Wafer-Scale Epitaxial Growth of an Atomically Thin Single-Crystal Insulator as a Substrate of Two-Dimensional Material Field-Effect Transistors.

As the electron mobility of two-dimensional (2D) materials is dependent on an insulating substrate, the nonuniform surface charge and morphology of silicon dioxide (SiO2) layers degrade the electron mobility of 2D materials. Here, we demonstrate that an atomically thin single-crystal insulating layer of silicon oxynitride (SiON) can be grown epitaxially on a SiC wafer at a wafer scale and find that the electron mobility of graphene field-effect transistors on the SiON layer is 1.5 times higher than that of graphene field-effect transistors on typical SiO2 films. Microscale and nanoscale void defects caused by heterostructure growth were eliminated for the wafer-scale growth of the single-crystal SiON layer. The single-crystal SiON layer can be grown on a SiC wafer with a single thermal process. This simple fabrication process, compatible with commercial semiconductor fabrication processes, makes the layer an excellent replacement for the SiO2/Si wafer.

A genome-wide association study for eumelanin pigmentation in chicken plumage using a computer vision approach.

Chicken plumage colouration is an important trait related to productivity in poultry industry. Therefore, the genetic basis for pigmentation in chicken plumage is an area of great interest. However, the colour trait is generally regarded as a qualitative trait and representing colour variations is difficult. In this study, we developed a method to quantify and classify colour using an F2 population crossed from two pure lines: White Leghorn and the Korean indigenous breed Yeonsan Ogye. Using red, green, and blue values in the cropped body region, we identified significant genomic regions on chromosomes 33:3 160 480-7 447 197 and Z:78 748 287-79 173 793. Furthermore, we identified two potential candidate genes (PMEL and MTAP) that might have significant effects on melanin-based plumage pigmentation. Our study presents a new phenotyping method using a computer vision approach and provides new insights into the genetic basis of melanin-based feather colouration in chickens.

BioVLAB-Cancer-Pharmacogenomics: tumor heterogeneity and pharmacogenomics analysis of multi-omics data from tumor on the cloud.

MOTIVATION: Multi-omics data in molecular biology has accumulated rapidly over the years. Such data contains valuable information for research in medicine and drug discovery. Unfortunately, data-driven research in medicine and drug discovery is challenging for a majority of small research labs due to the large volume of data and the complexity of analysis pipeline. RESULTS: We present BioVLAB-Cancer-Pharmacogenomics, a bioinformatics system that facilitates analysis of multi-omics data from breast cancer to analyze and investigate intratumor heterogeneity and pharmacogenomics on Amazon Web Services. Our system takes multi-omics data as input to perform tumor heterogeneity analysis in terms of TCGA data and deconvolve-and-match the tumor gene expression to cell line data in CCLE using DNA methylation profiles. We believe that our system can help small research labs perform analysis of tumor multi-omics without worrying about computational infrastructure and maintenance of databases and tools. AVAILABILITY AND IMPLEMENTATION: http://biohealth.snu.ac.kr/software/biovlab_cancer_pharmacogenomics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Higher-Order Topological Insulator in Twisted Bilayer Graphene.

Higher-order topological insulators are newly proposed topological phases of matter, whose bulk topology manifests as localized modes at two- or higher-dimensional lower boundaries. In this Letter, we propose the twisted bilayer graphenes with large angles as higher-order topological insulators, hosting topological corner charges. At large commensurate angles, the intervalley scattering opens up the bulk gap and the corner states occur at half filling. Based on both first-principles calculations and analytic analysis, we show the striking results that the emergence of the corner states do not depend on the choice of the specific angles as long as the underlying symmetries are intact. Our results show that the twisted bilayer graphene can serve as a robust candidate material of a two-dimensional higher-order topological insulator.

Electron Beam Irradiated Al Doped ZnO Thin Films as Efficient Tunnel Recombination Junction for Hydrogenated Amorphous Silicon/Cu(In,Ga)Se2 Tandem Solar Cells.

