Simulated annealing
An optimization algorithm inspired by the metallurgical process of annealing, where slowly cooling a heated material allows it to settle into a low-energy, globally optimal state.
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Balancing autonomy and expertise in autonomous synthesis laboratories nature.com
Nature Computational Science, 2025. [All Versions]. Autonomous synthesis laboratories promise to streamline the plan–make–measure–analyze iteration loop. Here, the authors comment on the barriers in the field, the promise of a human on-the-loop approach, and strategies for…
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Human–machine collaboration for improving semiconductor process development nature.com
Nature, 2023. [All Versions]. [Nature News]. This work studies Bayesian optimization algorithms to investigate how artificial intelligence (AI) might decrease the cost of developing complex semiconductor chip processes. In particular, this work create a controlled virtual…
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Nature Communications, 2023. [All Versions]. [Project]. Advances in machine learning (ML) and automated experimentation are poised to vastly accelerate research in polymer science. Data representation is a critical aspect for enabling ML integration in research workflows, yet…
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Single-atom alloy catalysts designed by first-principles calculations and artificial intelligence nature.com
Nature Communications, 2021. [All Versions]. This paper addresses the problem of new Single-atom-alloy catalysts (SAACs) discovery by applying a compressed-sensing data-analytics approach parameterized with density-functional inputs.
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Simulation in Chemistry and Biochemistry dasher.wustl.edu
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Optimization github.com
Naming › Data Structures and Algorithms: “An optimization algorithm inspired by the metallurgical process of annealing, where slowly cooling a heated material allows it to settle into a low-energy, globally optimal state.”