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| 1 | An electrostatic spectral neighbor analysis potential for lithium nitride显示文摘Machine-learned interatomic potentials based on local environment descriptors represent a transformative leap over traditional potentials based on rigid functional forms in terms of prediction accuracy.However,a challenge in their application to ionic systems is the treatment of long-ranged electrostatics.Here,we present a highly accurate electrostatic Spectral Neighbor Analysis Potential(eSNAP)for ionicα-Li3N,a prototypical lithium superionic conductor of interest as a solid electrolyte or coating for rechargeable lithium-ion batteries.We show that the optimized eSNAP model substantially outperforms traditional Coulomb–Buckingham potential in the prediction of energies and forces,as well as various properties,such as lattice constants,elastic constants,and phonon dispersion curves.We also demonstrate the application of eSNAP in long-time,large-scale Li diffusion studies in Li3N,providing atomistic insights into measures of concerted ionic motion(e.g.,the Haven ratio)and grain boundary diffusion.This work aims at providing an approach to developing quantum-accurate force fields for multi-component ionic systems under the SNAP formalism,enabling large-scale atomistic simulations for such systems. | Zhi Deng Chi Chen Xiang-Guo Li Shyue Ping Ong | 2019 | npj Computational Materials2019，，1： | 11 |
| 2 | Recent advances and applications of deep learning methods in materials science显示文摘Deep learning(DL)is one of the fastest-growing topics in materials data science,with rapidly emerging applications spanning atomistic,image-based,spectral,and textual data modalities.DL allows analysis of unstructured data and automated identification of features.The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular.In contrast,advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods.In this article,we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation,materials imaging,spectral analysis,and natural language processing.For each modality we discuss applications involving both theoretical and experimental data,typical modeling approaches with their strengths and limitations,and relevant publicly available software and datasets.We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations,challenges,and potential growth areas for DL methods in materials science. | Kamal Choudhary Brian DeCost Chi Chen Anubhav Jain Francesca Tavazza Ryan Cohn Cheol Woo Park Alok Choudhary Ankit Agrawal Simon J.L.Billinge Elizabeth Holm Shyue Ping Ong Chris Wolverton | 2022 | npj Computational Materials2022，，1： | 9 |
| 3 | Complex strengthening mechanisms in the NbMoTaW multiprincipal element alloy显示文摘Refractory multi-principal element alloys(MPEAs)have exceptional mechanical properties,including high strength-to-weight ratio and fracture toughness,at high temperatures.Here we elucidate the complex interplay between segregation,short-range order,and strengthening in the NbMoTaW MPEA through atomistic simulations with a highly accurate machine learning interatomic potential.In the single crystal MPEA,we find greatly reduced anisotropy in the critically resolved shear stress between screw and edge dislocations compared to the elemental metals.In the polycrystalline MPEA,we demonstrate that thermodynamically driven Nb segregation to the grain boundaries(GBs)and W enrichment within the grains intensifies the observed short-range order(SRO).The increased GB stability due to Nb enrichment reduces the von Mises strain,resulting in higher strength than a random solid solution MPEA.These results highlight the need to simultaneously tune GB composition and bulk SRO to tailor the mechanical properties of MPEAs. | Xiang-Guo Li Chi Chen Hui Zheng Yunxing Zuo Shyue Ping Ong | 2020 | npj Computational Materials2020，，1： | 4 |
| 4 | Automated generation and ensemble-learned matching of X-ray absorption spectra显示文摘X-ray absorption spectroscopy(XAS)is a widely used materials characterization technique to determine oxidation states,coordination environment,and other local atomic structure information.Analysis of XAS relies on comparison of measured spectra to reliable reference spectra.However,existing databases of XAS spectra are highly limited both in terms of the number of reference spectra available as well as the breadth of chemistry coverage.In this work,we report the development of XASdb,a large database of computed reference XAS,and an Ensemble-Learned Spectra IdEntification(ELSIE)algorithm for the matching of spectra.XASdb currently hosts more than 800,000 K-edge X-ray absorption near-edge spectra(XANES)for over 40,000 materials from the open-science Materials Project database.We discuss a high-throughput automation framework for FEFF calculations,built on robust,rigorously benchmarked parameters.FEFF is a computer program uses a real-space Green’s function approach to calculate X-ray absorption spectra.We will demonstrate that the ELSIE algorithm,which combines 33 weak“learners”comprising a set of preprocessing steps and a similarity metric,can achieve up to 84.2% accuracy in identifying the correct oxidation state and coordination environment of a test set of 19 K-edge XANES spectra encompassing a diverse range of chemistries and crystal structures.The XASdb with the ELSIE algorithm has been integrated into a web application in the Materials Project,providing an important new public resource for the analysis of XAS to all materials researchers.Finally,the ELSIE algorithm itself has been made available as part of veidt,an open source machine-learning library for materials science. | Chen Zheng Kiran Mathew Chi Chen Yiming Chen Hanmei Tang Alan Dozier Joshua J.Kas Fernando D.Vila John J.Rehr Louis F.J.Piper Kristin A.Persson Shyue Ping Ong | 2018 | npj Computational Materials2018，，1： | 3 |
