953 citations · 3.5k across the 41 of their papers we have counts for
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Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes
Penelope Jones, Fabian Coupette, Andreas Härtel +1
Electrolytes play an important role in a plethora of applications ranging from energy storage to biomaterials. Notwithstanding this, the structure of concentrated electrolytes rema…
Automatic virtual voltage extraction of a 2x2 array of quantum dots with machine learning
Giovanni A. Oakes, Jingyu Duan, John J. L. Morton +3
Spin qubits in quantum dots are a compelling platform for fault-tolerant quantum computing due to the potential to fabricate dense two-dimensional arrays with nearest neighbour cou…
Investigating 3D Atomic Environments for Enhanced QSAR
William McCorkindale, Carl Poelking, Alpha A. Lee
Predicting bioactivity and physical properties of molecules is a longstanding challenge in drug design. Most approaches use molecular descriptors based on a 2D representation of mo…
Mechanistic Insight to the Chemical Treatments of Monolayer Transition Metal Disulfides for Photoluminescence Enhancement
Zhaojun Li, Hope Bretscher, Yunwei Zhang +5
There is a growing interest in obtaining high quality monolayer transition metal disulfides (TMDSs) for optoelectronic device applications. Surface chemical treatments using a rang…
Materials Graph Transformer predicts the outcomes of inorganic reactions with reliable uncertainties
Shreshth A. Malik, Rhys E. A. Goodall, Alpha A. Lee
A common bottleneck for materials discovery is synthesis. While recent methodological advances have resulted in major improvements in the ability to predicatively design novel mate…
Machine learnt approximations to the bridge function yield improved closures for the Ornstein-Zernike equation
Rhys E. A. Goodall, Alpha A. Lee
A key challenge for soft materials design and coarse-graining simulations is determining interaction potentials between components that give rise to desired condensed-phase structu…
Materials Informatics Reveals Unexplored Structure Space in Cuprate Superconductors
Rhys E. A. Goodall, Bonan Zhu, Judith L. MacManus-Driscoll +1
High-temperature superconducting cuprates have the potential to be transformative in a wide range of energy applications. In this work we analyse the corpus of historical data abou…