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Two-dimensional arsenic allotropes have been grown on metallic surfaces, while topological properties have been theoretically described on strained structures. Here we experimentally grow arsenene by molecular beam epitaxy over the insulating SiC substrate. The arsenene presents a flat structure with a strain field that follows the SiC surface periodicity. Our ab initio simulations, based on the density functional theory, corroborate the experimental observation. The strained structure presents a new arsenene allotrope with a triangular structure, rather than the honeycomb previously predicted for other pnictogens. This strained structure presents a Peierls-like transition leading to an indirect gap semiconducting behavior.

Molecular linkers have emerged as an effective strategy to improve electronic transport properties on solution-processed layered materials via defect functionalization. However, a detailed discussion on the microscopic mechanisms behind the beneficial effects of functionalization is still missing. Here, by first-principles calculations based on density functional theory, we investigate the effects on the electronic properties of interconnected MoS$_2$ model flakes systems upon functionalization with different thiol molecule linkers, namely thiophenol, 1,4-benzenedithiol, 1,2-ethanedithiol, and 1,3-propanedithiol. The bonding of benzene- and ethanedithiol bridging adjacent armchair MoS$_2$ nanoflakes leads to electronic states just above or at the Fermi level, thus forming a molecular channel for electronic transport between flakes. In addition, the molecular linker reduces the potential barrier for thermally activated hopping between neighboring flakes, improving the conductivity as verified in experiments. The comprehension of such mechanisms helps in future developments of solution-processed layered materials for use on 2D electronic devices.

Transition metal dichalcogenides (TMDCs) are promising materials for applications in nanoelectronics and correlated fields, where their metallic edge states play a fundamental role in the electronic transport. In this work, we investigate the transport properties of MoS$_2$ zigzag nanoribbons under a butadiene (C$_4$H$_6$) atmosphere, as this compound has been used to obtain MoS$_2$ flakes by exfoliation. We use density functional theory combined with non-equilibrium Green's function techniques, in a methodology contemplating disorder and different coverages. Our results indicate a strong modulation of the TMDC electronic transport properties driven by butadiene molecules anchored at their edges, producing the suppression of currents due to a backscattering process. Our results indicate a high sensitivity of the TMDC edge states. Thus, the mechanisms used to reduce the dimensionality of MoS$_2$ considerably modify its transport properties.

Elucidating cellulose-lignin interactions at the molecular and nanometric scales is an important research topic with impacts on several pathways of biomass valorization. Here, the interaction forces between a cellulosic substrate and lignin are investigated. Atomic force microscopy with lignin-coated tips is employed to probe the site-specific adhesion to a cellulose film in liquid water. Over seven thousand force-curves are analyzed by a machine-learning approach to cluster the experimental data into types of cellulose-tip interactions. The molecular mechanisms for distinct types of cellulose-lignin interactions are revealed by molecular dynamics simulations of lignin globules interacting with different cellulose Iβ crystal facets. This unique combination of experimental force-curves, data-driven analysis, and molecular simulations opens a new approach of investigation and updates the understanding of cellulose-lignin interactions at the nanoscale.

Cellulose disassembly is an important issue in designing nanostructures using cellulose-based materials. In this work, we present a combination of experimental and theoretical study addressing the disassembly of cellulose nanofibrils. Through 2,2,6,6-tetramethylpiperidine-1-oxyl-mediated oxidation processes, combined with atomic force microscopy results, we show the formation of nanofibers with diameters corresponding to that of a single-cellulose polymer chain. The formation of these polymer chains is controlled by repulsive electrostatic interactions between the oxidized chains. Further, first-principles calculations have been performed in order to provide an atomistic understanding of the cellulose disassembling processes, focusing on the balance between the interchain (IC) and intersheet (IS) interactions upon oxidation. First, we analyze these interactions in pristine systems, where we found the IS interaction to be stronger than the IC interaction. In the oxidized systems, we have considered the formation of (charged) carboxylate groups along the inner sites of elementary fibrils. We show a net charge concentration on the carboxylate groups, supporting the emergence of repulsive electrostatic interactions between the cellulose nanofibers. Indeed, our total energy results show that the weakening of the binding strength between the fibrils is proportional to the concentration and net charge density of the carboxylate group. Moreover, by comparing the IC and IS binding energies, we found that most of the disassembly processes should take place by breaking the IC O-H···O hydrogen bond interactions and thus supporting the experimental observation of single- and double-cellulose polymer chains.

