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| 1 | Active learning for accelerated design of layered materials显示文摘Hetero-structures made from vertically stacked monolayers of transition metal dichalcogenides hold great potential for optoelectronic and thermoelectric devices.Discovery of the optimal layered material for specific applications necessitates the estimation of key material properties,such as electronic band structure and thermal transport coefficients.However,screening of material properties via brute force ab initio calculations of the entire material structure space exceeds the limits of current computing resources.Moreover,the functional dependence of material properties on the structures is often complicated,making simplistic statistical procedures for prediction difficult to employ without large amounts of data collection.Here,we present a Gaussian process regression model,which predicts material properties of an input hetero-structure,as well as an active learning model based on Bayesian optimization,which can efficiently discover the optimal hetero-structure using a minimal number of ab initio calculations.The electronic band gap,conduction/valence band dispersions,and thermoelectric performance are used as representative material properties for prediction and optimization.The Materials Project platform is used for electronic structure computation,while the BoltzTraP code is used to compute thermoelectric properties.Bayesian optimization is shown to significantly reduce the computational cost of discovering the optimal structure when compared with finding an optimal structure by building a regression model to predict material properties.The models can be used for predictions with respect to any material property and our software,including data preparation code based on the Python Materials Genomics(PyMatGen)library as well as python-based machine learning code,is available open source. | Lindsay Bassman Pankaj Rajak Rajiv K.Kalia Aiichiro Nakano Fei Sha Jifeng Sun David J.Singh Muratahan Aykol Patrick Huck Kristin Persson Priya Vashishta | 2018 | npj Computational Materials2018，，1： | 10 |
| 2 | Bismuth and antimony-based oxyhalides and chalcohalides as potential optoelectronic materials显示文摘In the last decade the ns^(2) cations(e.g.,Pb^(2+)and Sn^(2+))-based halides have emerged as one of the most exciting new classes of optoelectronic materials,as exemplified by for instance hybrid perovskite solar absorbers.These materials not only exhibit unprecedented performance in some cases,but they also appear to break new ground with their unexpected properties,such as extreme tolerance to defects.However,because of the relatively recent emergence of this class of materials,there remain many yet to be fully explored compounds.Here,we assess a series of bismuth/antimony oxyhalides and chalcohalides using consistent first principles methods to ascertain their properties and obtain trends.Based on these calculations,we identify a subset consisting of three types of compounds that may be promising as solar absorbers,transparent conductors,and radiation detectors.Their electronic structure,connection to the crystal geometry,and impact on band-edge dispersion and carrier effective mass are discussed. | Zhao Ran Xinjiang Wang Yuwei Li Dongwen Yang Xin-Gang Zhao Koushik Biswas David J.Singh Lijun Zhang | 2018 | npj Computational Materials2018，，1： | 3 |
| 3 | MatHub-2d:二维材料输运数据库及其高迁移率二维半导体材料高通量筛选应用显示文摘近些年来二维材料因其独特的物理化学性质引起了广泛关注.载流子迁移率是材料在电子设备应用中最重要的特性之一.在本文中,我们介绍了如何通过高通量计算筛选来发现高迁移率二维半导体材料.基于最近开发的MatHub-2d数据库(包含约1900个二维材料的结构信息及其第一性原理计算结果),以带隙、磁性、弹性模量和形变势作为搜索标准,通过初步筛选,得到133个候选者.对这些体系,我们使用形变势方法和玻尔兹曼输运理论预测了迁移率.最终,我们预测19种二维材料在室温下(300 K)具有高迁移率(>10^(3)cm^(-2)V^(-1)s^(-1))和良好的稳定性.这些材料高迁移率的来源主要是较小的形变势常数、较大的弹性模量,以及较小的有效质量.其中有两种类型的化合物值得关注,BX(X=P,As,Sb)和ZO_(2)(Z=Ge,Sn,Pb),它们具有面内各向同性高迁移率.BX中“flower-like”化学键有利于p型和n型电输运,而Z-O反键态是ZO_(2)型二维材料良好电子传导的原因.除了这些二维材料,Si_(2)P_(2)、Ga_(2)O_(2)、Ge_(2)N_(2)等同样也表现出高的电子迁移率.这些高迁移率二维材料在新型半导体电子器件中具有潜在的应用前景. | 姚明佳 计嘉琳 李鑫 朱振宇 葛军饴 David J.Singh 奚晋扬 杨炯 张文清 | 2023 | Science China Materials2023，66，7： | 1 |
| 4 | Defect-mediated Rashba engineering for optimizing electrical transport in thermoelectric BiTeI显示文摘The Rashba effect plays a vital role in electronic structures and related functional properties.The strength of the Rashba effect can be measured by the Rashba parameter α_(R);it is desirable to manipulate α_(R) to control the functional properties.The current work illustrates how α_(R) can be systematically tuned by doping,taking BiTeI as an example. | Xin Li Ye Sheng Lihua Wu Shunbo Hu Jiong Yang David J.Singh Jihui Yang Wenqing Zhang | 2020 | npj Computational Materials2020，，1： | 0 |
