Quantum materials are a class of exotic materials with special properties that are governed by rather than . Those properties — like , and unusual forms of magnetism — often originate in the tiny repeating patterns of atoms inside crystals, but through clever engineering they can be observed and controlled at a more human scale. Quantum materials are helping to power the quickly growing field of , and could find their way into future generations of energy-efficient electronics.��

Designing new materials from the atomic scale up, however, requires intense modeling and simulation. Some materials may appear ordinary when viewed as small clusters of atoms, yet reveal new and useful properties when their atomic building blocks repeat and interact over larger distances. Researchers must be able to accurately predict behaviors at large scales in order to find materials with practical applications — otherwise designing new materials is a slow and costly trial-and-error process.

In the past 50 years, supercomputers have helped materials scientists solve some of those thorny prediction problems, but two recent studies from the �������� demonstrate how newer computing techniques can help researchers sniff out promising quantum materials to pursue. , published June 2 in the Proceedings of the National Academy of Sciences, shows how researchers can use artificial intelligence to simulate dozens of sheets of atoms stacked in intricate patterns, a process that produces complex and potentially useful quantum behaviors. , published June 8 in Nature Communications, shows how quantum computers can create a self-improving design loop by discovering new materials that could themselves be components of future quantum computers.��

“What is exciting is that AI and quantum computing are beginning to change not just what problems we can solve, but how we do research,” said , a UW associate professor of materials science and engineering and the senior author of both studies.

These two new tools — AI and quantum computing — are complementary in that they each excel at a different kind of simulation problem. With the right training, an AI model can act as a fast and relatively inexpensive surrogate of a supercomputer, extrapolating the behavior of huge material systems from a relatively small dataset. Cao and collaborators used this approach to stack virtual sheets of atoms on top of one another over and over — a process that created completely new phenomena that were absent on a smaller scale, but would have been impractical to model by traditional supercomputing. From there, researchers can try to make the most promising materials in the lab to prove out the simulations.

Quantum computers, on the other hand, are essentially powered by the same quantum phenomena — like entanglement — that Cao and other materials researchers want to study. Such phenomena can be difficult to simulate using traditional computers or AI systems, but quantum computers are naturally suited to the task. In the study, Cao and his team used a quantum computer to study an exotic phase of matter known as a .��

Moving forward, Cao and his team plan to further build out their datasets and eventually develop models that can simulate a much wider range of materials. They also hope to combine their AI and quantum computing systems into a more powerful and flexible hybrid tool.

“The next step is to bring these tools together,” Cao said. “We can use AI to guide quantum simulations, and quantum computers to generate new data and insights that improve AI models.”

“We are at the start of a new era,” said , UW professor and chair of materials science and engineering and co-author of both studies. “Our field is fundamentally changing. Things that were literally impossible a couple of years ago are now becoming routine. And we are only beginning to see what AI and quantum computing will make possible for quantum materials.”

was led by , a UW doctoral student of materials science and engineering. was led by , a UW doctoral student of physics. A complete list of authors is included with the studies.

The authors acknowledge the support of Amazon and the Department of Energy.

For more information, contact Cao at tingcao@uw.edu.

The �������� is proud to announce that 56 faculty and researchers who completed their work while at UW have been named on the list from Clarivate.

The annual list identifies researchers who demonstrated significant influence in their chosen field or fields through the publication of multiple highly cited papers during the last decade. Their names are drawn from the publications that rank in the top 1% by citations for field and publication year in the .

Highly Cited Researchers demonstrate significant and broad influence in their fields of research. The total list includes 7,131 awards from more than 1,300 institutions in 60 countries and regions. This small fraction of the global researcher population contributes disproportionately to extending the frontiers of knowledge and contributing to innovations that make the world healthier, more sustainable and which drive societal impact, according to Clarivate.

The that determines the “who’s who” of influential researchers is drawn from data and analysis performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate.

The list below includes faculty and researchers whose primary affiliation is with the UW, Fred Hutch Cancer Center, and the Institute for Health Metrics and Evaluation.

Please note: Some of the people on the list are no longer with the UW and their current affiliation is noted. This list reflects initial data from Clarivate and may be updated.

