Heme-Mediated Charge Transport Modulation: Coupling Biological Recognition to Solid-State Protein Electronics

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• Química y materiales/Química molecular y computacional28 de sept de 2026

  Scaling Density Functional Theory with Gaussian Splatting

  We propose Gaussian Splatting for Density Functional Theory (GS-DFT), which represents molecular orbitals as a cloud of Gaussians whose positions, shapes, and mixing coefficients are optimized jointly by gradient descent to minimize the energy without training data.

  Andr\'es Guzm\'an-Cordero, Cindy Zhang, Majdi Hassan y 3 más — arXiv

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• Química y materiales/Química molecular y computacional28 de sept de 2026

  Observing Phase Space Evolution During Unimolecular Decay

  Phase space evolution, recurrence time distributions and Lyapunov exponent analysis are presented which support the conclusion that TR-CEI directly observes phase space evolution during unimolecular decay.

  Abhirami Vijayakumar, Raidel Martin Barrios, Meenu Upadhyay y 4 más — arXiv

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• Química y materiales/Química molecular y computacional28 de sept de 2026

  A General Non-Markovian Electronic Friction and Langevin Dynamics Framework for Nonequilibrium Systems

  We present a general framework for simulating the nonequilibrium vibronic dynamics of molecules interacting with metal surfaces, which utilizes non-Markovian electronic friction and the corresponding generalized Langevin equation.

  S. L. Rudge, R. J. Preston, D. S. Kosov y 1 más — arXiv

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• Química y materiales/Química molecular y computacional28 de sept de 2026

  Multiphysics Simulation Framework for Continuous Ion Transport and Energetics in Atmospheric Pressure Interfaces

  In this work, we introduce MuCITE (Multiphysics simulation for Continuous Ion Transport and Energetics), which combines continuous ion injection, precomputed electric and gas flow fields, and particle-in-cell space charge updates.

  Yihui Yan, Jozef Lengyel, Frederic Rosu y 1 más — arXiv

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• Química y materiales/Química molecular y computacional28 de sept de 2026

  Structural prediction of B${}_{18}$Y${}_2$ cluster: A Machine-Learning-Assisted Basin-Hopping Study

  These results demonstrate how yttrium doping can stabilize unusual double-ring boron architectures and highlight the effectiveness of machine-learning-assisted basin-hopping searches for exploring the complex potential-energy landscapes of doped boron clusters.

  Peter Ludwig Rodr\'iguez-Kessler — arXiv

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