The discovery and realization of topological insulators, a phase of matter which hosts metallic boundary states when the d-dimension insulating bulk is confined to (d − 1)-dimensions, led to several potential applications. Recently, it was shown that protected topological states can manifest in (d − 2)-dimensions, such as hinge and corner states for three- and two-dimensional systems, respectively. These nontrivial materials are named higher-order topological insulators (HOTIs). Here we show a connection between spin Hall effect and HOTIs using a combination of ab initio calculations and tight-binding modeling. The model demonstrates how a non-zero bulk midgap spin Hall conductivity (SHC) emerges within the HOTI phase. Following this, we performed high-throughput density functional theory calculations to find unknown HOTIs, using the SHC as a criterion. We calculated the SHC of 693 insulators resulting in seven stable two-dimensional HOTIs. Our work guides novel experimental and theoretical advances towards higher-order topological insulator realization and applications.

X-ray computed microtomography (μCT) is an innovative and nondestructive versatile technique that has been used extensively to investigate bio-based systems in multiple application areas. Emerging progress in this field has brought countless studies using μCT characterization, revealing three-dimensional (3D) material structures and quantifying features such as defects, pores, secondary phases, filler dispersions, and internal interfaces. Recently, x-ray computed tomography (CT) beamlines coupled to synchrotron light sources have also enabled computed nanotomography (nCT) and four-dimensional (4D) characterization, allowing in situ, in vivo, and in operando characterization from the micro- to nanostructure. This increase in temporal and spatial resolutions produces a deluge of data to be processed, including real-time processing, to provide feedback during experiments. To overcome this issue, deep learning techniques have risen as a powerful tool that permits the automation of large amounts of data processing, availing the maximum beamline capabilities. In this context, this review outlines applications, synchrotron capabilities, and data-driven processing, focusing on the urgency of combining computational tools with experimental data. We bring a recent overview on this topic to researchers and professionals working not only in this and related areas but also to readers starting their contact with x-ray CT techniques and deep learning.

Summary Atomic-scale structure determination is crucial to the understanding of nanomaterial properties and development of new technologies. Although pair distribution function (PDF) analysis by neutrons and X-ray scattering profile has been used to study materials, electron diffraction can offer advantages to characterize the atomic structure of clusters, amorphous samples, and nanomaterials. Electrons have higher scattering power than X-rays, allowing the acquirement of PDF from electron diffraction (ePDF) for small sample amounts and with time-efficient data acquisition. Compared with synchrotron X-rays and neutrons as sources for PDF, the availability of electron microscopes worldwide is advantageous. Nowadays, with the rise of methodologies and specific software for ePDF data analysis, the scientific community can benefit from advanced transmission electron microscopy (TEM) structure determination integrating commonly available TEM analyses—size, distribution, shape, and high-resolution TEM atomic visualization—with ePDF atomic structure determination, both for bulk and surface configurations. Therefore, ePDF has the potential to become a routine and advanced characterization tool for nanomaterials science.

Recently cycloarene has been experimentally obtained in a self-assembled structure, forming graphene-like monoatomic layered systems. Here, we established bandgap engineering/prediction in cycloarene assemblies within a combination of density functional theory and tight-binding Hamiltonians. Our results show that the inter-molecule bond density rules the bandgap. The increase in such bond density increases the valence/conduction bandwidth decreasing the energy gap linearly. We derived an effective model that allows the interpretation of the arising energy gap for general particle-hole symmetric molecular arrangements based on inter-molecular bond strength.

Two-dimensional transition metal dichalcogenides (MX$_2$) vacancy formation energetics is extensively investigated. Within an ab-initio approach we study the MX$_2$ systems, with M=Mo, W, Ni, Pd and Pt, and X=S, Se, and Te. Here we classify that chalcogen vacancies are always energetic favorable over the transition metal ones. However, for late transition metals Pd $4d$, and Pt $5d$ the metal vacancy are experimentally achievable, bringing up localized magnetic moments within the semiconducting matrix. By quantifying the localization of the chalcogen vacancy states we evidentiate that it rules the intra- and inter-vacancy interactions that establish both the number of vacancy states neatly lying within the semiconducting gap, as well as its electronic dispersion and SOC splitting. Combining different vacancies and phase variability 1T and 1H of the explored systems allow us to construct a guiding picture for the vacancy states localization.

