ArticleProceedings of the National Academy of Sciences of the United States of America2024
Programming patchy particles for materials assembly design.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Nonequilibrium Acceleration and Time Forecasting of Cluster-Mediated Self-Assembly.Journal of chemical theory and computation · 2025Article
- Hierarchical self-assembly for high-yield addressable complexity at fixed conditions.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Emergence of Polymer-Networked Nanoparticle Structures as Primitive Neuromorphic Computing States.The journal of physical chemistry. A · 2025Article
- Reversible molecular simulation for training classical and machine-learning force fields.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Nonequilibrium Self-Assembly Control by the Stochastic Landscape Method.Journal of chemical information and modeling · 2025Article
- Flexible interaction patches lead to building blocks with fluctuating valency.Nature chemistry · 2025Article
- Coarse-grained modeling of DNA-protein interactions helps elucidate DNA compaction.Biophysical journal · 2024Article
- Machine learning meets physics: A two-way street.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Direct design of complex functional materials would revolutionize technologies ranging from printable organs to novel clean energy devices. However, even incremental steps toward designing functional materials have proven challenging. If the material is constructed from highly complex components, the design space of materials properties rapidly becomes too computationally expensive to search. On the other hand, very simple components such as uniform spherical particles are not powerful enough to capture rich functional behavior. Here, we introduce a differentiable materials design model with components that are simple enough to design yet powerful enough to capture complex materials properties: rigid bodies composed of spherical particles with directional interactions (patchy particles). We showcase the method with self-assembly designs ranging from open lattices to self-limiting clusters, all of which are notoriously challenging design goals to achieve using purely isotropic particles. By directly optimizing over the location and interaction of the patches on patchy particles using gradient descent, we dramatically reduce the computation time for finding the optimal building blocks.
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Registered trials
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