agree that the proposed gene expression problems and lower Mg2+concentration do not provide a satisfying explanation for the exclusion of group II introns from the nuclear genome. Additional experiments, also in other eukaryotes, and a closer inspection of relatively recent transfers of group II introns to the nuclear genome, such as described in [, might elucidate this enigma in the future.Authors’ response: ribed in , might eAnother question worth pondering: it is relatively easy to imagine how selective and neutral processes could have given rise to the remarkable complexity of the spliceosome. Indeed, I particularly like how this paper gives credence to the latter, especially what has been called “Constructive Neutral Evolution” (authors’ references 9 and 15). Much harder to imagine is how a complex spliceosome, once it has become essential to the expression of most of the genes in a genome, could ever be simplified. And yet it has been, several times. This may be no more amazing than other instances in which what seem to be wired-in fundamental processes and structures can be completely dispensed with or radically transformed. Selection might be not nearly so important as we Darwinists want to believe, either in the building or the dismantling of complexity (author’s reference 18).Finally, and to me most interestingly, how can we combine multi-level selection theory with reasoning about introns as adaptations ? It may well be that multicellular eukaryotes of a certain type  have gained considerable evolvability (and consequent diversity) from having alternatively spliceable introns. But clearly, introns were not added to the genome of LECA so that more than a billion years later this advantage could be realized. Authors are  down on such teleological rationalizing, but might we imagine such evolvability to be an adaptation at some much higher level ?We did not mean to neglect or downplay the importance of multi-level selection and evolvability in the evolution of the complex nature of the spliceosome and introns. We have added a short discussion of this aspect at the end of “An interplay between neutral and adaptive evolution explains spliceosomal evolution” when we discuss the biphasic model.Authors’ response: Reviewer comments:In this review article, Vosseberg and Snel discuss the origin of the spliceosome that was initiated by the domestication of bacterial self-splicing introns. It is a subject of obvious importance and interest, and a long-standing, hard problem in evolutionary biology. The difficulty of the problem stems from the appearance of “irreducible” complexity: the most primitive eukaryotes we are aware of already have a (more or less) full-fledged spliceosome, with the implication that such was also the case for the LECA. Actually, as the authors emphasize, LECA most likely possessed both known types of spliceosomes, U12 and U2. The spliceosome is one of the best showcases for the evolution of eukaryotic cellular complexity because there can be no direct ancestors of the spliceosome in prokaryotes given the non-existence of splicing other than that of self-splicing introns. And, indeed, the authors summarize the relevant information and make a compelling case for the origin of both the spliceosome and the spliceosomal introns themselves from Group II self-splicing introns. In the discussion of the subsequent evolution of the splicesomes, the authors make a good case for a constructive neutral evolution scenario. I fully agree that, in the least, constructive neutral evolution is the appropriate null hypothesis for the evolution of the spliceosome and other complex eukaryotic features. The authors make a very interesting point about the relatively simple, spliceosome-like complexes that are involved in splicing of Group II introns in organelles. These are not ancestral but their evolution might recapitulate that of the spliceosome, so analysis of such complexes indeed might illuminate spliceosome evolution. On the whole, this is a very useful, interesting and insightful review, and a good read, too.We thank the reviewer for his excellent summary and appreciate the constructive feedback he has provided in his report.Authors’ response: I do not have particularly serious criticisms of this article. I find the discussion of the potential of phylogenetic analysis of the IEP and Prp8 (lines 230–237) to be rather disingenuous. I agree with the authors that such analysis is unlikely to be particularly informative. However, it seems to me that one should either try and actually do it or drop this line of discussion altogether.We apologize that our initial wording could be seen as disingenuous and we have decided to remove it.Authors’ response: In the discussion of the evolution of Lsm/Sm proteins, the following “A small number of introns are even shared between certain Lsm-Sm pairs. This is not trivial, as it implies that splicing could already take place before the diversification of the Sm family in eukaryotes” (lines 272–274) is indeed a non-trivial observation, and I think additional details are needed for the reader to be able to assess its validity and impact.We have added more details on these findings and discussed these in light of the low number of shared introns for paralogues originating from duplications during eukaryogenesis and the high number of shared introns for orthologues present in LECA. Upon mapping the location of introns onto the alignments of Lsm/Sm proteins in 22 eukaryotic species, Veretnik et al. [made the striking observation that for some pairs, and also between certain pairs, at the same position in the alignment an intron was located in multiple species for each paralogue, suggesting that this intron was already present before the duplication event. These findings have two major implications: 1) before the diversification of these proteins, which are essential for present-day splicing, splicing already took place; 2) these gene duplications likely did not occur early during eukaryogenesis.Authors’ response: k et al.  made theFor a review article, the current manuscript seems to be somewhat insufficiently referenced. In many case, the authors rely on previous reviews where several original references would do better. I will not suggest a full list of references to add and will only mention two: Along with ref. 96, the following should be cited: López-García P, Moreira D. Selective forces for the origin of the eukaryotic nucleus. Bioessays. 2006 May;28(5):525–33. The absence of this reference which presents a comprehensive reconstruction of intron gain and loss in eukaryotic evolution is surprising: Csuros M, Rogozin IB, Koonin EV. A detailed history of intron-rich eukaryotic ancestors inferred from a global survey of 100 complete genomes. PLoS Comput Biol. 2011 Sep;7(9):e1002150.Upon a critical reassessment of the references we have added 28 references to primary papers throughout the paper and we believe that the references are now more balanced. Initially, we did not include a discussion on the number of introns in LECA, but we agree that this was an omission and therefore added a small paragraph about this in the section "LECA’s spliceosome", including the latter reference. We did not discuss ref.96in light of the hypothesis on the origin of the nucleus, but for the scenario they propose for the origin of the spliceosome. In the revised version of this review we shortly mention the origin of the nucleus in the “Adaptive model” section, referring to both papers.Authors’ response: Further, in my view, there are too few figures in the article, and those included are too crude schematics. It would be good to show a better comparison between elements of self-splicing introns and snRNAs, and perhaps, a complete general scenario for the evolution of the spliceosome.Figure was drawn as a schematic figure on purpose, to immediately appreciate the similarities between group II and spliceosomal introns. Excellent figures with more details have been made before . We have added more details in Fig. by depicting also the RNA structures that are not similar and indicating that not the entire proteins are homologous. As suggested by the reviewer, we have also made a new figure  depicting the general scenario we propose with regards to spliceosome evolution pre- and post-LECA.Authors’ response: ig. 5 in ). We havReviewer comments:The authors have written a review of the evolution of the complexity of the spiceosomal machinery. They have touched on the various components of the spliceosome and their evolution. While there are many detailed discussions of this material available, this is a useful update summarizing the various ideas. Hence I find the review satisfactory and worthy of being published as is.The authors have presented a review of the prevalent ideas in the subject satisfactorily. I do not have any major recommendations.In pg 9–10 the authors discuss the loss of RT activity in Prp8 and point to a 2015 article. The inactive Prp8 and its possible link to Group II intron and spliceosomal evolution has been discussed in a much earlier 2012 paper (pmid: 22919680) by our group.The reference to the 2015 paper was actually for the last part of this sentence. We have added references to the suggested paper and another paper when discussing the loss of RT activity.Authors’ response:


We experimentally observed an asymmetric field screening effect relative to the polarization of the applied gate bias into the surface. Surprisingly, such behavior allows selection of the electronic states that screen external fields, and it can be enhanced with increasing of the number of layers of the semiconducting MoS2 rather than the semi-metal. This work not only provides unique insights on the screening properties of a vast amount of heterojunction fabricated so far, but also uncovers the great potential of controlling a fundamental property for device applications.A long-standing challenge facing the combination of two-dimensional crystals into heterojunction is the unknown effect of mixing layer of different electronic properties  on the screening features of the fabricated device platforms including their functionality. Here we use a compelling set of theoretical and experimental techniques to elucidate the intrinsic dielectric screening properties of heterostructures formed by MoS 2/graphene van der Waals heterostructures and identify an asymmetric electric response under different directions of the applied electric field.Charge density reorganization at the interface between 2D materials may lead to electric field screening. Here, the authors investigate the dielectric screening properties of MoS With the properties of the individual layers being characterized since the discovery of graphene and other 2D materials7, the great challenge is how to combine them in order to obtain unusual physical and chemical phenomena not observed on the original sheets1. The continuous development of experimental methods that allow atomically thin materials to be fabricated on-demand and to be placed on desired locations with an unprecedented control and accuracy have opened pioneering avenues to fabricate complex device architectures using regular bottom-up approaches4. The atomic flatness and lack of dangling bonds at the surface of 2D layered materials, such as graphene, boron nitride (BN) and transition metal dichalcogenides (TMDCs), allow them to form non-covalent interactions with a wide range of materials without the condition of lattice matching that normally heterojunctions would have. One of the first realizations of such vdWHs was the fabrication of BN/graphene interfaces and the probing of their electronic properties using gate bias8. Such system remarkably showed that graphene could develop superior electrical properties, achieving levels of performance comparable to those observed with freestanding layers. In this assembly, BN layers work as an underlying substrate screening out graphene from any dangling bonds, corrugations and charge inhomogeneities that are inherent to standards SiO2 surfaces to play a role on its electronic properties9. A direct extension of this system was the complete encapsulation of graphene, TMDCs and the combination of them between BN layers11. This rapidly showed that such device framework displayed improved transport properties with high-mobilities10. It is important to remark that in all these systems electrostatic gating schemes have been one of the main driving force to probe the chemical and physical properties of either isolated 2D materials before assembling, or their vdWHs afterwards. Electric gate bias measurements have become a feasible way to control, induce and manipulate electronic properties of almost any vdW crystals since graphene early days14. This relatively simple setup allows deep insight into the charge density reorganization between different stacking sequences, and on the electric-field screening, which determines most of the exquisite device properties observed in vdWHs. However, no direct measurements of the electrostatic screening features of different combinations of 2D materials have been reported yet, which ramp up further understanding and developments of vdWHs into any technological platform.The van der Waals heterostructures (vdWHs) composed of two-dimensional (2D) crystals and precisely assembled in a deterministic order constitutes a remarkable paradigm for promising electronic and optoelectronic applications with enhanced features and performance2, displays an asymmetrical behavior relative to the polarization of the applied gate bias into the surface allowing an asymmetric screening. Using electric force microscopy (EFM), we observe that graphene/MoS2 heterostructures exhibit distinct electric response to external fields with respect to the stacking sequence and the direction of electric field. A large depolarization field is recorded at the MoS2 side, which is shown to be dependent majority on the number of MoS2 layers into the heterostructure. A multiscale theoretical framework is developed for elucidating such stacking-dependent asymmetric electric screening phenomenon in graphene/MoS2 vdWHs. At the atomistic level, we employed quantum mechanical ab initio simulations based on density functional theory (DFT) using a total energy vdW functional to resolve various electronic properties of the vdWHs, including polarization, charge transfer and band structures. Our results indicate that the asymmetric formation of interfacial dipole moments preferably at the MoS2 facet accounts for the asymmetric response. We further show that such asymmetric behavior can be explained using a classical quantum capacitor model, described by a set of self-consistent electrostatic conservation equations and treating the 2D layers according to their individual electronic genomes . Our theoretical framework has good consistency with the experimental results at both ab initio and classical levels, showing that the combinations of 2D materials with distinct electronic structures can result in vdWHs with rich screening features. Furthermore, our theoretical framework is readily applicable for other vdWHs beyond graphene/MoS2 to explore a wide range of 2D material combinations with programmable electronic screening properties, which may greatly benefit the design of 2D vdWH-based functional devices.Here we show that the dielectric properties of an archetypal vdWH, involving graphene and MoS2 of different thicknesses on Au coated Si wafer were achieved by two rounds of polymethyl-methacrylate (PMMA) transfer15. Figure 2 (90 nm)/Si substrate. Their thickness was confirmed by the Raman spectra (514.5 nm wavelength) as shown in Fig. 16. The absence of Raman D band suggests the high quality of the graphene. Atomically thin MoS2 nanosheets were exfoliated on a SiO2 (270 nm)/Si substrate , which can be described as22:∂F/∂z is the local force gradient, representing the derivative of the electrostatic force felt by the cantilever tip; k is the spring constant of the cantilever; and Qcant is the Q factor of the cantilever. For simplicity, the interaction between the cantilever tip and the sample in EFM is often viewed as an ideal capacitance  due to the mismatch of the work functions between the tip and the sample. The raw data of the EFM spectroscopy from the Au substrate, 4L graphene, bulk MoS2, and three heterostructures, namely 1L MoS2/1L Graphene, 2L MoS2/4L Graphene, and 3L MoS2/4L Graphene are shown in Fig. y-axis as a function of the DC voltage. Considering the quadratic function in Eq. VCPD was fixed for each sample, the formation of the parabolic curves was due to the sweeping V. In other words, V was a dominant parameter in our EFM measurements. The opening-up means attractive capacitive interactions under both positive and negative voltages21. However, the different samples gave rise to slightly different shapes of the parabolas. This was caused by the other parameters, especially C and z. The distance z was inevitably slightly different from sample to sample during the EFM spectroscopy measurements. Although