Monolayers of transition metal dichalcogenides (TMDs) in the 2H structural phase have been recently classified as higher-order topological insulators (HOTI), protected by $C_3$ rotation symmetry. In addition, theoretical calculations show an orbital Hall plateau in the insulating gap of TMDs, characterized by an orbital Chern number. We explore the correlation between these two phenomena in TMD monolayers in two structural phases: the noncentrosymmetric 2H and the centrosymmetric 1T. Using density functional theory, we confirm the characteristics of 2H-TMDs and reveal that 1T-TMDs are identified by a $\mathbb{Z}_4$ topological invariant. As a result, when cut along appropriate directions, they host conducting edge-states, which cross their bulk energy-band gaps and can transport orbital angular momentum. Our linear response calculations thus indicate that the HOTI phase is accompanied by an orbital Hall effect. Using general symmetry arguments, we establish a connection between the two phenomena with potential implications for spin-orbitronics., 5 pages, 4 figures

It has recently been demonstrated that N-heterocyclic carbenes (NHCs) form self-assembled monolayers (SAMs) on metal surfaces. Consequently, it is important to both characterize and understand their binding modes to fully exploit NHCs in functional surface systems. To assist with this effort, we have performed first-principles total energy calculations for NHCs on Au(111) and simulations of X-ray absorption near edge structure (XANES). The NHCs we have considered are N,N-dimethyl-, N,N-diethyl-, N,N-diisopropylbenzimidazolylidene (BNHCX, with X = Me, Et, and iPr, respectively) and the bis-BNHCX-Au complexes derived from these molecules. We present a comprehensive analysis of the energetic stability of both the BNHCX and the complexes on Au(111) and, for the former, examine the role of the wing group in determining the attachment geometry. Further structural characterization is performed by calculating the nitrogen K-edge X-ray absorption spectra. Our simulated XANES results give insight into (i) the relationship between the BNHCX/Au geometry and the N(1s) → π*/σ*, pre-edge/near-edge, absorption intensities, and (ii) the contributions of the molecular deformation and molecule-surface electronic interaction to the XANES spectrum. These simulated spectra work not only as a map to the BNHCX conformation, but also, combined with electronic structure calculations, provide a clear understanding of recent experimental XANES findings on BNHCX/Au.

Using a combination of in situ high-resolution transmission electron microscopy and density functional theory, we report the formation and rupture of ZrO_{2} atomic ionic wires. Near rupture, under tensile stress, the system favors the spontaneous formation of oxygen vacancies, a critical step in the formation of the monatomic bridge. In this length scale, vacancies provide ductilelike behavior, an unexpected mechanical behavior for ionic systems. Our results add an ionic compound to the very selective list of materials that can form monatomic wires and they contribute to the fundamental understanding of the mechanical properties of ceramic materials at the nanoscale.

Proximity effects between layered materials trigger a plethora of novel and exotic quantum transport phenomena. Besides, the capability to modulate the nature and strength of proximity effects by changing crystalline and interfacial symmetries offers a vast playground to optimize physical properties of relevance for innovative applications. In this work, we use large-scale first principles calculations to demonstrate that strain and twist-angle strongly vary the spin–orbit coupling (SOC) in graphene/transition metal dichalcogenide heterobilayers. Such a change results in a modulation of the spin relaxation times by up to two orders of magnitude. Additionally, the relative strengths of valley-Zeeman and Rashba SOC can be tailored upon twisting, which can turn the system into an ideal Dirac–Rashba regime or generate transitions between topological states of matter. These results shed new light on the debated variability of SOC and clarify how lattice deformations can be used as a knob to control spin transport. Our outcomes also suggest complex spin transport in polycrystalline materials, due to the random variation of grain orientation, which could reflect in large spatial fluctuations of SOC fields., A P was supported in part by the Coordenaoção de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001. A F was supported by FAPESP (Grant 16/14011-2), J H G and S R were supported by the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 881603 (Graphene Flagship). ICN2 is funded by the CERCA Programme/Generalitat de Catalunya (Grant 2017SGR1506), and is supported by the Severo Ochoa program from Spanish MINECO (Grant No. SEV-2017-0706). Z Z acknowledges financial support by the Ramon y Cajal program RYC-2016-19344 (MINECO/AEI/FSE, UE). Z Z, N W, and P O acknowledge support from the EC H2020-INFRAEDI-2018-2020 MaX 'Materials Design at the Exascale' CoE (Grant No. 824143) and Spanish MCIU/AEI (Grant No. PGC2018-096055-B-C43). Z Z acknowledges the Netherlands Sector Plan program 2019–2023. N W has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 754558. Z Z and N W acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (FI-2020-1-0014). We acknowledge PRACE for awarding us access to MareNostrum 4 at Barcelona Supercomputing Center (BSC), Spain (OptoSpin Project ID. 2020225411).

