Quantum materials for brain sciences and artificial intelligence

MRS Bulletin ◽  
2018 ◽  
Vol 43 (7) ◽  
pp. 534-540 ◽  
Author(s):  
Shriram Ramanathan
Keyword(s):  
Artificial Intelligence ◽  
Brain Sciences ◽  
Quantum Materials ◽  
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Artificial intelligence for materials discovery

MRS Bulletin ◽  
2019 ◽  
Vol 44 (7) ◽  
pp. 538-544 ◽  
Author(s):  
Carla P. Gomes ◽  
Bart Selman ◽  
John M. Gregoire
Keyword(s):  
Artificial Intelligence ◽  
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Abstract

scholarly journals New digital laboratories of experimental knowledge production: Artificial intelligence and education research

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Ben James Williamson
Keyword(s):  
Artificial Intelligence ◽  
Education Research ◽  
Knowledge Production ◽  
Data Science ◽  
Learning Science ◽  
Data Intensive ◽  
Education Data ◽  
Brain Sciences ◽  
Disciplinary Expertise ◽  
Scientific Expertise

Education data scientists, learning engineers and precision education specialists are new experts in knowledge production in educational research. By bringing together data science methodologies and advanced artificial intelligence (AI) systems with disciplinary expertise from the psychological, biological and brain sciences, they are building a new field of AI-based learning science. This article presents an examination of how education research is being remade as an experimental data-intensive science. AI is combining with learning science in new ‘digital laboratories’ where ownership over data, and power and authority over educational knowledge production, are being redistributed to research assemblages of computational machines and scientific expertise.

scholarly journals Medicine, neurosciences and interdisciplinarity

2017 ◽  
Vol 1 (1) ◽  
pp. 2514183X1771411
Author(s):  
Maurice Campagna
Keyword(s):  
Artificial Intelligence ◽  
Quantitative Description ◽  
Scientific Progress ◽  
Past Century ◽  
Brain Organization ◽  
Aging Society ◽  
The Past ◽  
Brain Sciences ◽  
The World ◽  
The One

In terms of fundamental, universal scientific progress in the area of “hard sciences,” the past century was the one of relativity, quantum mechanics, and solid state/surface physics, whereas the 21st century prospects a focus on genomics/life/brain sciences, computer sciences/artificial intelligence, climate, and extraplanetary research. Among these, neurosciences represent a meta-plane, where new tools and insights provide key contributions to revolutionizing our current understandings. Increasingly, we move toward a quantitative description of various neural phenomena as well as to a new understanding of the nervous system and brain organization/functioning in particular. All this is strongly influencing the way we see the world. From this process, finally yet importantly, we derive large benefits for the cure of diseases as well as the management of an aging society.

Quantum materials for thermoelectricity

MRS Bulletin ◽  
2018 ◽  
Vol 43 (3) ◽  
pp. 187-192 ◽  
Author(s):  
Johannes Gooth ◽  
Gabi Schierning ◽  
Claudia Felser ◽  
Kornelius Nielsch
Keyword(s):  
Quantum Materials ◽  
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scholarly journals Emergent quantum materials

MRS Bulletin ◽  
2020 ◽  
Vol 45 (5) ◽  
pp. 340-347 ◽  
Author(s):  
Chun Ning Lau ◽  
Fengnian Xia ◽  
Linyou Cao
Keyword(s):  
Quantum Materials ◽  
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scholarly journals Navigating Uncertain Environments: Multiscale Computation in Biological and Artificial Intelligence

2020 ◽  
Author(s):  
Ryan Badman ◽  
Thomas T. Hills ◽  
Rei Akaishi
Keyword(s):  
Artificial Intelligence ◽  
Full Article ◽  
Open Access ◽  
Peer Review ◽  
Uncertain Environments ◽  
Multiscale Computation ◽  
Brain Sciences ◽  
Dynamic Attention ◽  
The Brain

After significant expansion and revision of the original preprint content during peer review, the full article has passed peer review and can now be accessed (open access) at the Brain Sciences journal where it was accepted: https://www.mdpi.com/2076-3425/10/6/396 The title formally was "Navigating Uncertain Environments: Multiscale Computation in Biological and Artificial Intelligence", but is now "Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence " to reflect the changed content. We have uploaded a one page preview of the accepted revised manuscript on psyarxiv to replace the outdated preprint, follow the link above for the full article.

scholarly journals Artificial intelligence for search and discovery of quantum materials

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Valentin Stanev ◽  
Kamal Choudhary ◽  
Aaron Gilad Kusne ◽  
Johnpierre Paglione ◽  
Ichiro Takeuchi
Keyword(s):  
Artificial Intelligence ◽  
Particle Physics ◽  
Climate Science ◽  
Physical Models ◽  
Computational Techniques ◽  
Spin Liquids ◽  
Use Of Data ◽  
Rapid Construction ◽  
Materials Research ◽  
Quantum Materials

AbstractArtificial intelligence and machine learning are becoming indispensable tools in many areas of physics, including astrophysics, particle physics, and climate science. In the arena of quantum materials, the rise of new experimental and computational techniques has increased the volume and the speed with which data are collected, and artificial intelligence is poised to impact the exploration of new materials such as superconductors, spin liquids, and topological insulators. This review outlines how the use of data-driven approaches is changing the landscape of quantum materials research. From rapid construction and analysis of computational and experimental databases to implementing physical models as pathfinding guidelines for autonomous experiments, we show that artificial intelligence is already well on its way to becoming the lynchpin in the search and discovery of quantum materials.

scholarly journals Thermal transport for probing quantum materials

MRS Bulletin ◽  
2020 ◽  
Vol 45 (5) ◽  
pp. 348-356 ◽  
Author(s):  
Mingda Li ◽  
Gang Chen
Keyword(s):  
Thermal Transport ◽  
Quantum Materials ◽  
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scholarly journals Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics

2019 ◽  
Vol 9 (3) ◽  
pp. 821-838 ◽  
Author(s):  
Rama K. Vasudevan ◽  
Kamal Choudhary ◽  
Apurva Mehta ◽  
Ryan Smith ◽  
Gilad Kusne ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
High Throughput ◽  
Materials Science ◽  
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Abstract

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