4.8 Article

Chemical hardness-driven interpretable machine learning approach for rapid search of photocatalysts

Related references

Note: Only part of the references are listed.
Article Chemistry, Physical

Anisotropic Interlayer Exciton in GeSe/SnS van der Waals Heterostructure

Nikhilesh Maity et al.

Summary: This study demonstrates the generation of linearly polarized, anisotropic intra- and interlayer excitonic bound states in the transition metal monochalcogenide (TMC) GeSe/SnS van der Waals heterostructure, showing dramatic variation in excitonic energies and optical absorption spectrum under compressive/tensile biaxial strain. The changes in excitonic energies and optical band gap are attributed to the shift in effective dielectric constant and band dispersion upon the application of biaxial strain, showing potential applications in optoelectronics and optical quantum computers.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2021)

Article Nanoscience & Nanotechnology

Exploring Two-Dimensional Materials Thermodynamic Stability via Machine Learning

Gabriel R. Schleder et al.

ACS APPLIED MATERIALS & INTERFACES (2020)

Article Chemistry, Physical

A Statistical Approach for the Rapid Prediction of Electron Relaxation Time Using Elemental Representatives

Madhubanti Mukherjee et al.

CHEMISTRY OF MATERIALS (2020)

Article Chemistry, Physical

A critical examination of compound stability predictions from machine-learned formation energies

Christopher J. Bartel et al.

NPJ COMPUTATIONAL MATERIALS (2020)

Article Chemistry, Physical

Predicting aqueous stability of solid with computed Pourbaix diagram using SCAN functional

Zhenbin Wang et al.

NPJ COMPUTATIONAL MATERIALS (2020)

Article Engineering, Manufacturing

Is Domain Knowledge Necessary for Machine Learning Materials Properties?

Ryan J. Murdock et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2020)

Article Computer Science, Artificial Intelligence

From local explanations to global understanding with explainable AI for trees

Scott M. Lundberg et al.

NATURE MACHINE INTELLIGENCE (2020)

Article Chemistry, Multidisciplinary

High-throughput computational screening for solid-state Li-ion conductors

Leonid Kahle et al.

ENERGY & ENVIRONMENTAL SCIENCE (2020)

Article Nanoscience & Nanotechnology

Energy, Phonon, and Dynamic Stability Criteria of Two-Dimensional Materials

Oleksandr I. Malyi et al.

ACS APPLIED MATERIALS & INTERFACES (2019)

Article Chemistry, Physical

Coordination corrected ab initio formation enthalpies

Rico Friedrich et al.

NPJ COMPUTATIONAL MATERIALS (2019)

Article Materials Science, Multidisciplinary

Two-dimensional photocatalyst design: A critical review of recent experimental and computational advances

Yunxuan Zhao et al.

Materials Today (2019)

Article Chemistry, Physical

Li-III-VI bilayers for efficient photocatalytic overall water splitting: the role of intrinsic electric field

Yingcai Fan et al.

JOURNAL OF MATERIALS CHEMISTRY A (2019)

Editorial Material Chemistry, Multidisciplinary

Introduction: 2D Materials Chemistry

Hua Zhang

CHEMICAL REVIEWS (2018)

Article Chemistry, Physical

Machine-Learning-Assisted Accurate Band Gap Predictions of Functionalized MXene

Arunkumar Chitteth Rajan et al.

CHEMISTRY OF MATERIALS (2018)

Article Materials Science, Multidisciplinary

Matminer: An open source toolkit for materials data mining

Logan Ward et al.

COMPUTATIONAL MATERIALS SCIENCE (2018)

Article Chemistry, Physical

C2N/WS2 van der Waals type-II heterostructure as a promising water splitting photocatalyst

Ritesh Kumar et al.

JOURNAL OF CATALYSIS (2018)

Review Materials Science, Multidisciplinary

The Computational 2D Materials Database: high-throughput modeling and discovery of atomically thin crystals

Sten Haastrup et al.

2D MATERIALS (2018)

Article Chemistry, Physical

Direct Z-Scheme Water Splitting Photocatalyst Based on Two-Dimensional Van Der Waals Heterostructures

Ruiqi Zhang et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2018)

Editorial Material Chemistry, Physical

How To Correctly Determine the Band Gap Energy of Modified Semiconductor Photocatalysts Based on UV-Vis Spectra

Patrycja Makula et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2018)

Article Materials Science, Multidisciplinary

Elastic properties of bulk and low-dimensional materials using van der Waals density functional

Kamal Choudhary et al.