A tunnel recombination junction (TRJ) layer for hydrogenated amorphous silicon (a-Si:H)/ Cu(In,Ga)Se2 (CIGS) tandem solar cells is investigated. An Al-doped zinc oxide (AZO) thin film is applied to the TRJ, and the influence of electron beam (e-beam) irradiation on defects along the TRJ is investigated. The AZO thin films are prepared using radio frequency (RF) sputtering and the e-beam is irradiated at 200 W RF power and 2 keV DC power for 5 min. In the e-beam irradiated AZO thin film, the number of oxygen vacancies and Zn interstitials increases, which in turn strengthens the effect of defect-enhanced tunnel recombination.

Band Topology and Linking Structure of Nodal Line Semimetals with Z_{2} Monopole Charges.

We study the band topology and the associated linking structure of topological semimetals with nodal lines carrying Z_{2} monopole charges, which can be realized in three-dimensional systems invariant under the combination of inversion P and time reversal T when spin-orbit coupling is negligible. In contrast to the well-known PT-symmetric nodal lines protected only by the π Berry phase, in which a single nodal line can exist, the nodal lines with Z_{2} monopole charges should always exist in pairs. We show that a pair of nodal lines with Z_{2} monopole charges is created by a double band inversion process and that the resulting nodal lines are always linked by another nodal line formed between the two topmost occupied bands. It is shown that both the linking structure and the Z_{2} monopole charge are the manifestation of the nontrivial band topology characterized by the second Stiefel-Whitney class, which can be read off from the Wilson loop spectrum. We show that the second Stiefel-Whitney class can serve as a well-defined topological invariant of a PT-invariant two-dimensional insulator in the absence of Berry phase. Based on this, we propose that pair creation and annihilation of nodal lines with Z_{2} monopole charges can mediate a topological phase transition between a normal insulator and a three-dimensional weak Stiefel-Whitney insulator. Moreover, using first-principles calculations, we predict ABC-stacked graphdiyne as a nodal line semimetal (NLSM) with Z_{2} monopole charges having the linking structure. Finally, we develop a formula for computing the second Stiefel-Whitney class based on parity eigenvalues at inversion-invariant momenta, which is used to prove the quantized bulk magnetoelectric response of NLSMs with Z_{2} monopole charges under a T-breaking perturbation.

Dirac-Weyl Semimetal: Coexistence of Dirac and Weyl Fermions in Polar Hexagonal ABC Crystals.

We propose that the noncentrosymmetric LiGaGe-type hexagonal ABC crystal SrHgPb realizes a new type of topological semimetal that hosts both Dirac and Weyl points in momentum space. The symmetry-protected Dirac points arise due to a band inversion and are located on the sixfold rotation z axis, whereas the six pairs of Weyl points related by sixfold symmetry are located on the perpendicular k_{z}=0 plane. By studying the electronic structure as a function of the buckling of the HgPb layer, which is the origin of inversion symmetry breaking, we establish that the coexistence of Dirac and Weyl fermions defines a phase separating two topologically distinct Dirac semimetals. These two Dirac semimetals are distinguished by the Z_{2} index of the k_{z}=0 plane and the corresponding presence or absence of 2D Dirac fermions on side surfaces. We formalize our first-principles calculations by deriving and studying a low-energy model Hamiltonian describing the Dirac-Weyl semimetal phase. We conclude by proposing several other materials in the noncentrosymmetric ABC material class, in particular SrHgSn and CaHgSn, as candidates for realizing the Dirac-Weyl semimetal.

Strain-Induced Ferroelectric Topological Insulator.