the local capacitance C is very difficult to define, as it depends on many factors, including the shape, size, conductivity, and dielectric property of a sample and cantilever, C was different from sample to sample. Therefore, it is understandable that the different samples resulted in the slightly different parabolic shapes in EFM spectroscopy.We used EFM to measure the electric field screening properties of the MoSres Fig. . Subtle 2/4L Graphene  of the 3L MoS2/4L Graphene heterostructure ; and a classical electrostatic approach using a capacitance model based on charge conservation equation solved variationally (see Methods for details). We first address the quantum mechanical part of the MoS2, respectively, but with a distinct number of graphene layers. Strikingly, only negative bias affected 2 sheets present in the heterostructures. This is in remarkable agreement with the experimental results, where an asymmetrical response was recorded only from graphene and few-layer MoS2 heterostructures , 2L (0.03) and 3L (0.05)), which indicates that thicker MoS2 tends to be more correlated with variations in the number of graphene layers. This follows the behavior observed from EFM measurements, which heterostructures involving thicker MoS2 sheets in contact with graphene gave rise to a more asymmetric EFM phase parabola . For negative fields towards MoS2 layers, the second term on the right-hand side in Eq. Eρ that would overcome the applied external bias. This resulted in smaller electric fields inside the heterojunction  tend to tune their Fermi level almost linearly with the electric field, which is a property intrinsically present at the pristine layers28. As the number of MoS2 sheets increased, ΔEFermi displayed variations at positive fields as large as 0.34 eV for 3L MoS2/3L Graphene but almost negligible for the negative electric field with the formation of a plateau at −0.2 V nm−1 and beyond. Such asymmetric behavior has been observed when MoS2 layers are used in metal-insulator-semiconductor junctions29. Carrier doping induced by the electric field was responsible for the variation of the Fermi level or the work function of MoS2, mainly along one direction, which is directly related to the unbalance of charge density between both sides of the semi-metal and the semiconductor interface. This indicates that the intrinsic character of the electronic structure of each system in vdW heterostructures contributes to the formation of the asymmetric screening observed. This effect has several main implications on the fundamental electronic structure of the MoS2/Graphene interfaces as can be appreciated on the band structure calculated at different magnitudes of gate bias for a sample system (e.g. 3 L MoS2/1L Graphene) in Fig. 2. At 0.0 V nm−1, the Fermi level crossed the Dirac point of graphene, as no charge-imbalance was present between both systems. Several MoS2 states at the conduction band were observed at 247.86 meV relative to the Fermi level, which also corresponds to the Schottky barrier presents at the interface30. At finite fields, those states are observed to shift up (down) with positive (negative) electric bias, with a consequent split as large as ~0.20 eV. This modifies their occupation, as some graphene states can become occupied (positive bias) or unoccupied (negative bias) according to the field polarization. The insets in Fig. 2 states near the Fermi level. This indicates that for electric fields toward the dichalcogenide layer, the states mainly composed of the conduction band of MoS2 with minor contribution from graphene were responsible for the charge-screening effect and vice versa. This suggests the important role of the interface on the electrical properties of the vdW heterostructures, as the polarity of the electric field can select, which states can screen the system against external bias.On the basis of the previous analysis, several implications on the electronic structure of the heterojunction can be foreseen. Figure eet Fig. , which gace Fig. . This choS2 Fig. . Thin sy2/Graphene vdW heterostructures under an external electric field can be well described using a classical electrostatic model, taking the quantum capacitance into consideration31. As the 2D vdWHs are stacked via non-covalent interactions, it is found that the individual properties of 2D materials can still be largely preserved in their stacked layers, which are coupled by the Coulombic interactions32. The idea behind our classical electrostatic model is that each individual layer has its own electronic “genome”  extracted from ab initio calculations, which can be used as building blocks in solving the electrostatic conservation equations of the whole vdWH, under the non-coupling assumption. Figure 2/Graphene vdWH used in the classical model. Due to the fact that there is no electron drift in the vdWH at equilibrium , the Fermi level EFermi aligns throughout the MoS2/Graphene vdWH. For simplicity of the model, we further assume that (i) the density of states (DOS) of individual layer is invariable with the stacking order and the external electric field and (ii) the interlayer distances (di) are not affected by the external electric field. Note that although the transition of band structure is ignored in assumption (i), it has been shown that such classical treatment using Coulombic coupling has relatively high consistency with the ab initio simulations32. The charge and potential distribution in the vdWH is solved by several conservation equations in a self-consistent approach33: (i) the charge of individual 2D layer Qi follows the charge conservation of the vdWH, (ii) Qi is determined by the electric displacement field adjacent to the 2D layer, (iii) Qi determines the work function of layer i, ϕi and (iv) the work function difference between two adjacent layers is determined by the electric displacement field. More details about the mean-field model can be found in Methods. For the simplest case of 1L MoS2/ 1L Graphene, we plot in Fig. ϕi of both materials, as a function of the external electric field strength (Eext) ranging from −8 to +8 V nm−1. Highly n-doped and p-doped MoS2 regimes can be found when Eext <−2.3 V nm−1 or Eext > 5.5 V nm−1, respectively. The fermi level of MoS2 shifts close to its conduction band (CB) or valence band (VB) in both regimes, respectively, which is accounted for the charge accumulation in the vdWH. Note that a noticeable charge accumulation (>1012 e cm−2) occurs even when the Fermi level of MoS2 is still ca 0.1 eV away from the band edges, due to the fact that the low quantum capacitance of graphene near its intrinsic Fermi level. On the other hand, when Eext is between −2.3 and 5.5 V nm−1, the Fermi level of MoS2 lies far away from the band edges, resulting that the vdWH is merely not polarized and the work function of graphene ϕGr shows little change with Eext. We find that the polarization of the MoS2/Graphene vdWH is more enhanced under negative external electric field, which corresponds with the findings in Fig. 2: MoS2 is considered as a n-type semiconductor with its intrinsic Fermi level (−4.5 eV) closer to its CB (−4.0 eV) than its VB (−5.8 eV)36, while graphene has symmetric linear band structure around its Dirac point (−4.6 eV)37, all energy levels are compared with the vacuum level that is set at 0 eV. Due to their close Fermi level values, little charge transfer occurs between graphene and MoS2 under weak electric field, and the degree of charge transfer is mainly determined by the position of the Fermi level with respect to the CB or VB of MoS2. Following the same procedure, we calculated the dipole moment δ , a considerable amount of total dipole moment can still be observed under weak electric field (|Eext| < 0.5 V nm−1), when the charge transfer between graphene and MoS2 is negligible (<1011 e cm−2). This indicates that the electric field is well screened by multilayer graphene under such conditions, since the DOS of graphene is finite around the intrinsic Fermi level. The screening in the MoS2 becomes more important only when the Fermi level reach the band edges, that is, when the DOS increases greatly. To verify such statement, we reconstructed the band diagram of 3L MoS2 /1L Graphene system under electric fields of −2 V nm−1 , that the local capacitance of the vdWHs can be varied under different electric field , here we further propose that such asymmetry can be described by the quantum capacitance, within both theoretical frameworks. The vdWH can be considered as a capacitor, characterized