| 5 | Search for potential K ion battery cathodes by first principles显示文摘An important challenge facing K-ion batteries lies in exploring earth-abundant and safe cathode materials that can provide high capacity with high migration rate of K ions.Here,we propose a simple and efficient method for searching potential K cathode materials with first principles calculations.Our screening is based on combinations of weight capacity,K ion occupation ratio,volume change per K,and valence limit.With this screening method we predicted a series of potential K ions cathodes with favorable electrochemical performance,such as K_(2)VPO_(4)CO_(3)-like structures with 1 D diffusion channels,3 D channel structures K_(2)CoSiO_(4),layered materials KCoO_(2),KCrO_(2),KVF_(4) and K_(5)V_(3)F_(14),and others.These potential cathodes have small volume changes,suitable voltage,and high capacity,with small diffusion barriers.They may be useful in K-ion batteries with high energy density and rate performance. | Kaining Li Xiaofeng Fan David J.Singh WTZheng | 2021 | Journal of Energy Chemistry2021，30，3： | 0 |
| 6 | Disorder and Itinerant Magnetism in Full Heusler Pd_(2)TiIn显示文摘We report electronic and magnetic properties of full Heusler Pd_(2)TiIn based on first principles calculations.This compound has been variously characterized as magnetic or non-magnetic.We use first principles calculations with accurate methods to reexamine this issue.We find that ideal ordered Heusler Pd_(2)TiIn remains non-magnetic,in accord with prior work.However,we do find that it is possible to explain the magnetism seen in experiments through disorder and in particular we find that site disorder can lead to moment formation in this compound.In addition,we find an alternative low energy cubic crystal structure,which will be of interest to explore experimentally. | 秦冠华 任伟 David J.Singh 雷兵华 | 2021 | Chinese Physics Letters2021，38，1： | 0 |
| 7 | High-throughput deformation potential and electrical transport calculations显示文摘The deformation potential plays an important role in electrical transport properties, but in the context of high-throughputsearches requires a consistent and readily computable reference level. Here, we design a high-throughput method forcalculating the deformation potential for semiconductors in the MatHub-3d database. The deformation potential is obtainedfrom the volume-dependent band edge (valence band maximum and conduction band minimum) variations with respect tothe reference level. In order to adapt the calculation of reference level to a high-throughput manner, the average value of thefirst valence electron energy band associated with each compound is used as the reference level. Deformation potentials for11,993 materials are calculated using the above-mentioned method. By considering the calculated deformation potentials,electronic structures, and bulk moduli, 9957 compounds with converged electrical transport properties are obtained. 332promising p-type thermoelectric materials, and 321 n-type entries are then proposed. Among them, 156 compounds arescreened to having both potentially good n- and p-type thermoelectric transport properties. The band structures and chemicalbonding information for several typical compounds are further presented to reveal favorable band and bonding features forthermoelectrics. | Yeqing Jin Xiangdong Wang Mingjia Yao Di Qiu David J.Singh Jinyang Xi Jiong Yang Lili Xi | 2023 | npj Computational Materials2023，，1： | 0 |
| 8 | Atomic Dispersed Hetero‑Pairs for Enhanced Electrocatalytic CO_(2)Reduction显示文摘Electrochemical carbon dioxide reduction reaction(CO_(2)RR)involves a variety of intermediates with highly correlated reaction and ad-desorption energies,hindering optimization of the catalytic activity.For example,increasing the binding of the*COOH to the active site will generally increase the*CO desorption energy.Breaking this relationship may be expected to dramatically improve the intrinsic activity of CO_(2)RR,but remains an unsolved challenge.Herein,we addressed this conundrum by constructing a unique atomic dispersed hetero-pair consisting of Mo-Fe di-atoms anchored on N-doped carbon carrier.This system shows an unprecedented CO_(2)RR intrinsic activity with TOF of 3336 h−1,high selectivity toward CO production,Faradaic efficiency of 95.96%at−0.60 V and excellent stability.Theoretical calculations show that the Mo-Fe diatomic sites increased the*COOH intermediate adsorption energy by bridging adsorption of*COOH intermediates.At the same time,d-d orbital coupling in the Mo-Fe di-atom results in electron delocalization and facilitates desorption of*CO intermediates.Thus,the undesirable correlation between these steps is broken.This work provides a promising approach,specifically the use of di-atoms,for breaking unfavorable relationships based on understanding of the catalytic mechanisms at the atomic scale. | Zhaoyong Jin Meiqi Yang Yilong Dong Xingcheng Ma Ying Wang Jiandong Wu Jinchang Fan Dewen Wang Rongshen Xi Xiao Zhao Tianyi Xu Jingxiang Zhao Lei Zhang David J.Singh Weitao Zheng Xiaoqiang Cui | 2024 | Nano-Micro Letters2024，16，1： | 0 |
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