Nature Search

Genetic algorithms for computational materials discovery accelerated by machine learning

Paul C. Jennings
Steen Lysgaard
Thomas Bligaard
ResearchOpen Access10 Apr 2019
npj Computational Materials

Volume: 5, P: 1-6
Ternary ruthenium complex hydrides for ammonia synthesis via the associative mechanism

The mechanism of ammonia synthesis on traditional iron or ruthenium catalysts features a high energetic span. Here, the authors introduce ternary ruthenium complex hydrides of lithium and barium that can activate dinitrogen via a lower-energy path, resulting in the highly efficient production of ammonia under milder conditions.

Qianru Wang
Jaysree Pan
Ping Chen
Research18 Nov 2021
Nature Catalysis

Volume: 4, P: 959-967
Cation insertion to break the activity/stability relationship for highly active oxygen evolution reaction catalyst

Renewable hydrogen production from water will require understanding and improving the oxygen evolution reaction (OER) on catalyst surfaces. Here, authors report α-Li₂IrO₃ to transform into a hydrated birnessite phase under OER conditions that exhibits enhanced OER performances and durabilities.

Chunzhen Yang
Gwenaëlle Rousse
Alexis Grimaud
ResearchOpen Access13 Mar 2020
Nature Communications

Volume: 11, P: 1-10
Operando identification of site-dependent water oxidation activity on ruthenium dioxide single-crystal surfaces

Understanding the nature of active sites is central to controlling the activity of a given catalyst. This work combines operando characterization and computational techniques to examine the oxygen evolution reaction mechanism on RuO₂ surfaces.

Reshma R. Rao
Manuel J. Kolb
Yang Shao-Horn
Research11 May 2020
Nature Catalysis

Volume: 3, P: 516-525
MultiXC-QM9: Large dataset of molecular and reaction energies from multi-level quantum chemical methods

Surajit Nandi
Tejs Vegge
Arghya Bhowmik
ResearchOpen Access08 Nov 2023
Scientific Data

Volume: 10, P: 1-6
Science acceleration and accessibility with self-driving labs

Collaborative self-diving research is crucial to research acceleration amidst ever more complex problems. Here, authors identify the key challenges to the dual cultivation of centralised self-driving user facilities and networks of self-driving labs.

Richard B. Canty
Jeffrey A. Bennett
Milad Abolhasani
ReviewsOpen Access24 Apr 2025
Nature Communications

Volume: 16, P: 1-11
Rapid mapping of alloy surface phase diagrams via Bayesian evolutionary multitasking

Shuang Han
Steen Lysgaard
Heine Anton Hansen
ResearchOpen Access10 Aug 2023
npj Computational Materials

Volume: 9, P: 1-14
Unfolding the structural stability of nanoalloys via symmetry-constrained genetic algorithm and neural network potential

Shuang Han
Giovanni Barcaro
Heine Anton Hansen
ResearchOpen Access01 Jun 2022
npj Computational Materials

Volume: 8, P: 1-11
Structural and chemical mechanisms governing stability of inorganic Janus nanotubes

Felix T. Bölle
August E. G. Mikkelsen
Ivano E. Castelli
ResearchOpen Access25 Mar 2021
npj Computational Materials

Volume: 7, P: 1-8
Computational framework for a systematic investigation of anionic redox process in Li-rich compounds

Alexander Sougaard Tygesen
Jin Hyun Chang
Juan Maria García-Lastra
ResearchOpen Access29 May 2020
npj Computational Materials

Volume: 6, P: 1-9
CALiSol-23: Experimental electrolyte conductivity data for various Li-salts and solvent combinations

Paolo de Blasio
Jonas Elsborg
Arghya Bhowmik
ResearchOpen Access10 Jul 2024
Scientific Data

Volume: 11, P: 1-11
Transition1x - a dataset for building generalizable reactive machine learning potentials

Mathias Schreiner
Arghya Bhowmik
Ole Winther
ResearchOpen Access24 Dec 2022
Scientific Data

Volume: 9, P: 1-9

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