Ivan Anishchenko (Vilya)

David Baker

William A. Banks

Gregory N. Bratman

Steven L. Brunton

Guozhong Cao

Ting Cao

Lauren Carter (Gates Medical Research Institute)

Helen Chu

David H. Cobden

Katharine H. D. Crawford

Riza M. Daza

Frank DiMaio

Kristie L. Ebi

Evan E. Eichler

Emmanuela Gakidou

David Ginger

Raphael Gottardo (CHUV)

Alexander L. Greninger

Simon I. Hay

Andrew Hill (Infinimmune)

Eric Huang

Michael C. Jensen (BrainChild)

Neil P.�� King

C. Dirk Keene

J. Nathan Kutz

Eric H. Larson

Aaron Lyon

Michael J. MacCoss

Brendan MacLean

C. M. Marcus

Julian D. Marshall

Ali Mokdad

Thomas J. Montine (Stanford)

Mohsen Naghavi

Marian L. Neuhouser

Julian D. Olden

Robert W. Palmatier

David Pigott

Hannah A. Pliner (Bristol Myers Squibb)

Ganesh Raghu

Stanley Riddell

Andrea Schietinger (Memorial Sloan Kettering Cancer Center)

Jay Shendure

M. Alejandra Tortorici

Troy R. Torgerson (Allen Institute)

Cole Trapnell

Katherine R. Tuttle

David Veesler

Theo Vos

Alexandra C. Walls (BioNTech SE)

Bryan J. Weiner

Di Xiao

Jie Xiao

Xiaodong Xu

Jihui Yang

The �������� is proud to announce that more than 40 faculty and researchers who completed their work while at UW have been named on the annual list from Clarivate.

The annual list identifies researchers who demonstrated significant influence in their chosen field or fields through the publication of multiple highly cited papers during the last decade. Their names are drawn from the publications that rank in the top 1% by citations for field and publication year in the Web of Science citation index.

The list of faculty and researchers whose primary affiliation is with the UW or with the Institute for Health Metrics and Evaluation who were acknowledged for their work includes:

David Baker

William A. Banks

Gregory N. Bratman

Steven L. Brunton

Guozhong Cao

William A. Catterall

Helen Chu

David H. Cobden

Katharine H.D. Crawford

Riza M. Daza

Frank DiMaio

Evan E. Eichler

Michael Gale Jr.

Raphael Gottardo

Allison J. Greaney

Alexander L. Greninger

Simon I. Hay

Celestia S. Higano

Neil P. King

James B. Leverenz

Charles M. Marcus

Philip Mease

Ali Mokdad

Thomas J. Montine*

Christopher J. L. Murray

Mohsen Naghavi

William S. Noble

Young-Jun Park

David M. Pigott

Stanley Riddell

Andrea Schietinger **

Jay Shendure

M. Alejandra Tortorici

Troy R. Torgerson***

Cole Trapnell

David Veesler

Theo Vos

Alexandra C. Walls****

Bryan J. Weiner

Spencer A. Wood

Sanfeng Wu

Di Xiao

Xiaodong Xu

The that determines the “who’s who” of influential researchers draws on the data and analysis performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based.

The full 2023 Highly Cited Researchers list and executive summary can be found online .

* now is at Stanford University.

** now is at Memorial Sloan Kettering Cancer Center.

*** now is at the Allen Institute.

**** now is at BoiNTech SE.

now is at Princeton University.

The �������� is proud to announce that 47 faculty and researchers who completed their work while at UW have been named on the annual list from Clarivate.

The highly anticipated annual list identifies researchers who demonstrated significant influence in their chosen field or fields through the publication of multiple highly cited papers during the last decade. Their names are drawn from the publications that rank in the top 1% by citations for field and publication year in the Web of Science citation index.

The list of faculty and researchers who were acknowledged for their work while at UW includes:

• David Baker
• Frank DiMaio
• William Sheffler
• Dr. Jay Shendure
• Cole Trapnell
• David Veesler
• Alexandra C. Walls*
• Philip Mease
• Dr. Christopher J. L. Murray
• Dr. Ganesh Raghu
• Dr. Stanley Riddell
• Alejandra Tortorici
• Dr. William A. Banks
• Gregory N. Bratman
• Steven L. Brunton
• Guozhong Cao
• William A. Catterall
• David H. Cobden
• Riza M. Daza
• Dr. E. Patchen Dellinger
• Dr. Janet A. Englund
• E. Erskine
• Michael Gale Jr.
• Raphael Gottardo
• Celestia S. Higano
• Neil P. King
• Ali Mokdad
• William S. Noble
• Julian D. Olden
• L. Patrick
• David L. Smith
• Dr. Piper Meigs Treuting
• Spencer A. Wood
• Jesse R. Zaneveld
• Ning Zheng
• Dr. Hans D. Ochs
• Simon I. Hay
• Evan E. Eichler
• Deborah A. Nickerson**
• John A. Stamatoyannopoulos***
• Dr. Thomas J. Montine****
• Di Xiao
• Xiaodong Xu
• Bryan J. Weiner
• Mohsen Naghavi
• Theo Vos
• David M. Pigott

The that determines the “who’s who” of influential researchers draws on the data and analysis performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based. This year Clarivate partnered with Retraction Watch and extended the qualitative analysis of the Highly Cited Researchers list, addressing increasing concerns over potential misconduct.

The full 2022 Highly Cited Researchers list and executive summary can be found online .

* now is at BioNTech SE.

** on Dec. 24, 2021.

*** now is at Altius.

**** now is at Stanford University.