| 5 | AtomSets as a hierarchical transfer learning framework for small and large materials datasets显示文摘Predicting properties from a material’s composition or structure is of great interest for materials design.Deep learning has recently garnered considerable interest in materials predictive tasks with low model errors when dealing with large materials data.However,deep learning models suffer in the small data regime that is common in materials science.Here we develop the AtomSets framework,which utilizes universal compositional and structural descriptors extracted from pre-trained graph network deep learning models with standard multi-layer perceptrons to achieve consistently high model accuracy for both small compositional data(<400)and large structural data(>130,000).The AtomSets models show lower errors than the graph network models at small data limits and other non-deep-learning models at large data limits.They also transfer better in a simulated materials discovery process where the targeted materials have property values out of the training data limits.The models require minimal domain knowledge inputs and are free from feature engineering.The presented AtomSets model framework can potentially accelerate machine learning-assisted materials design and discovery with less data restriction. | Chi Chen Shyue Ping Ong | 2021 | npj Computational Materials2021，，1： | 2 |
| 6 | Emodin induces apopto- sis in human lung adenocarcinama ceils through a reactiveoxygen species-dependent mitochondrial signaling pathway 显示文摘 | Su YT chang HL Shyue SK | 2005 | Biochem Pharmaco12005，70，2： | 1 |
| 7 | An efficient shock-capturing algorithm for compressible multicomponent problems显示文摘 | Shyue K M | 1998 | J Comput Phys1998，1，： | 1 |
| 8 | activation of endothelial nitric oxide synthase显示文摘 | Su KH Shyue SK Kou YR | 2011 | J Cell Physiol2011，226，12： | 1 |
| 9 | Emodin induces apoptosis in human lung adenocarcinoma cells through a reactive oxygen species- dependent mitochondrial signaling pathway 显示文摘 | Su YT Chang HL Shyue SK | 2005 | Biochem Pharmacol2005，70，2： | 1 |
| 10 | Adenovirus-mediated overexpression of catalase attenuates oxLDL-induced apoptosis in human aortic endothelial cells via AP-1 and C-Jun N-terminal kinase/extracellular signal-regulated kinase mitogen-activated protein kinase pathways显示文摘 | Lin S J Shyue S K Liu P L | 2004 | J Mol Cell Cardiol2004，36，1： | 1 |
| 11 | Emodin induces apoptosis in human lung adenocarcinorna cells through a reactive oxygen species-dependent mitochondrial signaling pathway 显示文摘 | Su YT Chang HL Shyue SK | 2005 | Bioehem Pharmacol2005，70，2： | 1 |
| 12 | Rapid label-free determination of ketamine in whole blood using secondary ion mass spectrometry 显示文摘 | Liao HY Chen JH Shyue JJ | 2015 | Talanta2015，143，： | 1 |
| 13 | Emodin Induces Apoptosis in Human Lung Adenocarcinoma Cells through a Reactive Oxygen Species-dependent Mitochondrial Signaling Pathway显示文摘 | Su Y T Chang H L Shyue S K | 2005 | Biochemical Pharmacology2005，70，： | 1 |
| 14 | Lineage differentiation-associated loss of adenoviral susceptibility and Coxsackie-adenovirus receptor expression in human mesenchymal stem cells显示文摘 | Hung S C Lu C Y Shyue S K | 2004 | Stem cells2004，22，7： | 1 |
| 15 | An efficient shock-capturing algorithm for compressible multicomponent problems显示文摘 | Shyue K M | 1998 | J Comput Phys1998，142，： | 1 |
| 16 | A mixture-energy-consistent six-equation two-phase numerical model for fluids with interfaces, cavitation and evaporation waves显示文摘 | Pelanti M Shyue K M | 2014 | Journal of Computational Physics2014，259，： | 1 |
| 17 | overexpression of catalase attenuates oxLDL-induced apoptosis in human aortic endothelial cells via AP-1 and C-Jun N-terminal kinase/extracellular signal-regulated kinase mitogen-activated protein kinase pathways 显示文摘 | Lin SJ Shyue SK Liu PL | 2004 | J Mol Cell Cardiol2004，36，1： | 1 |
| 18 | Superoxide dismutase inhibits the expression of vascular cell adhesion molecule-1 and intracellular cell adhesion molecule-1 induced by tumor necrosis factor-alpha in human endothelial cells through the JNK/p38 pathways显示文摘 | Lin SJ Shyue SK Hung YY | 2005 | Arterioscler Thromb Vasc Biol2005，25，： | 1 |
| 19 | Emodin induces apoptosis in human lung adenocarcinoma cells through a reactive oxygen speciesdependent mitochondrial signaling pathway显示文摘 | Su YT Chang HL Shyue SK | 2005 | Biochem Pharmacol2005，70，2： | 1 |
| 20 | Bcl-xL augmentation potentially reduces ischemia/reperfusion induced proximal and distal tubular apoptosis and autophagy 显示文摘 | Chien CT Shyue SK Lai MK | 2007 | Transplantation2007，84，9： | 1 |
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