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Rechargeable Batteries of the Future—The State of the Art from a BATTERY 2030+ Perspective

Advanced energy materials, 2022-05, Vol.12 (17), p.n/a

2022

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Transition1x - a dataset for building generalizable reactive machine learning potentials

Scientific data, 2022-12, Vol.9 (1), p.779-9, Article 779

2022

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ArtiSAN: navigating the complexity of material structures with deep reinforcement learning

Machine learning: science and technology, 2024-09, Vol.5 (3), p.35043

2024

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MultiXC-QM9: Large dataset of molecular and reaction energies from multi-level quantum chemical methods

Scientific data, 2023-11, Vol.10 (1), p.783-783, Article 783

2023

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Role of CO as a Spectator in CO2 Electroreduction on RuO2

Journal of physical chemistry. C, 2017-08, Vol.121 (34), p.18333-18343

2017

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Descriptors and Thermodynamic Limitations of Electrocatalytic Carbon Dioxide Reduction on Rutile Oxide Surfaces

ChemSusChem, 2016-11, Vol.9 (22), p.3230-3243

2016

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Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids

npj computational materials, 2022-08, Vol.8 (1), p.1-10, Article 183

2022

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CALiSol-23: Experimental electrolyte conductivity data for various Li-salts and solvent combinations

Scientific data, 2024-07, Vol.11 (1), p.750-11, Article 750

2024

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Genetic algorithm-based re-optimization of the Schrock catalyst for dinitrogen fixation

PeerJ physical chemistry, 2023-12, Vol.5, p.e30, Article e30

2023

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Equivariant Graph-Representation-Based Actor–Critic Reinforcement Learning for Nanoparticle Design

Journal of chemical information and modeling, 2023-06, Vol.63 (12), p.3731-3741

2023

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Frequency- and temperature-dependent dielectric response in hybrid molecular beam epitaxy-grown BaSnO3 films

APL materials, 2018-06, Vol.6 (6), p.066107-066107-6

2018

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Reducing training data needs with minimal multilevel machine learning (M3L)

Machine learning: science and technology, 2024-06, Vol.5 (2), p.025058

2024

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AI Fast Track to Battery Fast Charge

Joule, 2020-04, Vol.4 (4), p.717-719

2020

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Sensitivity analysis methodology for battery degradation models

Electrochimica acta, 2023-01, Vol.439, p.141430, Article 141430

2023

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Alteration of Electronic Band Structure via a Metal–Semiconductor Interfacial Effect Enables High Faradaic Efficiency for Electrochemical Nitrogen Fixation

ACS nano, 2021-12, Vol.15 (12), p.20364-20376

2021

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Artificial Intelligence Applied to Battery Research: Hype or Reality?

Chemical reviews, 2022-06, Vol.122 (12), p.10899-10969

2022

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Synthesis of Cu/CeO2‑x Nanocrystalline Heterodimers with Interfacial Active Sites To Promote CO2 Electroreduction

ACS catalysis, 2019-06, Vol.9 (6), p.5035-5046

2019

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Neural network potentials for accelerated metadynamics of oxygen reduction kinetics at Au-water interfaces

Chemical science (Cambridge), 2023-04, Vol.14 (14), p.3913-3922

2023

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Temperature Dependent Reversible p–n–p Type Conduction Switching with Colossal Change in Thermopower of Semiconducting AgCuS

Journal of the American Chemical Society, 2014-09, Vol.136 (36), p.12712-12720

2014

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Computational Investigation of LiF Formation at Graphite–Electrolyte Interfaces

ACS applied materials & interfaces, 2024-06, Vol.16 (22), p.29347-29354

2024

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Advancing energy materials through high throughput experiments and computation

Journal of materials chemistry. A, Materials for energy and sustainability, 2024-09, Vol.12 (35), p.23122-23124

2024

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Modeling the Solid Electrolyte Interphase: Machine Learning as a Game Changer?

Advanced materials interfaces, 2022-03, Vol.9 (8), p.n/a

2022

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Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT

Journal of chemical information and modeling, 2022-10, Vol.62 (19), p.4727-4735

2022

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Role of CO as a Spectator in CO 2 Electroreduction on RuO 2

Journal of physical chemistry. C, 2017-08, Vol.121 (34), p.18333-18343

2017

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A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning

Energy Storage Materials, 2019-09, Vol.21, p.446-456

2019

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Rechargeable Batteries of the Future—The State of the Art from a BATTERY 2030+ Perspective

Transition1x - a dataset for building generalizable reactive machine learning potentials

ArtiSAN: navigating the complexity of material structures with deep reinforcement learning

MultiXC-QM9: Large dataset of molecular and reaction energies from multi-level quantum chemical methods

Role of CO as a Spectator in CO2 Electroreduction on RuO2

Descriptors and Thermodynamic Limitations of Electrocatalytic Carbon Dioxide Reduction on Rutile Oxide Surfaces

Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids

CALiSol-23: Experimental electrolyte conductivity data for various Li-salts and solvent combinations

Genetic algorithm-based re-optimization of the Schrock catalyst for dinitrogen fixation

Equivariant Graph-Representation-Based Actor–Critic Reinforcement Learning for Nanoparticle Design

Frequency- and temperature-dependent dielectric response in hybrid molecular beam epitaxy-grown BaSnO3 films

Reducing training data needs with minimal multilevel machine learning (M3L)

AI Fast Track to Battery Fast Charge

Sensitivity analysis methodology for battery degradation models

Alteration of Electronic Band Structure via a Metal–Semiconductor Interfacial Effect Enables High Faradaic Efficiency for Electrochemical Nitrogen Fixation

Artificial Intelligence Applied to Battery Research: Hype or Reality?

Synthesis of Cu/CeO2‑x Nanocrystalline Heterodimers with Interfacial Active Sites To Promote CO2 Electroreduction

Neural network potentials for accelerated metadynamics of oxygen reduction kinetics at Au-water interfaces

Temperature Dependent Reversible p–n–p Type Conduction Switching with Colossal Change in Thermopower of Semiconducting AgCuS

Computational Investigation of LiF Formation at Graphite–Electrolyte Interfaces

Advancing energy materials through high throughput experiments and computation

Modeling the Solid Electrolyte Interphase: Machine Learning as a Game Changer?

Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT

Role of CO as a Spectator in CO 2 Electroreduction on RuO 2

A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning

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