Papers citing Machine Learning Directed Search for Ultraincompressible, Superhard Materials
Brgoch Superhard Materials Training Data
Figshare · 2018
Aria Mansouri Tehrani, Anton O. Oliynyk, Marcus E. Parry, Zeshan Rizvi, Samantha Couper, Lin, Feng, Lowell Miyagi, Taylor D. Sparks, Jakoah Brgoch, Hacking Materials
Read original paper ↗ ·Notizen aus der Chemie
Nachrichten aus der Chemie · 2018
Christine Beemelmanns, Guillaume Delaittre, Johanna Heine, Constantin Hoch, Ullrich Jahn, Stefan Knecht, Björn Meermann, Andreas Schnepf, Carl Christoph Tzschucke
Read original paper ↗ ·Extracting Knowledge from DFT: Experimental Band Gap Predictions Through Ensemble Learning
ChemRxiv · 2018
Taylor D. Sparks, Steven Kauwe, Taylor Welker
Read original paper ↗ ·Not Just Par for the Course: 73 Quaternary Germanides RE4M2XGe4 (RE = La–Nd, Sm, Gd–Tm, Lu; M = Mn–Ni; X = Ag, Cd) and the Search for Intermetallics with Low Thermal Conductivity
Inorganic Chemistry · 2018
Dong Zhang, Anton O. Oliynyk, Gabriel M. Duarte, Abishek K. Iyer, Leila Ghadbeigi, Steven K. Kauwe, Taylor D. Sparks, Arthur Mar
Read original paper ↗ ·Hard and superhard materials: A computational perspective
Journal of Solid State Chemistry · 2018
Aria Mansouri Tehrani, Jakoah Brgoch
Read original paper ↗ ·The vacancy ordering produces a new cubic monocarbide: ReC
Materials Today Physics · 2018
Yongcheng Liang, Jiong Yang, Lili Xi, C. Liu, G. Zhang, W. Zhang
Read original paper ↗ ·Prediction of Carbon Dioxide Adsorption via Deep Learning
Angewandte Chemie International Edition · 2018
Zihao Zhang, Jennifer Ann Schott, Miaomiao Liu, Hao Chen, Xiuyang Lü, Bobby G. Sumpter, Jie Fu, Sheng Dai
Read original paper ↗ ·Prediction of Carbon Dioxide Adsorption via Deep Learning
Angewandte Chemie · 2018
Zihao Zhang, Jennifer Ann Schott, Miaomiao Liu, Hao Chen, Xiuyang Lü, Bobby G. Sumpter, Jie Fu, Sheng Dai
Read original paper ↗ ·Emerging Investigators in Solid-State Inorganic Chemistry
Inorganic Chemistry · 2018
Susan E. Latturner, Julia Y. Chan
Read original paper ↗ ·A Study of the Utility of a Machine-Learning Approach Applied to the Prediction of Site Occupancy and New Members of the Half-Heusler Family
ERA: Education and Research Archive (University of Alberta) · 2019
Alexander S. Gzyl
Read original paper ↗ ·Designing promising molecules for organic solar cells via machine learning assisted virtual screening
Journal of Materials Chemistry A · 2019
Harikrishna Sahu, Feng Yang, Xiaobo Ye, Jing Ma, Wei‐Hai Fang, Haibo Ma
Read original paper ↗ ·Lattice strain and texture analysis of superhard Mo 0.9 W 1.1 BC and ReWC 0.8 via diamond anvil cell deformation
Journal of Materials Chemistry A · 2019
Marcus E. Parry, Samantha Couper, Aria Mansouri Tehrani, Anton O. Oliynyk, Jakoah Brgoch, Lowell Miyagi, Taylor D. Sparks
Read original paper ↗ ·Ternary and Quaternary Rare-Earth Transition-Metal Germanides
ERA: Education and Research Archive (University of Alberta) · 2019
Dong Zhang
Read original paper ↗ ·Finding the Right Bricks for Molecular Legos: A Data Mining Approach to Organic Semiconductor Design
Chemistry of Materials · 2019
Christian Künkel, Christoph Schober, Johannes T. Margraf, Karsten Reuter, Harald Oberhofer
Read original paper ↗ ·Data-Driven Studies of Li-Ion-Battery Materials
Crystals · 2019
Steven Kauwe, Trevor David Rhone, Taylor D. Sparks
Read original paper ↗ ·Machine Learning-Aided Design of Materials with Target Elastic Properties
The Journal of Physical Chemistry C · 2019
Shuming Zeng, Geng Li, Yinchang Zhao, Ruirui Wang, Jun Ni
Read original paper ↗ ·Paradigm shift in electron-based crystallography via machine learning
arXiv (Cornell University) · 2019
Kevin Kaufmann, Chaoyi Zhu, Alexander S. Rosengarten, Daniel Maryanovsky, Tyler Harrington, Eduardo Marin, Kenneth S. Vecchio