by the quantum capacitance (CQ), which is a function of the DOS at the Fermi level of the whole vdWH: CQ = DOS(EFermi)e2. The total DOS of the vdWH can be obtained quantum mechanically at high accuracy. On the other hand, the apparent quantum capacitance in the classical model can be calculated by the differentiating the charge density by the potential drop across the vacuum level ΔEvac  and DFT calculations (CQDFT) as functions of Eext in various MoS2/Graphene systems in Fig. −2 in 3L MoS2 /3L Graphene configuration, under an electric field of −1 V nm−1. We find the layer dependency of quantum capacitance is very similar to that of the dipole moment and charge transfer: the layer number of MoS2 is dominating the magnitude of the total quantum capacitance under strong electric field. This is reasonable due to the higher quantum capacitance of MoS2 than graphene when Fermi level shifts to the band edges33. Note that the DFT calculations predict a non-zero quantum capacitance of vdWHs with 2L and 3L graphene even without external electric field, as a result of the interlayer coupling, which is not included in the classical model. Despite the minute difference between both theoretical frameworks, it is clear that the quantum capacitance of the MoS2/Graphene vdWH, as a combination of the energy levels and DOS, can describe the asymmetric screening behavior with good precision. Our multiscale theoretical framework is thus readily applicable for a variety of vdWHs beyond graphene/MoS2, by utilizing the electronic “genome”, in particular, the quantum capacitances of individual 2D layers. A full picture of electric screening of 2D vdWHs can be built benefited from the framework proposed in this work, extending the “tip of the iceberg” of the electrostatic nature of two-layer 2D vdWHs revealed by recent studies40.The classical electrostatic model shows sound agreement with the ab initio calculations in predicting the asymmetric screening behavior of the MoS2. Graphene/MoS2 constitutes an archetypal of vdW heterostructure with exciting possibilities for electronic devices based on atomically thin films. We have shown an asymmetric electric field response on the screening properties of MoS2/Graphene stackings via high-resolution EFM spectroscopy and a multiscale theoretical analysis that involve quantum mechanical ab initio density functional theory, including vdW dispersion forces, and a classical electrostatic approach considering the quantum capacitance. Our ab initio calculations are further unified in a quantum capacitance-based model, showing that the difference between the energy levels and band structures between graphene and MoS2 is account for the asymmetric screening behavior. After the transfer of MoS2 on graphene, the screening of either isolated graphene or MoS2 changes accordingly to the sign of the electric bias utilized becoming polarity-dependent. The EFM phase spectrum shows an asymmetry with the tip voltage, as the number of MoS2 layers increases relative to that of the graphene. Electric fields towards MoS2 tend to be better screened than those directed to graphene as an asymmetrical polarization associated with charge transfer at the MoS2/Graphene interface, generate response fields that opposed to external bias. Such charge rearrangement also polarized the interface inducing the appearance of dipole moments and consequently giving a directional character to the underlying electronic structure. In particular, external fields in such vdW heterostructures can select which electronic states can be used to screen the gate bias, which clearly give an external control on the screening properties according to the stacking order and thickness. Our computational-experimental framework paves the way to understand and engineer the electronic and dielectric properties of a broad class of 2D materials assembled in heterojunctions for different technological applications, such as optoelectronics and plasmonics.In summary, our findings reveal fundamental knowledge of the screening properties of van der Waals heterostructures using widely used two-dimensional materials, such as graphene and MoS2 nanosheets were mechanically exfoliated by Scotch tape. Highly oriented pyrolytic graphite (HOPG)  and synthetic MoS2 crystals  were used as received. Si wafers with 90 and 270 nm thick thermal SiO2 were used for graphene and MoS2, respectively. An Olympus optical microscopy (BX51) equipped with a DP71 camera was used to search atomically thin nanosheets, and a Cypher AFM  was employed for topography measurements. The Raman spectra were collected by a Renishaw Raman microscope using 514.5 nm (for MoS2) and 633 nm (for graphene) lasers and an objective lens of ×100. For the fabrication of the heterostructure, the identified MoS2 nanosheets were firstly coated by thin layer of PMMA, then peeled off from the SiO2/Si via etching by NaOH, stacked on graphene on SiO2/Si under the optical microscope. The MoS2/Graphene structure was transferred to Au (100 nm) coated SiO2/Si substrate following a similar procedure. The Au coating was produced by a Leica ACE600 sputter with a crystal balance monitoring the coating thickness in real time. The EFM measurements were conducted on the Cypher AFM. The EFM phase data were collected by a Pt/Ti-coated cantilever with a spring constant of ~2 N/m  dwelling above the heterostructure at a sampling rate of 2 kHz, while a voltage sweeping linearly from +9 to −9 V was applied on the cantilever over a period of 20 s.The graphene and MoS41 and the VASP codes43. Projected augmented wave method (PAW)45 for the latter, and norm-conserving (NC) Troullier-Martins pseudopotentials46 for the former, have been used in the description of the bonding environment for Mo, S and C. The shape of the numerical atomic orbitals (NAOs) was automatically determined by the algorithms described in ref. 41. The generalized gradient approximation47 along with the DRSLL48 functional was used in both methods, together with a double-zeta polarized basis set in Siesta, and a well-converged plane-wave cutoff of 500 eV in VASP. We have explicitly checked the effect of different modifications on the exchange part of the vdW density functional on the interlayer distance between graphene and MoS2 as shown in Supplementary Table −8 eV Å−1. The self-consistent field (SCF) convergence was also set to 1.0 × 10−8 eV. To model the system studied in the experiments, we created large supercells containing up to 394 atoms to simulate the interface between different number of graphene and MoS2 layers. We have optimized the supercell for the MoS2/Graphene interface using a 5 × 5 graphene cell on a 4 × 4 MoS2 cell, where the mismatch between different lattice constants is smaller than ~2.0% (i.e. the systems are commensurate). We have kept the lattice constant of the MoS2 at equilibrium, and stretched the one for graphene by that amount. Negligible variations of the graphene electronic properties are observed with the preservation of the Dirac cone for all systems. To avoid any interactions between supercells in the non-periodic direction, a 20 Å vacuum space was used in all calculations. In addition to this, a cutoff energy of 120 Ry was used to resolve the real-space grid used to calculate the Hartree and exchange correlation contribution to the total energy in SIESTA. The Brillouin zone was sampled with a 9 × 9 × 1 grid under the Monkhorst-Pack scheme49 to perform relaxations with and without van der Waals interactions. Energetics and electronic band structure were calculated using a converged 44 × 44 × 1 k-sampling for the unit cell of Graphene/MoS2. In addition to this we used a Fermi–Dirac distribution with an electronic temperature of kBT = 20 meV to resolve the electronic structure.Calculations were based on ab initio density functional theory using the SIESTAEext=Ez across the vdW heterostructures is simulated using a spatially periodic sawtooh-like potential 2/Graphene heterostructures. Such potential is convenient to analyze the response of finite systems  to electric fields55, while problematic for extended systems . The magnitudes of the spatially varying electrostatic potential P(r) is calculated by the integration of l the thickness of the vdW heterostructure, and c the height of the supercell24.The electric field 2 layers are treated as individual layers, with the the band structures  considered as invariable to external electric field (i.e. the effect interlayer coupling on band structure is neglected). We further consider that the interlayer