The development of spintronic devices demands the existence of materials with some kind of spin splitting (SS). In this Data Descriptor, we build a database of ab initio calculated SS in 2D materials. More than that, we propose a workflow for materials design integrating an inverse design approach and a Bayesian inference optimization. We use the prediction of SS prototypes for spintronic applications as an illustrative example of the proposed workflow. The prediction process starts with the establishment of the design principles (the physical mechanism behind the target properties), that are used as filters for materials screening, and followed by density functional theory (DFT) calculations. Applying this process to the C2DB database, we identify and classify 358 2D materials according to SS type at the valence and/or conduction bands. The Bayesian optimization captures trends that are used for the rationalized design of 2D materials with the ideal conditions of band gap and SS for potential spintronics applications. Our workflow can be applied to any other material property.

Understanding the role of microscopic attributes in nanocomposites allows for a controlled and, therefore, acceleration in experimental system designs. In this work, we extracted the relevant parameters controlling the graphene oxide binding strength to cellulose by combining first-principles calculations and machine learning algorithms. We were able to classify the systems among two classes with higher and lower binding energies, which are well defined based on the isolated graphene oxide features. By a theoretical X-ray photoelectron spectroscopy analysis, we show the extraction of these relevant features. Additionally, we demonstrate the possibilities of a refined control within a machine learning regression between the binding energy values and the system's characteristics. Our work presents a guiding map to the control graphene oxide/cellulose interaction.

Made available in DSpace on 2020-12-10T19:51:01Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-02-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) In this perspective, we discuss computational advances in the last decades, both in algorithms as well as in technologies, that enabled the development, widespread use, and maturity of simulation methods for molecular and materials systems. Such advances led to the generation of large amounts of data, which required the creation of several computational databases. Within this scenario, with the democratization of data access, the field now encounters several opportunities for data-driven approaches toward chemical and materials problems. Specifically, machine learning methods for predictions of novel materials or properties are being increasingly used with great success. However, black box usage fails in many instances; several technical details require expert knowledge in order for the predictions to be useful, such as with descriptors and algorithm selection. These approaches represent a direction for further developments, notably allowing advances for both developed and emerging countries with modest computational infrastructures. Fed Univ ABC UFABC, Santo Andre, SP, Brazil Brazilian Nanotechnol Natl Lab LNNano CNPEM, Campinas, SP, Brazil Sao Paulo State Univ, Inst Fis Teor, Sao Paulo, Brazil Sao Paulo State Univ, Inst Fis Teor, Sao Paulo, Brazil FAPESP: 2017/18139-6 FAPESP: 18/05565-0 FAPESP: 17/02317-2

Novel two-dimensional non-van der Waals materials have been reported, boosting efforts to probe their properties and identify key applications. In this work, we report the synthesis, by means of a novel route via sonication of synthetic hematite, and characterization by transmission electron and atomic force microscopy of samples composed of two-dimensional hematite ([001]-cut layered α-Fe2O3). Microscopy images show a layered material with a handful of possible crystalline orientations, of which the [001] is the most abundant, presenting thickness of up to approximately 100 nm. Next, we employed first-principles calculations to study their structural stability and evaluate their thickness distribution. The stability of single, double, and triple layered structures is confirmed by phonon spectra and the formation energy is obtained, pointing out to the possibility of few layers, freestanding, stable samples. Further statistical modeling suggests that even though such thin samples are stable, their abundan...

The electronic transport properties in molecular heterojunctions are intimately connected with the molecular conformation between the electrodes, and the electronic structure of the molecule/electrode interface. In this work, we perform an ab initio density-functional-theory investigation of the structural and transport properties through self-assembled CuPc molecules sandwiched between gold contacts with (111) surfaces. We demonstrated (i) a tunneling regime ruled by the π orbitals of the aromatic rings of CuPc molecules; and (ii) a high variation (up to two orders of magnitude) of the current density with the orientation of the CuPc molecules relative to the gold surface. The source of this variation is the geometrical dependence of the energy of the highest-occupied-molecular-orbital with respect to the chemical potential of the metal and the generation of intra-molecular transport channels for a configuration with CuPc molecules tilted with respect to the gold surface.