Ferroelectricity and band topology are two extensively studied yet distinct properties of insulators. Nonetheless, their coexistence has never been observed in a single material. Using first-principles calculations, we demonstrate that a noncentrosymmetric perovskite structure of CsPbI3 allows for the simultaneous presence of ferroelectric and topological orders with appropriate strain engineering. Metallic topological surface states create an intrinsic short-circuit condition, helping stabilize bulk polarization. Exploring diverse structural phases of CsPbI3 under pressure, we identify that the key structural feature for achieving a ferroelectric topological insulator is to suppress PbI6 cage rotation in the perovskite structure, which could be obtained via strain engineering. Ferroelectric control over the density of topological surface states provides a new paradigm for device engineering, such as perfect-focusing Veselago lens and spin-selective electron collimator. Our results suggest that CsPbI3 is a simple model system for ferroelectric topological insulators, enabling future studies exploring the interplay between conventional symmetry-breaking and topological orders and their novel applications in electronics and spintronics.

Monolayer Single-Crystal 1T'-MoTe2 Grown by Chemical Vapor Deposition Exhibits Weak Antilocalization Effect.

Growth of transition metal dichalcogenide (TMD) monolayers is of interest due to their unique electrical and optical properties. Films in the 2H and 1T phases have been widely studied but monolayers of some 1T'-TMDs are predicted to be large-gap quantum spin Hall insulators, suitable for innovative transistor structures that can be switched via a topological phase transition rather than conventional carrier depletion [ Qian et al. Science 2014 , 346 , 1344 - 1347 ]. Here we detail a reproducible method for chemical vapor deposition of monolayer, single-crystal flakes of 1T'-MoTe2. Atomic force microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, and transmission electron microscopy confirm the composition and structure of MoTe2 flakes. Variable temperature magnetotransport shows weak antilocalization at low temperatures, an effect seen in topological insulators and evidence of strong spin-orbit coupling. Our approach provides a pathway to systematic investigation of monolayer, single-crystal 1T'-MoTe2 and implementation in next-generation nanoelectronic devices.

Two-Dimensional π-Conjugated Covalent-Organic Frameworks as Quantum Anomalous Hall Topological Insulators.

The quantum anomalous Hall (QAH) insulator is a novel topological state of matter characterized by a nonzero quantized Hall conductivity without an external magnetic field. Using first-principles calculations, we predict the QAH state in monolayers of covalent-organic frameworks based on the newly synthesized X_{3}(C_{18}H_{12}N_{6})_{2} structure where X represents 5d transition metal elements Ta, Re, and Ir. The π conjugation between X d_{xz} and d_{yz} orbitals, mediated by N p_{z} and C p_{z} orbitals, gives rise to a massive Dirac spectrum in momentum space with a band gap of up to 24 meV due to strong spin-orbit coupling. We show that the QAH state can appear by chemically engineering the exchange field and the Fermi level in the monolayer structure, resulting in nonzero Chern numbers. Our results suggest a reliable pathway toward the realization of a QAH phase at temperatures between 100 K and room temperature in covalent-organic frameworks.

Double Dirac Semimetals in Three Dimensions.

We study a class of Dirac semimetals that feature an eightfold-degenerate double Dirac point. We show that 7 of the 230 space groups can host such Dirac points and argue that they all generically display linear dispersion. We introduce an explicit tight-binding model for space groups 130 and 135. Space group 135 can host an intrinsic double Dirac semimetal with no additional states at the Fermi energy. This defines a symmetry-protected topological critical point, and we show that a uniaxial compressive strain applied in different directions leads to topologically distinct insulating phases. In addition, the double Dirac semimetal can accommodate topological line defects that bind helical modes. Connections are made to theories of strongly interacting filling-enforced semimetals, and potential materials realizations are discussed.

Dirac Line Nodes in Inversion-Symmetric Crystals.