Read original paper ↗ ·From DFT to machine learning: recent approaches to materials science–a review
Journal of Physics Materials · 2019
Gabriel Ravanhani Schleder, A. C. M. Padilha, Carlos Mera Acosta, Marcio Costa, A. Fazzio
Read original paper ↗ ·Rocketsled: a software library for optimizing high-throughput computational searches
Journal of Physics Materials · 2019
Alexander Dunn, Julien Brenneck, Anubhav Jain
Read original paper ↗ ·Data-Mining for Processes in Chemistry, Materials, and Engineering
Processes · 2019
Hao Li, Zhien Zhang, Zhe-Ze Zhao
Read original paper ↗ ·Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
Chemistry of Materials · 2019
Chi Chen, Weike Ye, Yunxing Zuo, Zheng Chen, Shyue Ping Ong
Read original paper ↗ ·Synthesis and Characterization of Single-Phase Metal Dodecaboride Solid Solutions: Zr1–xYxB12 and Zr1–xUxB12
Journal of the American Chemical Society · 2019
Georgiy Akopov, Wai Han Mak, Dimitrios Koumoulis, Hang Yin, Bryan Owens‐Baird, Michael T. Yeung, Mit Muni, Shannon Lee, Inwhan Roh, Zachary C. Sobell, Paula L. Diaconescu, Reza Mohammadi, Kirill A. Kovnir, Richard B. Kaner
Read original paper ↗ ·Synthesis and characterization of WB2-WB3-B4C hard composites
International Journal of Refractory Metals and Hard Materials · 2019
Feng Zhao, Li-Xia Qiu, Zhanhui Ding, Yongfeng Li, Bin Yao, Wei Dong Shen, Quan Li, Pinwen Zhu
Read original paper ↗ ·Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system
Computational Materials Science · 2019
Ruirui Wang, Shuming Zeng, Xinming Wang, Jun Ni
Read original paper ↗ ·Fast and Accurate Artificial Neural Network Potential Model for MAPbI3 Perovskite Materials
ACS Omega · 2019
Hsin‐An Chen, Chun‐Wei Pao
Read original paper ↗ ·Rapid Discovery of Ferroelectric Photovoltaic Perovskites and Material Descriptors via Machine Learning
Small Methods · 2019
Shuaihua Lu, Qionghua Zhou, Liang Ma, Yilv Guo, Jinlan Wang
Read original paper ↗ ·Artificial intelligence for materials discovery
MRS Bulletin · 2019
Carla Pedro Gomes, Bart Selman, John M. Gregoire
Read original paper ↗ ·Single-Crystal Automated Refinement (SCAR): A Data-Driven Method for Determining Inorganic Structures
Inorganic Chemistry · 2019
Gayatri Viswanathan, Anton O. Oliynyk, Erin Antono, Julia Ling, Bryce Meredig, Jakoah Brgoch
Read original paper ↗ ·Atom table convolutional neural networks for an accurate prediction of compounds properties
npj Computational Materials · 2019
Shuming Zeng, Yinchang Zhao, Geng Li, Ruirui Wang, Xinming Wang, Jun Ni
Read original paper ↗ ·Recent advances and applications of machine learning in solid-state materials science
npj Computational Materials · 2019
Jonathan Schmidt, Mário R. G. Marques, Silvana Botti, Miguel A. L. Marques
Read original paper ↗ ·Atomic Substitution to Balance Hardness, Ductility, and Sustainability in Molybdenum Tungsten Borocarbide
Chemistry of Materials · 2019
Aria Mansouri Tehrani, Anton O. Oliynyk, Zeshan Rizvi, Sogol Lotfi, Marcus E. Parry, Taylor D. Sparks, Jakoah Brgoch
Read original paper ↗ ·Mechanism for unconventional nonlinear elasticity
Physical review. B./Physical review. B · 2019
Aria Mansouri Tehrani, Amber Lim, Jakoah Brgoch
Read original paper ↗ ·Machine Learning Optimization of p-Type Transparent Conducting Films
Chemistry of Materials · 2019
Lingfei Wei, Xiaojie Xu, Gurudayal Gurudayal, James Bullock, Joel W. Ager
Read original paper ↗ ·Structural, mechanical, and thermodynamic properties of R-3m ReB4 under high pressure
The European Physical Journal B · 2019
Jianli Ma, Yi-Long Wu, Zhifen Fu, Qun Wei, Zhangfu Yang, Juan Gao, Jianping Zhou
Read original paper ↗ ·Predicting superhard materials via a machine learning informed evolutionary structure search
Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) · 2019
Proserpio, D.M.