Polyphenols are natural molecules of crucial importance in many applications, of which tannic acid (TA) is one of the most abundant and established. Most high-value applications require precise control of TA interactions with the system of interest. However, the molecular structure of TA is still not comprehended at the atomic level, of which all electronic and reactivity properties depend. Here, we combine an enhanced sampling global optimization method with density functional theory (DFT)-based calculations to explore the conformational space of TA assisted by unsupervised machine learning visualization and then investigate its lowest energy conformers. We study the external environment's effect on the TA structure and properties. We find that vacuum favors compact structures by stabilizing peripheral atoms' weak interactions, while in water, the molecule adopts more open conformations. The frontier molecular orbitals of the conformers with the lowest harmonic vibrational free energy have a HOMO-LUMO energy gap of 2.21 (3.27) eV, increasing to 2.82 (3.88) eV in water, at the DFT generalized gradient approximation (and hybrid) level of theory. Structural differences also change the distribution of potential reactive sites. We establish the fundamental importance of accurate structural consideration in determining TA and related polyphenol interactions in relevant technological applications.

Vacancies in materials structure -- lowering its atomic density -- take the system closer to the atomic limit, to which all systems are topologically trivial. Here we show a mechanism of mediated interaction between vacancies inducing a topologically non-trivial phase. Within an {\it ab initio} approach we explore topological transition dependence with the vacancy density in transition metal dichalcogenides. As a case of study, we focus on the PtSe$_2$, to which pristine form is a trivial semiconductor with an energy gap of $1.2$\,eV. The vacancies states lead to a large topological gap of $180$\,meV within the pristine system gap. We derive an effective model describing this topological phase in other transition metal dichalcogenide systems. The mechanism driving the topological phase allows the construction of backscattering protected metallic channels embedded in a semiconducting host.

One of the main goals and challenges of materials discovery is to find the best candidates for each interest property or application. Machine learning rises in this context to efficiently optimize this search, exploring the immense materials space, consisting of simultaneously the atomic, compositional, and structural spaces. Topological insulators, presenting symmetry-protected metallic edge states, are a promising class of materials for different applications. However, further, development is limited by the scarcity of viable candidates. Here we present and discuss machine learning-accelerated strategies for searching the materials space for two-dimensional topological materials. We show the importance of detailed investigations of each machine learning component, leading to different results. Using recently created databases containing thousands of ab initio calculations of 2D materials, we train machine learning models capable of determining the electronic topology of materials, with an accuracy of over 90%. We can then generate and screen thousands of novel materials, efficiently predicting their topological character without the need for a priori structural knowledge. We discover 56 non-trivial materials, of which 17 novel insulating candidates for further investigation, for which we corroborate their topological properties with density functional theory calculations. This strategy is 10$\times$ more efficient than the trial-and-error approach while few orders of magnitude faster and is a proof of concept for guiding improved materials discovery search strategies., Comment: Accepted for publication in Applied Physical Review. For Supplemental Materials please contact one of the authors

In recent years, the notion of Quantum Materials has emerged as a powerful unifying concept across diverse fields of science and engineering, from condensed-matter and cold atom physics to materials science and quantum computing. Beyond traditional quantum materials such as unconventional superconductors, heavy fermions, and multiferroics, the field has significantly expanded to encompass topological quantum matter, two-dimensional materials and their van der Waals heterostructures, Moire materials, Floquet time crystals, as well as materials and devices for quantum computation with Majorana fermions. In this Roadmap collection we aim to capture a snapshot of the most recent developments in the field, and to identify outstanding challenges and emerging opportunities. The format of the Roadmap, whereby experts in each discipline share their viewpoint and articulate their vision for quantum materials, reflects the dynamic and multifaceted nature of this research area, and is meant to encourage exchanges and discussions across traditional disciplinary boundaries. It is our hope that this collective vision will contribute to sparking new fascinating questions and activities at the intersection of materials science, condensed matter physics, device engineering, and quantum information, and to shaping a clearer landscape of quantum materials science as a new frontier of interdisciplinary scientific inquiry., Comment: 93 pages, 27 figures

