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Machine learning for electrocatalyst and photocatalyst design and discovery
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …
reducing the impact of global warming, and providing solutions to environmental pollution …
The 2021 room-temperature superconductivity roadmap
Designing materials with advanced functionalities is the main focus of contemporary solid-
state physics and chemistry. Research efforts worldwide are funneled into a few high-end …
state physics and chemistry. Research efforts worldwide are funneled into a few high-end …
Machine learning and the physical sciences
Machine learning (ML) encompasses a broad range of algorithms and modeling tools used
for a vast array of data processing tasks, which has entered most scientific disciplines in …
for a vast array of data processing tasks, which has entered most scientific disciplines in …
A critical review of machine learning of energy materials
Abstract Machine learning (ML) is rapidly revolutionizing many fields and is starting to
change landscapes for physics and chemistry. With its ability to solve complex tasks …
change landscapes for physics and chemistry. With its ability to solve complex tasks …
The physics of pair-density waves: cuprate superconductors and beyond
We review the physics of pair-density wave (PDW) superconductors. We begin with a
macroscopic description that emphasizes order induced by PDW states, such as charge …
macroscopic description that emphasizes order induced by PDW states, such as charge …
Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook
In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
traditional research paradigms in the era of artificial intelligence and automation. An …
Machine learning for quantum matter
J Carrasquilla - Advances in Physics: X, 2020 - Taylor & Francis
Quantum matter, the research field studying phases of matter whose properties are
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …
[HTML][HTML] The 2021 quantum materials roadmap
In recent years, the notion of'Quantum Materials' has emerged as a powerful unifying
concept across diverse fields of science and engineering, from condensed-matter and …
concept across diverse fields of science and engineering, from condensed-matter and …
Heterogeneity at multiple length scales in halide perovskite semiconductors
Materials with highly crystalline lattice structures and low defect concentrations have
classically been considered essential for high-performance optoelectronic devices …
classically been considered essential for high-performance optoelectronic devices …