We propose and characterize a new Z2 class of topological semimetals with a vanishing spin-orbit interaction. The proposed topological semimetals are characterized by the presence of bulk one-dimensional (1D) Dirac line nodes (DLNs) and two-dimensional (2D) nearly flat surface states, protected by inversion and time-reversal symmetries. We develop the Z2 invariants dictating the presence of DLNs based on parity eigenvalues at the parity-invariant points in reciprocal space. Moreover, using first-principles calculations, we predict DLNs to occur in Cu_{3}N near the Fermi energy by doping nonmagnetic transition metal atoms, such as Zn and Pd, with the 2D surface states emerging in the projected interior of the DLNs. This Letter includes a brief discussion of the effects of spin-orbit interactions and symmetry breaking as well as comments on experimental implications.

Layered Topological Crystalline Insulators.

Topological crystalline insulators (TCIs) are insulating materials whose topological property relies on generic crystalline symmetries. Based on first-principles calculations, we study a three-dimensional (3D) crystal constructed by stacking two-dimensional TCI layers. Depending on the interlayer interaction, the layered crystal can realize diverse 3D topological phases characterized by two mirror Chern numbers (MCNs) (µ1,µ2) defined on inequivalent mirror-invariant planes in the Brillouin zone. As an example, we demonstrate that new TCI phases can be realized in layered materials such as a PbSe (001) monolayer/h-BN heterostructure and can be tuned by mechanical strain. Our results shed light on the role of the MCNs on inequivalent mirror-symmetric planes in reciprocal space and open new possibilities for finding new topological materials.

Applying dynamic priority scheduling scheme to static systems of pinwheel task model in power-aware scheduling.

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10-80% over the existing algorithms.

Absorption Distribution Metabolism Excretion and Toxicity Property Prediction Utilizing a Pre-Trained Natural Language Processing Model and Its Applications in Early-Stage Drug Development.

Machine learning techniques are extensively employed in drug discovery, with a significant focus on developing QSAR models that interpret the structural information of potential drugs. In this study, the pre-trained natural language processing (NLP) model, ChemBERTa, was utilized in the drug discovery process. We proposed and evaluated four core model architectures as follows: deep neural network (DNN), encoder, concatenation (concat), and pipe. The DNN model processes physicochemical properties as input, while the encoder model leverages the simplified molecular input line entry system (SMILES) along with NLP techniques. The latter two models, concat and pipe, incorporate both SMILES and physicochemical properties, operating in parallel and with sequential manners, respectively. We collected 5238 entries from DrugBank, including their physicochemical properties and absorption, distribution, metabolism, excretion, and toxicity (ADMET) features. The models' performance was assessed by the area under the receiver operating characteristic curve (AUROC), with the DNN, encoder, concat, and pipe models achieved 62.4%, 76.0%, 74.9%, and 68.2%, respectively. In a separate test with 84 experimental microsomal stability datasets, the AUROC scores for external data were 78% for DNN, 44% for the encoder, and 50% for concat, indicating that the DNN model had superior predictive capabilities for new data. This suggests that models based on structural information may require further optimization or alternative tokenization strategies. The application of natural language processing techniques to pharmaceutical challenges has demonstrated promising results, highlighting the need for more extensive data to enhance model generalization.

Supervised chemical graph mining improves drug-induced liver injury prediction.

Drug-induced liver injury (DILI) is the main cause of drug failure in clinical trials. The characterization of toxic compounds in terms of chemical structure is important because compounds can be metabolized to toxic substances in the liver. Traditional machine learning approaches have had limited success in predicting DILI, and emerging deep graph neural network (GNN) models are yet powerful enough to predict DILI. In this study, we developed a completely different approach, supervised subgraph mining (SSM), a strategy to mine explicit subgraph features by iteratively updating individual graph transitions to maximize DILI fidelity. Our method outperformed previous methods including state-of-the-art GNN tools in classifying DILI on two different datasets: DILIst and TDC-benchmark. We also combined the subgraph features by using SMARTS-based frequent structural pattern matching and associated them with drugs' ATC code.

Monolayer Kagome metals AV3Sb5.