Understanding the effects of atomic structure modification in hematite photoanodes is essential for the rational design of high-efficiency functionalizations. Recently it was found that interface modification with Sn/Sb segregates considerably increases hematite photocatalytic efficiency. However, the understanding of the different electronic effects of these modifications at the atomic level is still lacking. This letter describes the segregation effects of two different dopants-Sn and Sb-on both the solid-solid (grain-boundaries) and solid-liquid interfaces (surfaces) of hematite. Within an ab-initio approach, we quantitatively extract the potential barrier reduction on polycrystalline interfaces due to the dopant, which causes an increase in the inter-grain electron transport. Concomitantly, the dopants' segregation on hematite surfaces results in a decrease of the oxygen vacancy formation energy. Such vacancies lead to the experimentally observed rise of the flat-band potential. The comprehension of the electronic effects of dopants on both types of interfaces explains the experimental peak efficiency of interface-modified hematite with dopant segregates, also enabling the control and design of interfaces for different higher-efficiency applications.

Avanços recentes nas técnicas experimentais e desenvolvimentos teóricos e computacionais resultaram em um aumento crescente na geração de dados. Essa disponibilidade de dados, associada à novas ferramentas e tecnologias capazes de armazenar e processar esses dados, culminaram na chamada ciência de dados. Uma das áreas de maior destaque recente são os algoritmos de aprendizado de máquina (machine learning), que têm como objetivo a identificação de correlações e padrões nos conjuntos de dados. Esses algoritmos vêm sendo usados há décadas, por exemplo nas áreas da saúde. Apenas recentemente a comunidade introduziu a sua aplicação para materiais, devido à criação, padronização e consolidação de bancos de dados consistentes. O uso dessas metodologias permite extrair conhecimento e insights da enorme quantidade de dados brutos e informações agora disponíveis. A área apresenta diversas oportunidades para a solução de desafios na física, química e ciência de materiais. Especificamente, os métodos de machine learning são uma poderosa ferramenta para a descoberta e design de novos materiais com propriedades e funcionalidades desejadas e otimizadas. Neste artigo apresentamos o contexto do surgimento do machine learning, seus fundamentos e aplicações para a descoberta e design de materiais.

Made available in DSpace on 2022-04-28T19:41:57Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-09-01 Alexander von Humboldt-Stiftung Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The advances of surface-supported metal-organic framework (SURMOF) thin-film synthesis have provided a novel strategy for effectively integrating metal-organic framework (MOF) structures into electronic devices. The considerable potential of SURMOFs for electronics results from their low cost, high versatility, and good mechanical flexibility. Here, the first observation of room-temperature negative differential resistance (NDR) in SURMOF vertical heterojunctions is reported. By employing the rolled-up nanomembrane approach, highly porous sub-15 nm thick HKUST-1 films are integrated into a functional device. The NDR is tailored by precisely controlling the relative humidity (RH) around the device and the applied electric field. The peak-to-valley current ratio (PVCR) of about two is obtained for low voltages (

Material's geometrical structure is a fundamental part of their properties. The honeycomb geometry of graphene is responsible for the arising of its Dirac cone, while the kagome and Lieb lattice hosts flat bands and pseudospin-1 Dirac dispersion. These features seem to be particular for few 2D systems rather than a common occurrence. Given this correlation between structure and properties, exploring new geometries can lead to unexplored states and phenomena. Kepler is the pioneer of the mathematical tiling theory, describing ways of filing the euclidean plane with geometrical forms in its book {\it Harmonices Mundi}. In this letter, we characterize $1255$ lattices composed of the euclidean plane's k-uniform tiling, with its intrinsic properties unveiled - this class of arranged tiles present high-degeneracy points, exotic quasiparticles, and flat bands as a common feature. Here, we present aid for experimental interpretation and prediction of new 2D systems.

Jacutingate, a recently discovered Brazilian naturally occurring mineral, has been shown to be an experimental realization of the Kane-Mele topological model. In this paper we present a class of materials, ${M}_{2}N{X}_{3}$ ($M=\mathrm{Ni}$, Pt, and Pd; $N=\mathrm{Zn}$, Cd, and Hg; and $X=\mathrm{S}$, Se, and Te), sharing jacutingaite's key features, i.e., high stability and a topological phase. By employing first-principles calculations we extensively characterize the energetic stability of this class while showing a common occurrence of the Kane-Mele topological phase. Here we present Pt-based materials surpassing jacutingaite's impressive topological gap and lower exfoliation barrier while retaining its stability.