Read original paper ↗ ·Machine Learning Interatomic Potentials as Emerging Tools for Materials Science
Advanced Materials · 2019
Volker L. Deringer, Miguel A. Caro, Gábor Cśanyi
Read original paper ↗ ·Autonome Entdeckung in den chemischen Wissenschaften, Teil I: Fortschritt
Angewandte Chemie · 2019
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Read original paper ↗ ·Autonomous Discovery in the Chemical Sciences Part I: Progress
Angewandte Chemie International Edition · 2019
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Read original paper ↗ ·Virtual Issue on Machine-Learning Discoveries in Materials Science
Chemistry of Materials · 2019
Anton O. Oliynyk, Jillian M. Buriak
Read original paper ↗ ·Viewpoint: Atomic-Scale Design Protocols toward Energy, Electronic, Catalysis, and Sensing Applications
Inorganic Chemistry · 2019
Florian Belviso, Victor E. P. Claerbout, Aleix Comas‐Vives, Naresh S. Dalal, Feng-Ren Fan, Alessio Filippetti, Vincenzo Fiorentini, Lucas Foppa, Cesare Franchini, Benjamin Geisler, Luca M. Ghiringhelli, Axel Groß, Shunbo Hu, Jorge Íñiguez, Steven K. Kauwe, Janice L. Musfeldt, Paolo Nicolini, Rossitza Pentcheva, Tomáš Polcar, Wei Li Ren, Fabio Ricci, Francesco Ricci, Hüseyin Şener Şen, Jonathan Michael Skelton, Taylor D. Sparks, Alessandro Stroppa, Andrea Urru, Matthias Vandichel, P. Vavassori, Hua Wu, Ke Yang, Hong Jian Zhao, Danilo Puggioni, Remedios Cortese, Antonio Cammarata
Read original paper ↗ ·Machine learning and artificial neural network accelerated computational discoveries in materials science
Wiley Interdisciplinary Reviews Computational Molecular Science · 2019
Yang Hong, Bo Hou, Hengle Jiang, Jingchao Zhang
Read original paper ↗ ·Five High-Impact Research Areas in Machine Learning for Materials Science
Chemistry of Materials · 2019
Bryce Meredig
Read original paper ↗ ·The influence of high pressure on the structural stability, Vickers hardness and mechanical properties of Re and Ru dodecaborides
International Journal of Quantum Chemistry · 2019
Yong Pan, Yanlin Jia
Read original paper ↗ ·Role of W-site substitution on mechanical and electronic properties of cubic tungsten carbide
Journal of Physics Condensed Matter · 2019
Anu Maria Augustine, Ponniah Ravindran
Read original paper ↗ ·Evaluating Thermal Quenching Temperature in Eu 3+ -Substituted Oxide Phosphors via Machine Learning
ACS Applied Materials & Interfaces · 2019
Ya Zhuo, Shruti Hariyani, Edward Armijo, Zainab Abolade Lawson, Jakoah Brgoch
Read original paper ↗ ·Can machine learning find extraordinary materials?
Computational Materials Science · 2019
Steven K. Kauwe, Jake Graser, Ryan Murdock, Taylor D. Sparks
Read original paper ↗ ·Accurate predictions of aqueous solubility of drug molecules via the multilevel graph convolutional network (MGCN) and SchNet architectures
Physical Chemistry Chemical Physics · 2020
Peng Gao, Jie Zhang, Yuzhu Sun, Jianguo Yu
Read original paper ↗ ·Directly predicting limiting potentials from easily obtainable physical properties of graphene-supported single-atom electrocatalysts by machine learning
Journal of Materials Chemistry A · 2020
Shiru Lin, Haoxiang Xu, Yekun Wang, Xiao Cheng Zeng, Zhongfang Chen
Read original paper ↗ ·Graph convolutional neural networks with global attention for improved materials property prediction
Physical Chemistry Chemical Physics · 2020
Steph-Yves Louis, Yong Zhao, Alireza Nasiri, Xiran Wang, Yuqi Song, Fei Liu, Jianjun Hu
Read original paper ↗ ·Machine Learning Chemical Guidelines for Engineering Electronic Structures in Half-Heusler Thermoelectric Materials
Research · 2020
Maxwell Thomas Dylla, Alexander Dunn, Shashwat Anand, Anubhav Jain, Gerald Jeffrey Snyder
Read original paper ↗ ·