distance di between the i-1 and i-th layers is fixed, and taken as the interlayer distance in DFT calculations under zero field. The interlayer dielectric constant εi between the i-1 and i-th layer is considered as uniform. For simplicity, we consider that εi is independent of the external field, while the current model can be easily adapted for field-dependent dielectric constant in multilayer 2D materials using ab initio calculation results24. We consider the interlayer electric field Ei to be uniform. The charge density Qi and work function ϕi of each layer can thus be solved through the following conservation equations in a self-consistent way:In the classical model, the graphene and MoSThe charge neutrality of the vdWH:i-th layer by Gauss law:Charge balance of the Qi as a function of the work function ϕi of i-th layer:ϕi0 is the intrinsic work function of the i-th layer.The potential drop between 2 adjacent layers:CiQ,  = DOSi·e2. We simplify the quantum capacitance of graphene using a linear model: CiGraphene, = 26.1 μF cm−2 V−1 Δϕi, while the quantum capacitance of MoS2 is a step function, where no density of states exist within the band gap, while 2 are set at 4.6 and 4.5 V, respectively. The energy levels of CB and VB of MoS2 are taken as −4.0 and −5.8 eV, respectively.Note that for individual layers, The data that support the findings of this study are available from the corresponding author upon reasonable request.Supplementary InformationPeer Review File


The BER performance as a function of the relative time offset between three signals  is also evaluated showing favorable performance.We propose graphene-assisted multiple-input high-base optical computing. We fabricate a nonlinear optical device based on a fiber pigtail cross-section coated with a single-layer graphene grown by chemical vapor deposition (CVD) method. An approach to implementing modulo 4 operations of three-input hybrid addition and subtraction of quaternary base numbers in the optical domain using multiple non-degenerate four-wave mixing (FWM) processes in graphene coated optical fiber device and  quadrature phase-shift keying ((D)QPSK) signals is presented. We demonstrate 10-Gbaud modulo 4 operations of three-input quaternary hybrid addition and subtraction  in the experiment. The measured optical signal-to-noise ratio (OSNR) penalties for modulo 4 operations of three-input quaternary hybrid addition and subtraction  are measured to be less than 7 dB at a bit-error rate (BER) of 2 × 10 Graphene possesses the properties of tunable Fermi level, saturable photon absorption, and adjustable refractive index45101112et al.(3)). It also indicates that the nonlinear response of graphene is essentially dispersionless over the wavelength. Such nonlinearity of graphene can be utilized to realize various nonlinear functional devices for telecommunications, such as optical switches, wavelength converters, and signal regenerators. Optical bistability, self-induced regenerative oscillations and four-wave mixing (FWM) have been consecutively observed in graphene-silicon hybrid optoelectronic devices182018Graphene2Recently, spectrally efficient advanced modulation formats have been widely used in optical fiber transmission systems232425262729−3.In this paper, we propose an approach to performing modulo 4 operations of three-input optical addition and subtraction of quaternary base numbers using multiple non-degenerate FWM processes based on graphene coated fiber device. By adopting (D)QPSK signals , we demonstrate 10-Gbaud modulo 4 operations of three-input hybrid addition and subtraction of quaternary base numbers . The received optical signal-to-noise ratio (OSNR) penalties for modulo 4 operations of three-input quaternary hybrid addition and subtraction are measured to be less than 7 dB at bit-error rate (BER) of 2 × 10where the subscripts A, B, C, i1, i2, i3 denote input signal A, signal B, signal C, output idler 1, idler 2 and idler 3, respectively. Considering the phase wrap characteristic with a period of 2π, the linear phase relationships in In the experiment, the wavelengths of three-input signals A, B and C are fixed at 1548.52, 1550.12 and 1552.52 nm, respectively. −3 (7% enhanced forward error correction (EFEC) threshold). The increased OSNR penalties might be mainly due to the relatively low conversion efficiency for converted idlers and accumulated distortions transferred from three-input signals . The insets in To characterize the performance of the proposed graphene-assisted modulo 4 functions of three-input high-base optical computing, we further measure the BER curves as a function of the received OSNR for back to back (B-to-B) signals and three converted idlers. For the graphene-assisted modulo 4 functions of three-input high-base optical computing, we also study the performance tolerance to the relative time offset between three input signals. −3 are measured to be less than 7 dB for three converted idlers . The BER performance as a function of the relative time offset between three signals  is also evaluated and a favorable performance tolerance is achieved. With future improvement, graphene coated fiber device might be employed to facilitate more interesting optical signal processing applications.In summary, an innovative scheme to perform graphene-assisted modulo 4 functions of three-input high-base optical computing is presented. By exploiting multiple non-degenerate FWM processes in a single-layer graphene coated fiber device and adopting (D)QPSK signals, we experimentally demonstrate 10-Gbaud modulo 4 operations of three-input quaternary hybrid addition and subtraction of A + B − C, A + C − B, and B + C − A, respectively. The received OSNR penalties at a BER of 2 × 103 = 8 possibilities of the operations of A, B and C. We only demonstrate 3 of them in the experiment, i.e. A + B − C, A + C − B and B + C − A. Actually, the left 5 possibilities of the operations could be also implemented based on the same multiple non-degenerate FWM processes in graphene coated fiber device. For instance, when using –C instead of C as the input , one can easily get A + B + C, A − C − B, B − C − A. As a consequence, when selectively using –A/–B/–C instead of A/B/C at the inputs, it is possible implement all the 8 possibilities of the operations of A, B and C based on the same multiple non-degenerate FWM processes in graphene coated fiber device, i.e. A + B + C, A + B − C, A − B + C, A − B − C, −A + B + C, −A + B − C, −A − B + C, −A − B − C. Note that the conversion from C to –C can be achieved using conjugated degenerate FWM process which was demonstrated in our previouis worksRemarkably, for three-input optical computing, there are, in principle, 2Additionally, in order to verify the the enhancement of graphene coated fiber device, we measure the output spectrum without graphene for reference under the same experimental conditions. Moreover, we repeat the experiment by adding extra 2 m and 5 m single mode fibers in the setup and get almost the same experimental results. 3 solution. The resultant PMMA/graphene film (5 mm × 5 mm) is then washed in deionized water several times and transferred to deionized water solution or Si/SiO2 substrate. Then, the floating PMMA/graphene sheet is mechanically transferred onto the fiber pigtail cross-section and dried in a cabinet. After drying at room temperature for about 24 hours, the carbon atoms could be self-assembled onto the fiber end-facet thanks to the strong viscosity of graphene. The PMMA layer is finally removed by boiling acetone. By connecting this graphene-on-fiber component with another clean and dry FC/PC fiber connector, the nonlinear optical device is thereby constructed for multiple-input high-base optical computing applications based on non-degenerate FWM processes.In order to fabricate the nonlinear optical device based on a single-layer graphene, as illustrated in 2/Si substrate. The grown graphene sheet is also transferred on silicon-on-insulter (SOI) for SEM characterization, as show in −1, respectively. The obtained I2D/IG ratio of 1.65 demonstrates the formation of monolayer graphene2/Si substrate is almost defect-freeIn the experiment, optical image is taken with an optical microscope (Olympus DX51), Raman spectroscopy is performed with a laser micro-Raman spectrometer , and scanning electron microscopy (SEM) images are obtained by Hitachi-S4800. How to cite this article: Hu, X. et al. Graphene-assisted multiple-input high-base optical computing. Sci. Rep.6, 32911; doi: 10.1038/srep32911 (2016).