The robustness of topological materials against disorder and defects is presumed but has not been demonstrated explicitly in realistic systems. In this work, we use state-of-the-art density functional theory and recursive nonequilibrium Green's functions methods to study the effect of disorder on the electronic transport of long nanoribbons, up to $157\phantom{\rule{0.28em}{0ex}}\mathrm{nm}$, as a function of vacancy concentration. In narrow nanoribbons, a finite-size effect gives rise to hybridization between the edge states erasing topological protection. Hence, even small vacancy concentrations enable backscattering events. We show that the topological protection is more robust for wide nanoribbons, but surprisingly it breaks down at moderate structural disorder. Our study helps to establish some bounds on defective bismuthene nanoribbons as promising candidates for spintronic applications.

Cofunctionality---the coexistence of different (possibly even contraindicated) properties in the same compound---is an exciting prospect that never fails to deliver interesting surprises, as in transparent while electrically conducting compounds, topological insulators having Rashba spin split bands, or electrically conducting while thermally insulating (thermoelectric) compounds. Here we study a cofunctionality of ferroelectricity and Rashba effect that combines the directional helical spin-polarization characteristic of the energy bands of bulk Rashba compounds with the existence of two opposite electric polarization states, characteristic of atomic displacements in displacive ferroelectrics. Flipping of the ferroelectric polarization (e.g., via an applied electric field) would result in the reversal of the Rashba spin polarization. However, thus far, only very few (essentially one) compounds have been found to be ferroelectric Rashba semiconductors (FERSCs), e.g., GeTe ($R3m$). In this paper, we propose a general strategy for the identification of compounds that possess cofunctionalities and apply it to perform an inverse design, finding compounds that simultaneously have ferroelectricity and Rashba spin splitting. The inverse design combining functionality ${f}_{1}$ with ${f}_{2}$ involves definition and utilization of causal factors that enable the said functionalities, and involves three steps: (1) screening materials that satisfy the enabling DPs common to the two functionalities ${f}_{1}$ and ${f}_{2}$; (2) filtering the materials according to DPs that are unique to each of the individual functionalities ${f}_{1}$ and ${f}_{2}$; and (3) by using the ensuing two compound lists of compounds $C({f}_{1})$ and $C({f}_{2})$ identifying the intersection between them, i.e., compounds $C({f}_{1},{f}_{2})$ possessing simultaneous ${f}_{1}$ and ${f}_{2}$. Based on this process, we design 52 atomic combinations not suspected to be FERSCs that were previously synthesized. Of these 52 compounds, we find 24 FERSCs that are thermodynamically stable (i.e., reside on the convex hull) and, at the same time, feature larger spin splitting (large than 25 meV). These include ${\mathrm{BrF}}_{5}(Cmc{2}_{1})$, $\mathrm{TlI}{\mathrm{O}}_{3}(R3m)$, $\mathrm{Zn}{\mathrm{I}}_{2}{\mathrm{O}}_{6}(P{2}_{1})$, $\mathrm{LaTa}{\mathrm{O}}_{4}(Cmc{2}_{1})$, ${\mathrm{Tl}}_{3}{\mathrm{S}}_{3}\mathrm{Sb}(R3m)$, ${\mathrm{Sn}}_{2}{\mathrm{P}}_{2}{\mathrm{Se}}_{6}$ (Pc), and ${\mathrm{Bi}}_{2}\mathrm{Si}{\mathrm{O}}_{5}(Cmc{2}_{1})$ that have Rashba spin splitting of 31, 57, 111, 40, 90, 67, and 76 meV, respectively. Density functional theory calculations illustrate the reversal of the spin texture when the electric polarization is flipped. This paper validates a general approach for the search of other cofunctionalities based on causal enabling design principles rather than uncovering machine correlations.

Extracellular vesicles (EVs) are a frontier class of circulating biomarkers for the diagnosis and prognosis of different diseases. These lipid structures afford various biomarkers such as the concentrations of the EVs (CV) themselves and carried proteins (CP). However, simple, high-throughput, and accurate determination of these targets remains a key challenge. Herein, we address the simultaneous monitoring of CV and CP from a single impedance spectrum without using recognizing elements by combining a multidimensional sensor and machine learning models. This multidetermination is essential for diagnostic accuracy because of the heterogeneous composition of EVs and their molecular cargoes both within the tumor itself and among patients. Pencil HB cores acting as electric double-layer capacitors were integrated into a scalable microfluidic device, whereas supervised models provided accurate predictions, even from a small number of training samples. User-friendly measurements were performed with sample-to-answer data processing on a smartphone. This new platform further showed the highest throughput when compared with the techniques described in the literature to quantify EVs biomarkers. Our results shed light on a method with the ability to determine multiple EVs biomarkers in a simple and fast way, providing a promising platform to translate biofluid-based diagnostics into clinical workflows.

