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RESEARCH PAPER · Physical Review Letters · 2021

Neuroevolutionary Learning of Particles and Protocols for Self-Assembly

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20 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

Neuroevolutionary Learning of Particles and Protocols for Self-AssemblyOriginalDeposition control of model glasses with surface-mediated orientational order1Machine learning-based approach: global trends, research directions, and regulatory standpoints373A simple solution to the problem of self-assembling cubic diamond crystals22SAT-assembly: a new approach for designing self-assembling systems27Low-dissipation self-assembly protocols of active sticky particles3Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction82Designing the Self-Assembly of Arbitrary Shapes Using Minimal Complexity Building Blocks35Two-step nucleation in a binary mixture of patchy particles6Novelty Search for Neuroevolutionary Reinforcement Learning of Deceptive Systems: An Application to Control of Colloidal Self-assembly3Genetic-tunneling driven energy optimizer for spin systems2Surrogate Modeling of the Relative Entropy for Inverse Design Using Smolyak Sparse Grids5Engineering Azeotropy to Optimize the Self-Assembly of Colloidal Mixtures6Computational investigation of the effects of polymer grafting on the effective interaction between silica nanoparticles in water2Programming patchy particles for materials assembly design25Curiosity-driven search for novel nonequilibrium behaviors5Learning protocols for the fast and efficient control of active matter15Assembly of Complex Colloidal Systems Using DNA22Multiobjective Optimization for Targeted Self-Assembly among Competing Polymorphs8Nonequilibrium Self-Assembly Control by the Stochastic Landscape Method7Machine-Assisted Inverse Design of Patchy Particles for Self-Assembly of Archimedean Tilings2

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  1. Deposition control of model glasses with surface-mediated orientational order

    The Journal of Chemical Physics · 2021-09-28

    Stephen Whitelam, Peter R. Harrowell

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  2. Machine learning-based approach: global trends, research directions, and regulatory standpoints

    Data Science and Management · 2021-12-01

    Raffaele Pugliese, Stefano Regondi, Riccardo Marini

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  3. A simple solution to the problem of self-assembling cubic diamond crystals

    Nanoscale · 2022-01-01

    Lorenzo Rovigatti, John Russo, Flavio Romano, Michael Matthies, Lukáš Kroc, Petr Šulc

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  4. SAT-assembly: a new approach for designing self-assembling systems

    Journal of Physics Condensed Matter · 2022-02-11

    John Russo, Flavio Romano, Lukáš Kroc, Francesco Sciortino, Lorenzo Rovigatti, Petr Šulc

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  5. Low-dissipation self-assembly protocols of active sticky particles

    Journal of Crystal Growth · 2022-10-13

    Stephen Whitelam, Jeremy D. Schmit

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  6. Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

    Chemical Reviews · 2022-10-19

    Li Shao, Jinrong Ma, Jesse L. Prelesnik, Yicheng Zhou, Mary T. H. D. Nguyen, Mingfei Zhao, Samson A. Jenekhe, Sergei V. Kalinin, Andrew L. Ferguson, Jim Pfaendtner, Christopher J. Mundy, James J. De Yoreo, François Baneyx, Chun‐Long Chen

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  7. Designing the Self-Assembly of Arbitrary Shapes Using Minimal Complexity Building Blocks

    ACS Nano · 2023-02-10

    Joakim Bohlin, Andrew J. Turberfield, Ard A. Louis, Petr Šulc

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  8. Two-step nucleation in a binary mixture of patchy particles

    The Journal of Chemical Physics · 2023-03-30

    Camilla Beneduce, Diogo E. P. Pinto, Petr Šulc, Francesco Sciortino, John Russo

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  9. Novelty Search for Neuroevolutionary Reinforcement Learning of Deceptive Systems: An Application to Control of Colloidal Self-assembly

    Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · 2023-05-31

    Jared O’Leary, Mira M. Khare, Ali Mesbah

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  10. Genetic-tunneling driven energy optimizer for spin systems

    Communications Physics · 2023-09-02

    Qichen Xu, Zhuanglin Shen, Manuel Pereiro, Erik Sjöqvist, Pawel Andrzej Herman, Olle Eriksson, Anna Delin

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  11. Surrogate Modeling of the Relative Entropy for Inverse Design Using Smolyak Sparse Grids

    Journal of Chemical Theory and Computation · 2023-09-13

    C. Levi Petix, Mohammadreza Fakhraei, Chris A. Kieslich, Michael P. Howard

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  12. Engineering Azeotropy to Optimize the Self-Assembly of Colloidal Mixtures

    ACS Nano · 2023-12-04

    Camilla Beneduce, Francesco Sciortino, Petr Šulc, John Russo

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  13. Computational investigation of the effects of polymer grafting on the effective interaction between silica nanoparticles in water

    Soft Matter · 2024-01-01

    Yuvraj Singh, Chandan Kumar Choudhury, Rikhia Ghosh, Rakesh Sharan Singh

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  14. Programming patchy particles for materials assembly design

    Proceedings of the National Academy of Sciences · 2024-06-24

    Ella M. King, Chrisy Xiyu Du, Qian-Ze Zhu, Samuel S. Schoenholz, Michael P. Brenner

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  15. Curiosity-driven search for novel nonequilibrium behaviors

    Physical Review Research · 2024-07-11

    Martin J. Falk, Finnegan D. Roach, William Gilpin, Arvind Murugan

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  16. Learning protocols for the fast and efficient control of active matter

    Nature Communications · 2024-10-23

    Corneel Casert, Stephen Whitelam

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  17. Assembly of Complex Colloidal Systems Using DNA

    Annual Review of Condensed Matter Physics · 2025-03-10

    William M. Jacobs, W. Benjamin Rogers

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  18. Multiobjective Optimization for Targeted Self-Assembly among Competing Polymorphs

    Physical Review X · 2025-03-31

    Sambarta Chatterjee, William M. Jacobs

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  19. Nonequilibrium Self-Assembly Control by the Stochastic Landscape Method

    Journal of Chemical Information and Modeling · 2025-04-08

    Michael Faran, Gili Bisker

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  20. Machine-Assisted Inverse Design of Patchy Particles for Self-Assembly of Archimedean Tilings

    ACS Nano · 2025-10-16

    Yiwei Xu, Xin You, Tinghao Xu, Xuewei Dong, Bing Yuan, Kai Yang

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