PHYSICAL REVIEW B (2018)

Review Chemistry, Physical

Two-dimensional nanomaterials for photocatalytic CO2 reduction to solar fuels

Yong Chen et al.

SUSTAINABLE ENERGY & FUELS (2017)

Article Materials Science, Multidisciplinary

Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

Logan Ward et al.

PHYSICAL REVIEW B (2017)

Review Biochemistry & Molecular Biology

Photocatalytic Water SplittingThe Untamed Dream: A Review of Recent Advances

Tahereh Jafari et al.

MOLECULES (2016)

Review Chemistry, Multidisciplinary

Recent advances in 2D materials for photocatalysis

Bin Luo et al.

NANOSCALE (2016)

Article Chemistry, Physical

A general-purpose machine learning framework for predicting properties of inorganic materials

Logan Ward et al.

NPJ COMPUTATIONAL MATERIALS (2016)

Article Materials Science, Multidisciplinary

Theory-guided Machine learning in Materials science

Nicholas Wagner et al.

FRONTIERS IN MATERIALS (2016)

Article Chemistry, Physical

Computational 2D Materials Database: Electronic Structure of Transition-Metal Dichalcogenides and Oxides

Filip A. Rasmussen et al.

JOURNAL OF PHYSICAL CHEMISTRY C (2015)

Article Chemistry, Physical

Computational Screening of 2D Materials for Photocatalysis

Arunima K. Singh et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2015)

Article Chemistry, Physical

A new equation for calculation of chemical hardness of groups and molecules

Savas Kaya et al.

MOLECULAR PHYSICS (2015)

Article Materials Science, Multidisciplinary

Heats of formation of solids with error estimation: The mBEEF functional with and without fitted reference energies

Mohnish Pandey et al.

PHYSICAL REVIEW B (2015)

Article Chemistry, Multidisciplinary

Low temperature synthesis of ZrS2 nanoflakes and their catalytic activity

Yan Wen et al.

RSC ADVANCES (2015)

Article Chemistry, Physical

New Light-Harvesting Materials Using Accurate and Efficient Bandgap Calculations

Ivano E. Castelli et al.

ADVANCED ENERGY MATERIALS (2015)

Editorial Material Chemistry, Multidisciplinary

Mind the gap!

Jean-Luc Bredas

MATERIALS HORIZONS (2014)

Article Materials Science, Multidisciplinary

Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis

Shyue Ping Ong et al.

COMPUTATIONAL MATERIALS SCIENCE (2013)

Article Chemistry, Multidisciplinary

A Facile Band Alignment of Polymeric Carbon Nitride Semiconductors to Construct Isotype Heterojunctions

Jinshui Zhang et al.

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2012)

Article Chemistry, Multidisciplinary

New cubic perovskites for one- and two-photon water splitting using the computational materials repository

Ivano E. Castelli et al.

ENERGY & ENVIRONMENTAL SCIENCE (2012)

Review Chemistry, Physical

Semiconductor nanostructure-based photoelectrochemical water splitting: A brief review

Yongjing Lin et al.

CHEMICAL PHYSICS LETTERS (2011)

Article Chemistry, Physical

Calculation of Ionization Potential and Chemical Hardness: A Comparative Study of Different Methods

R. Shankar et al.

INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY (2009)

Article Physics, Applied

First-principles elastic constants of α- and θ-Al2O3

Shunli Shang et al.

APPLIED PHYSICS LETTERS (2007)

Article Chemistry, Physical

Efficiency of solar water splitting using semiconductor electrodes

A. B. Murphy et al.

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY (2006)

Article Materials Science, Multidisciplinary

Implementation and performance of the frequency-dependent GW method within the PAW framework

M. Shishkin et al.

PHYSICAL REVIEW B (2006)

Article Physics, Multidisciplinary

Quasiparticle self-consistent GW theory

M. van Schilfgaarde et al.

PHYSICAL REVIEW LETTERS (2006)

Article Computer Science, Artificial Intelligence

Extremely randomized trees

P Geurts et al.

MACHINE LEARNING (2006)