In recent years, cryogenic electron microscopy (Cryo-EM) has revolutionized the structure determination of wet samples and especially that of biological macromolecules. The glassy-water medium in which the molecules are embedded is considered an almost

Made available in DSpace on 2020-12-10T17:26:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-02-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Memristors (MRs) are considered promising devices with the enormous potential to replace complementary metal-oxide-semiconductor (CMOS) technology, which approaches the scale limit. Efforts to fabricate MRs-based hybrid materials may result in suitable operating parameters coupled to high mechanical flexibility and low cost. Metal-organic frameworks (MOFs) arise as a favorable candidate to cover such demands. The step-by-step growth of MOFs structures on functionalized surfaces, called surface-supported metal-organic frameworks (SURMOFs), opens the possibility for designing new applications in strategic fields such as electronics, optoelectronics, and energy harvesting. However, considering the MRs architecture, the typical high porosity of these hybrid materials may lead to short-circuited devices easily. In this sense, here, it is reported for the first time the integration of SURMOF films in rolled-up scalable-functional devices. A freestanding metallic nanomembrane provides a robust and self-adjusted top mechanical contact on the SURMOF layer. The electrical characterization reveals an ambipolar resistive switching mediated by the humidity level with low-power consumption. The electronic properties are investigated with density functional theory (DFT) calculations. Furthermore, the device concept is versatile, compatible with the current parallelism demands of integration, and transcends the challenge in contacting SURMOF films for scalable-functional devices. Brazilian Ctr Res Energy & Mat CNPEM, Campinas, Brazil Univ Campinas UNICAMP, Campinas, Brazil Sao Paulo State Univ UNESP, Bauru, SP, Brazil Sao Paulo State Univ UNESP, Bauru, SP, Brazil CNPq: 465452/2014-0 CNPq: 305305/2016-6 CNPq: 408770/2018/0 FAPESP: 2014/25979-2 FAPESP: 2016/25346-5 FAPESP: 2017/02317-2 FAPESP: 2017/25553-3 FAPESP: 2018/05565-0 FAPESP: 2014/50906-9

The spin-orbit -induced spin splitting of energy bands in low symmetry compounds (the Rashba Effect) has a long-standing relevance to spintronic applications and to the fundamental understanding of symmetry breaking in solids, yet the knowledge of what controls its magnitude in different materials is difficult to anticipate. Indeed, rare discoveries of compounds with large Rashba coefficients are invariably greeted as pleasant surprises. We advance the understanding of the "Rashba Scale" using the "inverse design" approach by formulating theoretically the relevant design principle and then identifying compounds that satisfy it. We show that the presence of energy band anti-crossing provides a causal design principle of compounds with large Rashba coefficients, leading to the identification via first-principles calculations of 34 rationally designed strong-Rashba compounds. Since topological insulators must have band anti crossing, this leads us to establish an interesting cross functionality of "Topological Rashba Insulators" (TRI) that may provide a platform for the simultaneous control of spin splitting and spin-polarization., Comment: 24 pages and 9 figures

Two-dimensional ${\mathrm{Na}}_{3}\mathrm{Bi}$ is a dual topological insulator protected by time-reversal and mirror symmetry, resulting in a promising platform for device design. However, in reality, the design of topological devices is hindered by a sensitivity against disorder and temperature. We study the topological properties of ${\mathrm{Na}}_{3}\mathrm{Bi}$ in the presence of intrinsic defects, investigating the robustness of the edge states and the resulting transport properties. We apply a recursive Green's function technique enabling the study of disordered systems with lengths comparable to experimentally synthesized materials, in the order of micrometers. We combine our findings to propose a topological insulator device, where intrinsic defects are used to filter the response of trivial bulk states. This results in a stable conductance throughout a large range of electronic temperatures, and controllable by a perpendicular electric field. Our proposal is general, enabling the design of various dual topological insulator devices.