Thomas Bligaard - Catalysis

Author Information

Thomas Bligaard is affiliated with the SUNCAT Center for Interface Science and Catalysis, located at the SLAC National Accelerator Laboratory, Menlo Park, California. His research primarily focuses on catalysis and materials discovery, leveraging advanced computational techniques and machine learning methodologies to accelerate scientific discoveries.

Research Contributions

Thomas Bligaard has made significant contributions to the field of catalysis and materials science. His work spans various aspects of computational chemistry, including the development of machine learning models for local structure optimizations in surface science, the simulation of X-ray diffraction patterns for battery materials, and the use of autonomous intelligent agents for accelerated materials discovery. Notably, he has also contributed to the theory-aided discovery of metallic catalysts for selective propane dehydrogenation and the active learning-accelerated discovery of stable iridium oxide polymorphs for the oxygen evolution reaction.

Aliases

Thomas Bligaard is also known by the aliases T Bligaard and T. Bligaard.

Publication and Citation Metrics

Metric	Value
Citation Count	35,508
h-index	62
Paper Count	170

Publications:

MCML: Combining physical constraints with experimental data for a multi‐purpose meta‐generalized gradient approximation

DOI: 10.1002/jcc.26732

Year: 2021

Theory-Aided Discovery of Metallic Catalysts for Selective Propane Dehydrogenation to Propylene

DOI: 10.1021/ACSCATAL.0C05711

Year: 2021

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction

DOI: 10.1021/acs.chemmater.0c01894

Year: 2020

Autonomous intelligent agents for accelerated materials discovery

DOI: 10.1039/d0sc01101k

Year: 2020

Autonomous Intelligent Agents for Accelerated Materials Discovery

DOI: 10.26434/chemrxiv.11860104.v1

Year: 2020

Machine learning with bond information for local structure optimizations in surface science.

DOI: 10.1063/5.0033778

Year: 2020

DFT simulation of the X-ray diffraction pattern of aluminum-ion-intercalated graphite used as the cathode material of the aluminum-ion battery.

DOI: 10.1039/c9cp06394c

Year: 2020

Contributors

DOI: 10.1016/b978-0-08-102941-1.01002-6

Year: 2020

Autonomous Intelligent Agents for Accelerated Materials Discovery

DOI: 10.26434/chemrxiv.11860104

Year: 2020

Bayesian error estimation in density functional theory

DOI: 10.1016/b978-0-08-102941-1.00003-1

Year: 2020

What are the Challenges in Using Magnetic Catalysts?

How to Collect and Analyze Product Samples?

What does the award entail?

What is a Working Electrode?

What are the Types of Electronic Effects?

How to Ensure Volume Accuracy?

What are the Common Challenges in Drafting Patent Claims for Catalysis?

What is Stability in Aqueous Media?

What are the Objectives of the Audit?

How Can User Feedback Improve Catalysis UIs?

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