Computer simulations of deep eutectic solvents: Challenges, solutions, and perspectives

D Tolmachev, N Lukasheva, R Ramazanov… - International journal of …, 2022 - mdpi.com
Deep eutectic solvents (DESs) are one of the most rapidly evolving types of solvents,
appearing in a broad range of applications, such as nanotechnology, electrochemistry …

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

K Choudhary, KF Garrity, ACE Reid, B DeCost… - npj computational …, 2020 - nature.com
Abstract The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an
integrated infrastructure to accelerate materials discovery and design using density …

Autonomous reaction network exploration in homogeneous and heterogeneous catalysis

M Steiner, M Reiher - Topics in Catalysis, 2022 - Springer
Autonomous computations that rely on automated reaction network elucidation algorithms
may pave the way to make computational catalysis on a par with experimental research in …

Continuum-scale modelling of polymer blends using the Cahn–Hilliard equation: transport and thermodynamics

PK Inguva, PJ Walker, HW Yew, K Zhu, AJ Haslam… - Soft matter, 2021 - pubs.rsc.org
The Cahn–Hilliard equation is commonly used to study multi-component soft systems such
as polymer blends at continuum scales. We first systematically explore various features of …

JARVIS-Leaderboard: a large scale benchmark of materials design methods

K Choudhary, D Wines, K Li, KF Garrity… - npj Computational …, 2024 - nature.com
Lack of rigorous reproducibility and validation are significant hurdles for scientific
development across many fields. Materials science, in particular, encompasses a variety of …

Large scale benchmark of materials design methods

K Choudhary, D Wines, K Li, KF Garrity, V Gupta… - arXiv preprint arXiv …, 2023 - arxiv.org
Lack of rigorous reproducibility and validation are major hurdles for scientific development
across many fields. Materials science in particular encompasses a variety of experimental …

Phase field benchmark problems for nucleation

W Wu, D Montiel, JE Guyer, PW Voorhees… - Computational Materials …, 2021 - Elsevier
We present nucleation phase field model benchmark problems, expanding on our previous
benchmark problems on diffusion, precipitation, dendritic growth, linear elasticity, fluid flow …

Data needs and challenges for quantum dot devices automation

JP Zwolak, JM Taylor, RW Andrews, J Benson… - npj Quantum …, 2024 - nature.com
Gate-defined quantum dots are a promising candidate system for realizing scalable, coupled
qubit systems and serving as a fundamental building block for quantum computers …

Setting the standard for machine learning in phase field prediction: a benchmark dataset and baseline metrics

LH Rieger, K Zelič, I Mele, T Katrašnik, A Bhowmik - Scientific data, 2024 - nature.com
Phase field models are an important mesoscale method that serves as a bridge between the
atomic scale and the macroscale, used for modeling complex phenomena at the …

Data needs and challenges of quantum dot devices automation: Workshop report

JP Zwolak, JM Taylor, R Andrews, J Benson… - arXiv preprint arXiv …, 2023 - arxiv.org
Gate-defined quantum dots are a promising candidate system to realize scalable, coupled
qubit systems and serve as a fundamental building block for quantum computers. However …