Furthermore, the correlation between the SUVmax and PD-L1 expression has not been assessed. Thus, the purpose of this study was to investigate the correlation between PD-L1 expression and the SUVmax on 18FDG-PET and to examine the prognostic significance of PD-L1 expression and the SUVmax in surgical pulmonary SCC. Expression of PD-L1 was examined in 84 patients with resected SCC using immunohistochemistry. Positive PD-L1 expression in tumour cells was observed in 58.3% (49/84) of patients with SCC. High PD-L1 expression levels were significantly correlated with histological differentiation (P=0.006), and a high SUVmax was associated with histological differentiation (P=0.037), and lymph node metastasis (P=0.025). Spearman's test showed that there was a significant correlation between PD-L1 expression levels and the SUVmax. High PD-L1 expression levels and a high SUVmax were both independent risks factors for poor overall survival. Our results suggested that high PD-L1 expression levels and a high SUVmax was associated with poor prognosis in surgical pulmonary SCC. The existence of a statistically significant correlation between the SUVmax and PD-L1 expression levels justifies exploring the usefulness of the SUVmax as a predictor of PD-1/PD-L1 inhibitor activity.Programmed cell death-ligand 1 (PD-L1) expression is commonly observed in non-small cell lung cancer (NSCLC). The prognostic value of PD-L1 expression and the maximum standardized uptake value (SUVmax) on 18F-Fluorodeoxyglucose positron emission tomography ( Lung cancer, which can be broadly divided into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), is the most prevalent cancer worldwide . CertainThe programmed death 1 (PD-1) pathway is a major immune checkpoint. The binding of PD-1 ligand (PD-L1) to PD-1 induces activated T-cell apoptosis or exhaustion, and agents that block this inhibitory signal have been shown to enhance T-cells activity . Previou18FDG-PET) is an important noninvasive tool used for the diagnosing NSCLC and performing TNM staging in patients with the disease. The maximum standardized uptake value (SUVmax) on FDG-PET is widely used in clinical practice because of its simplicity [18F-Fluorodeoxyglucose positron emission tomography .The correlations between PD-L1 expression and the SUVmax and clinicopathological characteristics are presented in Table PD-L1-positive patients displayed significantly shorter DFS (P=0.007) and OS P=0.002) than PD-L1-negative patients. Furthermore, patients with a high SUVmax displayed shorter DFS (P=0.002) and OS P=0.014) than patients with a low SUVmax. for 60 minutes at room temperature. For antigen visualization, we immersed the sectionsin 3, 3-diaminobenzidine solution and counterstained them with hematoxylin.The PD-L1 immunostaining results were classified into two groups based on staining intensity and tumour cell positivity. Staining intensity was scored as follows: 0, negative staining; 1, weak staining; 2, moderate staining; and 3, strong staining. All cases in which more than 5% of tumour cells displayed a staining intensity ≥2 were considered positive. Cases with staining intensity <2 or less than 5% of tumour cells were considered negative. The 5% threshold used herein was chosen based on the results of a previous clinical trial –42.p values <0.05 were considered statistically significant. All statistical analyses were performed using SPSS software .The correlations between PD-L1 expression and clinicopathological characteristics were evaluated using chi-square tests or Fisher's exact test. Spearman’ s correlation coefficient (rho) was used for rank correlation. Disease-free survival and overall survival were calculated using by the Kaplan–Meier method, and comparisons were performed using the log-rank test. Univariate and multivariate regression was performed using the Cox proportional hazards model. Two-sided


High electron mobility is one of graphene's key properties, exploited for applications and fundamental research alike. Highest mobility values are found in heterostructures of graphene and hexagonal boron nitride, which consequently are widely used. However, surprisingly little is known about the interaction between the electronic states of these layered systems. Rather pragmatically, it is assumed that these do not couple significantly. Here we study the unoccupied band structure of graphite, boron nitride and their heterostructures using angle-resolved reflected-electron spectroscopy. We demonstrate that graphene and boron nitride bands do not interact over a wide energy range, despite their very similar dispersions. The method we use can be generally applied to study interactions in van der Waals systems, that is, artificial stacks of layered materials. With this we can quantitatively understand the ‘chemistry of layers' by which novel materials are created via electronic coupling between the layers they are composed of. Heterostructures of graphene and hexagonal boron nitride have great potential for high-mobility electronics, yet little is known about the electronic interaction between these two atomically thin materials. Here, the authors perform angle-resolved reflected-electron spectroscopy to unveil their interplay. Electronic band structure is the key to most properties of crystalline materials. Band structure measurements are therefore widely used to study the subtle interplay of electrons with lattice excitations1578101112in situ, with high lateral resolution14ab initio calculations. Finally, we turn to stacks of few-layer graphene on hBN to study their electronic coupling over an energy range of ∼25 eV. All samples are produced on a conductive silicon substrate using a polymer-free assembly techniqueHere we scrutinize the band structure of graphene–hBN heterostructures over a wide energy range to shed light on the interactions in this most widely used vdW system. We apply a series of experimental techniques based on low-energy electron microscopy (LEEM) to assess structural and electronic properties E0  is regularly used in so-called LEEM-IV experiments22E0 refs , 15, 19 k|| refs , 21  to both the three and four hBN layer areas. This indicates that the monolayer flake is electronically coupled to the underlying hBN in the same way these hBN layers are coupled to each other. It is worth noting that the minima expected for E0<2 eV are convoluted with the steep mirror-mode transition and are therefore hard to identify or are completely invisible.After establishing ARRES as a method to study band properties of graphite and bulk hBN—the mother compounds of vdW heterostructures—let us now discuss these materials in the few-layer limit. It is well known that for few-layer graphene, the continuous conduction band of graphite splits up into quantized transmission resonances. For a stack of ab initio ARRES calculations, that is, solving the full electron scattering problem in the vacuum and crystal half spaces (see Methods). The calculations, shown in E0<5 eV as well. The latter is the most exciting part, being the energy range of the quantized quasi-two-dimensional bands of bilayer, trilayer and four-layer hBN. Their respective dispersion relations are deduced from both E0<5 eV. However, this scenario is in stark contrast to the experimental results. In n transmission resonances for n+1 layers, just similar to that for few-layer graphene on Si. Hence, the intimate contact to the layered hBN crystal below does not lead to a common continuous band. Moreover, if we zoom out to the full energy scale (0–30 eV), we find that the IV curves continuously evolve from hBN-like to graphite-like as the number of graphene layers n increases. Specifically, all hBN-related features , and bulk hBN, IhBN(E0) (green and blue curves in the first panel of IvdW reflected from the full stack is given byFrom 1627n and the full energy range (it is noteworthy that the layer-dependent low-energy minima cannot be reproduced with