Recently, layered kagome metals AV3Sb5 (A = K, Rb, and Cs) have emerged as a fertile platform for exploring frustrated geometry, correlations, and topology. Here, using first-principles and mean-field calculations, we demonstrate that AV3Sb5 can crystallize in a mono-layered form, revealing a range of properties that render the system unique. Most importantly, the two-dimensional monolayer preserves intrinsically different symmetries from the three-dimensional layered bulk, enforced by stoichiometry. Consequently, the van Hove singularities, logarithmic divergences of the electronic density of states, are enriched, leading to a variety of competing instabilities such as doublets of charge density waves and s- and d-wave superconductivity. We show that the competition between orders can be fine-tuned in the monolayer via electron-filling of the van Hove singularities. Thus, our results suggest the monolayer kagome metal AV3Sb5 as a promising platform for designer quantum phases.

A Brief Review of Transparent Conducting Oxides (TCO): The Influence of Different Deposition Techniques on the Efficiency of Solar Cells.

Global-warming-induced climate changes and socioeconomic issues increasingly stimulate reviews of renewable energy. Among energy-generation devices, solar cells are often considered as renewable sources of energy. Lately, transparent conducting oxides (TCOs) are playing a significant role as back/front contact electrodes in silicon heterojunction solar cells (SHJ SCs). In particular, the optimized Sn-doped In2O3 (ITO) has served as a capable TCO material to improve the efficiency of SHJ SCs, due to excellent physicochemical properties such as high transmittance, electrical conductivity, mobility, bandgap, and a low refractive index. The doped-ITO thin films had promising characteristics and helped in promoting the efficiency of SHJ SCs. Further, SHJ technology, together with an interdigitated back contact structure, achieved an outstanding efficiency of 26.7%. The present article discusses the deposition of TCO films by various techniques, parameters affecting TCO properties, characteristics of doped and undoped TCO materials, and their influence on SHJ SC efficiency, based on a review of ongoing research and development activities.

Spectroscopic ellipsometry analysis of amorphous silicon thin films for Si-nanocrystals.

Hydrogenated amorphous and nano-crocrystalline silicon thin films were grown by very-high-frequency plasma-enhanced chemical vapor deposition (VHF-PECVD, 60 MHz). In this paper, we report the defects of nano-crystallites embedded in an amorphous matrix of hydrogenated silicon alloy (a-Si:H) thin film as investigated by spectroscopic ellipsometry (SE). The peak intensity and position of the imaginary part of the dielectric constant (epsilon2) as a function of the energy show various material states, including a-Si:H (3.5 eV) and nc-Si (4.2 eV), along with the absorption coefficient, thickness, optical gap, and the characteristics of the defects. The ratio of the characteristic Raman features, the TA/LO and LA/LO ratio, is related to the defect states in the films. It was correlated to the SE data. Following this, we look into the systematic change in the crystallinity of the film from the SE results. Quantized crystallinity values from the SE data show good agreement by more than 88.75% with the crystallinity information obtained through Raman spectroscopy.

Enhanced luminescence of Cu-In-S nanocrystals by surface modification.

We have synthesized highly luminescent Cu-In-S nanocrystals by heating the mixture of metal carboxylates and alkylthiol under inert atmosphere. We modified the surface of CIS nanocrystals with zinc carboxylate and subsequent injection of alkylthiol. As a result of the surface modification, highly luminescent CIS@ZnS core/shell nanocrystals were synthesized. The luminescence quantum yield (QY) of best CIS@ZnS nanocrystals was above 50%, which is more than 10 times higher than the initial QY of CIS nanocrystals before surface modification (QY = 3%). Detailed study on the luminescence mechanism implies that etching of the surface of nanocrystals by dissociated carboxylate group (CH3COO-) and formation of epitaxial shell by Zn with sulfur from alkylthiol efficiently removed the surface defects which are major non-radiative recombination sites in semiconductor nanocrystals. In this study, we developed a novel surface modification route for monodispersed highly luminescent Cu-In-S nanocrystals with less toxic and highly stable precursors.