this approach). We find a characteristic penetration depth of δ=0.9 graphene layers and a ratio of interaction cross-sections of low-energy electrons with graphene and hBN of σ=15. Moreover, this simple fit describes the data at least as well as more sophisticated electron reflection calculations that take band structures and coherent effects into account (light blue lines). The last panel in ab initio calculations of IV curves for different stacking geometries of graphene on hBN. The result is independent of the stacking geometry, which suggests that the unoccupied bands are not significantly affected by the details of the Moiré superlattice formed due to the lattice mismatch between graphene and hBN, a subtle effect that can be resolved at low temperatures close to the Fermi level101112The fit works remarkably well for all In this letter, we present a test bed for interactions in vdW materials by measuring quantized transmission resonances in their unoccupied band structure. We show that the conduction bands of few-layer hBN and graphene are quantized in a comparable manner. Despite their similar symmetry and energy range, however, the interlayer states of graphene and hBN do not interact electronically. This is an important insight into the graphene–hBN system, which is the most widely used vdW heterostructure. The methods presented here, specifically ARRES, are directly applicable to more complex vdW materials, for example, stacks including transition-metal dichalcogenides. Consequently, we can study (lack of) electronic overlap between the layers quantitatively. Similar to chemistry, where molecular orbitals are formed from atomic orbitals via their interaction to create compounds with novel properties, this brings us one step closer to a quantitative chemistry of layers. Detailed insight into the interlayer coupling marks an important step towards creating vdW heterostructures with properties not available in conventional materials.2 substrates. Few-layer flakes are selected via optical microscopy. For the vdW assembly, the top few-layer graphene flake is picked up from the Si/SiO2 substrate with a polydimethylsiloxane stamp coated with an adhesion layer of poly(bisphenol A-carbonate). vdW forces allow us to pick up hBN with this graphene layer. The whole assembly is placed onto a conductive silicon sample via thermal release of the poly(bisphenol A-carbonate) and wet-chemical cleaning in chloroform and isopropanol, subsequently. Few-layer hBN is transferred onto silicon substrates using the same method. The measurements presented here do not depend on the substrate used, as long as it is conductive enough to prevent charging. The samples are heated in the LEEM to 500 °C, to desorb any residues from the surface.We exfoliate flakes from highly oriented pyrolitic graphite and bulk hBN crystals onto Si/SiO−10 mbar and 400 °C, to prevent the formation of carbon-based contaminants under the electron beam.All measurements presented are conducted in the ESCHER setupab initio reflectivity spectra are obtained with the all-electron Bloch wave-based scattering method described in ref. All calculations were performed with a full-potential linear augmented plane waves method based on a self-consistent crystal potential obtained within the local density approximation as explained in ref. The data that support the findings of this study are available from the corresponding author upon request.How to cite this article: Jobst, J. et al. Quantifying electronic band interactions in van der Waals materials using angle-resolved reflected-electron spectroscopy. Nat. Commun.7, 13621 doi: 10.1038/ncomms13621 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


P < 0.05). Manual analysis of PD-L1 staining patterns identified tumors with an immune-induced reactive pattern relevant for immunotherapy that would ordinarily be excluded by the arbitrary 25% staining threshold (P < 0.05). Conversely, some cases with completely or predominantly immune-independent constitutive PD-L1 staining patterns that indicate insensitivity to immunotherapy may have been incorrectly selected using this staining cut-off point criterion. Therefore, we propose differentiation of reactive vs constitutive PD-L1 staining patterns to improve the accuracy of this biomarker assay in selecting NSCLC patients for PD-1/PD-L1 immunotherapy.Non-Small Cell Lung Cancer (NSCLC) is the leading cause of cancer death globally, and new immunotherapies developed and under development targeting PD-1/PD-L1 checkpoint inhibition require accurate patient selection to assure good clinical outcome. PD-L1 immunohistochemistry is the current biomarker assay used for patient selection, but still imprecise in predicting therapy response. Exploring this issue, we performed computational tissue analysis of PD-L1 immunostaining in procured NSCLC tissues (n = 50) using the Merck KGaA anti-PD-L1 clone MKP1A07310. Staining patterns and PD-L1 cut-off points were interrogated using relevant cancer immune-surveillance biomarkers. Groups with high PD-L1 expression levels (above 25/50% staining cut-off points) were enriched for a biomarker profile in the tumor-nest and microenvironment indicating escape from host-immunity, as represented by increased numbers of cells positive for CD8 and Granzyme B (immune-effectors), FOXP3 (immune-suppressive), and CD68 ( Lung cancer is the most lethal cancer type worldwide, with non-small cell lung cancer (NSCLC) accounting for the majority ~85%) of deaths . Late di% of deatThe PD-L1 staining profile targeted by PD-L1/PD-1 immunotherapies should be a reactive pattern induced by interferon (IFN)-γ secreted by tumor infiltrating lymphocytes (TIL) at tumor-nest-TME interfaces , 8–10. T™) capable of scoring entire sections, complementary to another NSCLC digital study [This is the first publication to report IHC data for tumor-nest and TME compartments in NSCLC samples using the Merck KGaA anti-PD-L1 clone MKP1A07310 for Avelumab development together with an immune panel of effector and regulatory TIL , as wellal study , we expaFormalin-fixed paraffin-embedded tissue blocks prepared using surgical resections from 50 treatment-naive NSCLC patients  were proin-situ carcinomatous changes. Exclusion annotations were made around staining and tissue artifacts including folds and tears, mounting media artifacts, stain smudges, and other artifacts deemed irreversible in the scanning process. Additional exclusions were areas of necrosis  at Flagship Biosciences’ tissue analysis laboratory. A minimum of 4 focal points were set for each slide to allow for optimal scanning quality, with scanning performed at x20. All whole-slide digital images were assessed for scanning artifacts including blurring due to incomplete cleaning, and ‘stitching’ artifacts. Scanning was repeated until all slides reached Flagships’ quality criteria for digital scans. Digital images were viewed using Aperio ImageScope , with manual annotation to include region(s) of interest (ROI). Inclusion annotations were made just outside the invasive margin of the tumor mass when present , excludinecrosis , entrappFull scan analysis was performed using Flagship Bioscience’s proprietary cTA image analysis software system  available for research. The platform identified nuclei in each sample based upon hematoxylin staining, then quantified the intensity of DAB staining for each nucleus-identified cell. To identify positive cells, thresholds for DAB staining were set using biomarker-specific algorithms for CD8, FOXP3, CD56, Granzyme B, CD68, and PD-L1. For PD-L1, multiple thresholds were identified according to a negative, +1, +2, and +3 scoring paradigm contiguous with manual scoring approaches . The bioIn addition to the image analysis detailed above, all slide images were reviewed and categorized according to the PD-L1 staining patterns (I-V) noted in tumor-nest and TME compartments, including the tumor-nest-TME interfaces . The sysHierarchical clustering of the data for all biomarkers was performed using the MATLAB bioinformatics toolbox version 2015a  with Euclidean distance metric and average linkage to generate the hierarchical tree. Data were normalized such that the mean was 0 and the standard deviation was 1 across samples for each marker score. Pearson correlation coefficients were also calculated between marker measurements and a heatmap was generated to visualize the strength of the correlations.P-values were calculated using a two-tailed Student’s t-test, assuming unequal sample variances. The Holm method was used to correct for multiple comparisons, with a significance threshold of P<0.05 for each subset of analyses.Percentages of cells positive for each biomarker were compared for tumors above and below 5%, 25%, 50%, and 80% cut-off points for PD-L1 immunostaining. These comparisons were made for the tumor-nest, TME, and “All Cells” compartments. Additionally, positive PD-L1 percentages, immune cell percentages, and digital H-scores were compared between the PD-L1 staining pattern categories in the tumor-nest and TME compartments, respectively. Data were plotted as box-and-whisker plots. Boxes show the median and interquartile range (IQR) and whiskers show the range of the data excluding outliers. Outliers are defined as data more than 1.5*IQR beneath the lower quartile or more than 1.5*IQR above the upper quartile. No data points were removed from analysis. P < 0.0001; Multiple biomarkers were analyzed in the tumor-nest, TME, and All Cells compartments. This allowed us to accurately assess the relative proportions of effector and regulatory cells in the typically heterogeneous NSCLC tissue microenvironment, and their possible relationships. In a small number of cases (n = 7), it was not possible to separate tumor-nest and TME compartments digitally as the latter was minimal; All Cells scores only were analyzed for those slides. In the group of cases where a separation between tumor-nest and microenvironment was feasible (n = 43), scores derived from a single marker showed a greater correlation across compartments than scores derived from different markers in the same compartment . For exaP < 0.05) of stained cells for CD68, CD8, FOXP3, and Granzyme B were detected in the high PD-L1 group when compared vs the low PD-L1 group (P = 0.14), but a higher FOXP3/CD8 ratio beneath the 50% threshold (P = 0.03). When applying a 5% PD-L1 tumor-nest cut-off, 70% of samples segregated to the high PD-L1 group, with CD8, Granzyme B, and CD68 significantly higher in those samples (P < 0.05). Statistical comparisons using an 80% PD-L1 tumor-nest cut-off value were impossible given that only one sample segregated to the high PD-L1 group.We compared the distributions of our immune markers relative to PD-L1 positive staining cut-offs  currently used in Merck KGaA PD-L1 clinical development programs. We studied cut-off points in the tumor nest, TME, and All Cells compartments, with a full analysis of the immune markers in each compartment. A 50% PD-L1 TME cut-off put only 14% of samples in the high PD-L1 group, increasing to 100% at a 5% PD-L1 TME cut-off. Whereas, data from tumor-nest cut-offs permitted a more balanced sample size distribution. For example, using the 25% and 50% PD-L1 tumor-nest cut-offs, approximately half of the samples were in the high PD-L1 group . A plot of 50% PD-L1 tumor-nest cut-off (most frequently scored by pathologists) for overall immune cell expression (All Cells) provides a summary of the global changes in cellular distribution for the PD-L1 high/low groups . Higher L1 group . ResultsThe staining patterns for PD-L1  were claIn NSCLC classified as pattern I, the tumor cells showed variable percentages of PD-L1 membrane labeling  and positive staining in TME cells . HeavierP < 0.00001). Importantly, most of those pattern II samples fell beneath the cut-off points when applying 50% and 25% PD-L1 tumor-nest thresholds .Comparison of tumor groups with patterns I and II revealed a lower percentage of PD-L1 positive cells in the tumor-nests from the group showing pattern II staining (resholds . Howeverresholds . A similresholds . In termUsing procured NSCLC tissues from naïve-treated patients with advanced disease, we adopted the cTA platform to identify and quantify multiple immune biomarkers in tumor-nest and TME compartments in whole sections. Pivotal to this analysis was the usage of the Merck KGaA anti-PD-L1 clone MKP1A07310, which is the analytical Ab for the evaluation of Avelumab , with sa+ cells versus total CD8+ cells in our study might be explained by a large proportion of exhausted CD8 T cells [+/CD8+ ratio did not differ significantly across the 25% and 50% thresholds, but might not be expected in our particular cohort of patients with advanced disease. Increased percentages of FOXP3+ cells with higher PD-L1 expression also suggested a tumor cell modulation of the adaptive immune response given that PD-L1/PD-1 interactions promote T-cells differentiation into regulatory cells [+ and CD8+ T-cells is another clinically linked parameter, as low-FOXP3/ high-CD8+ ratios have been linked with positive survival effects across multiple cancer types including NSCLC [+/CD8+ ratio was lower in NSCLC above the 50% PD-L1 cut-off point, but this result does not necessarily indicate a favorable TME for an adaptive anti-tumoral immune response due to the likelihood that most of those TIL are exhausted. Overall, these results support using PD-L1 immunostaining cut-off points to select patients with higher chances of responding to PD-1/PD-L1 checkpoint inhibition, as they are consistent with previous positive correlations of PD-L1 expression, numbers of TIL, and longer overall survival in NSCLC and other solid tumors [We have demonstrated enrichment of effector and regulatory immune cell types in groups with higher PD-L1 expression as defined by IHC thresholds of over 25 and 50%. This included CD8 and Granzyme B positive cells, with the latter being a marker that highlights functional effector T-cells . The sur T cells , 16. Thery cells . The balng NSCLC –19. In td tumors , 22–23. The categorization of tumor PD-L1 expression patterns related to TIL distribution has been discussed previously, suggesting clear guidelines for checkpoint inhibition immunotherapy , 8. ThisThe analysis of PD-L1 staining patterns of tumor cells was performed to titrate the presence of morphological structures where PD-L1/PD-1 interactions should occur like an ‘immunologic synapse’. This is the classic TCR/antigen presentation interface where T-cell immune activation and inhibitory signals interplay . In our In conclusion, using our cTA analysis of PD-L1 immunostaining relative to immune biomarkers that might be involved in NSCLC immune surveillance during this late disease stage, we demonstrated that groups with high levels of PD-L1 defined by cut-off points of 25 and 50% enriched also for higher amounts of FOxP3, CD8, Granzyme B, and CD68 positive cells in tumor-nest and TME. This association between high levels of PD-L1 and increased effector and suppressor adaptive as well as augmented innate immune tumor infiltrates may reflects escape from a potential host anti-tumoral immune response. Furthermore, high amounts of PD-L1 in NSCLC defined by these or other cut-off points may not accurately predict if anti-PD-1/PD-L1 therapy will successfully unleash a host anti-tumoral immune response. Selection of a specifically reactive PD-L1 staining pattern within regions of the tumor architecture where immunological synapses are formed is likely to be required for more accurate determination of which patients will benefit from this therapeutic intervention. We anticipate that the current data may trigger a new way to analyze clinical trial specimens, because discrimination between constitutive and reactive PD-L1 staining patterns should improve the precision of immunotherapy patient selection.