141 papers
This review surveys recent advances in using atomistic molecular dynamics simulations to characterize RNA conformational dynamics across various contexts, emphasizing the role of enhanced sampling, integrative approaches, and artificial intelligence in improving the precision and accuracy of structural ensembles.
This paper introduces TBSCI, a fully distributed diagonalization framework utilizing a tensor-product bitstring representation and novel communication strategies that overcomes memory bottlenecks to enable scalable selected configuration interaction calculations on over 2.5 million cores while demonstrating the method's ability to achieve near-full configuration interaction accuracy with a compact wavefunction.
This paper introduces a novel, scalable, and size-intensive "Double Configuration Interaction Singles" method that utilizes a perturbative treatment of the electronic Hessian to variationaly account for orbital relaxation, thereby significantly improving the accuracy of charge-transfer excitation energies and single bond dissociation descriptions while maintaining a mean-field computational cost.
The paper introduces HEroBM, a deep equivariant graph neural network that utilizes a hierarchical, local-principle-based approach to achieve accurate, transferable, and universal backmapping from coarse-grained to all-atom molecular representations across diverse chemical systems.
This study introduces a unified static-limit formulation to compare two scissors-correction schemes for calculating second-harmonic generation in ultraviolet nonlinear-optical crystals, revealing that while both preserve spectral shapes, scheme-N yields systematically larger magnitudes and that apparent violations of Kleinman symmetry in practice stem from sum-rule approximations rather than the underlying theory.
This study presents the first definitive eight-sigma detection of the C3 molecule in Titan's atmosphere using ultra-high-resolution VLT-ESPRESSO observations, confirming a column density consistent with photochemical models and demonstrating the efficacy of exoplanet research techniques for Solar System targets.
This paper introduces "Ara," an LLM-based agentic workflow that leverages chemical priors to efficiently navigate the design space of covalent organic frameworks, successfully identifying durable and active photocatalysts for solar hydrogen production with significantly higher hit rates and faster convergence than random search or Bayesian optimization.
This study presents an inverse-design framework combining genetic algorithms with frequency-domain micromagnetics to successfully discover unconventional two-dimensional magnonic crystal structures featuring large band gaps, thereby addressing the challenges of optimizing complex lattice geometries for targeted spin-wave properties.
This study demonstrates that aqueous chlorine dioxide radicals can serve as transient spin labels for poly(ethylene terephthalate), enabling the identification of plastic types and the measurement of molecular diffusion within the polymer matrix through electron spin resonance spectroscopy.
This study employs rigidity-based spring network analysis on thousands of metal-organic frameworks to reveal that while most are formally over-constrained, they cluster near mechanical instability due to accidental geometric modes, suggesting a design principle rooted in near-criticality that can be stabilized by tuning long-range constraints.
This study establishes a validated computational framework using rSCAN+ density functional theory to predict the equilibrium morphologies of rock salt, zinc blende, and wurtzite manganese sulfide nanocrystals as a function of sulfur chemical potential, a prediction that is experimentally confirmed by the synthesis of cubic rock salt nanocrystals and oxidative solution calorimetry measurements.
This paper demonstrates that a classical solver utilizing a clustering approximation can efficiently simulate NMR spectra with linear resource scaling, thereby challenging the assumption that such problems inherently require exponential resources and necessitating a re-evaluation of the potential for quantum advantage in this domain.
This paper introduces MQED-QD, an open-source package that integrates macroscopic quantum electrodynamics with classical electromagnetic solvers to simulate exciton dynamics in complex dielectric and plasmonic environments, demonstrating how silver nanorods enhance long-range interactions and exciton delocalization compared to planar geometries.
This paper elucidates the mechanism behind the improved accuracy of semiclassical dynamics enhanced by generalized quantum master equations by demonstrating that exact "left-handed" time-derivatives delay inaccuracy while introducing long-term instability, and subsequently proposes a protocol to determine memory kernel cutoffs that leverages short-time gains while avoiding unphysical behavior in challenging regimes.
This paper presents a theoretical framework demonstrating that the transport and fluorescence dynamics of biexcitons in molecular aggregates are critically governed by the initial state's coherence and momentum composition, revealing distinct transport behaviors for standing versus traveling waves and significant differences between J and H aggregates driven by band structure-dependent interference.
This paper presents the first full-dimensional quantum scattering calculations for rovibrationally excited HD+HD collisions, identifying near-resonant transitions and low-energy resonances dominated by l=3 partial waves that agree with previous experimental cross sections and provide rate coefficients for temperatures ranging from 0.1 K to 200 K.
This paper extends first-principles spin-lattice relaxation theory to include three-phonon processes, demonstrating that while these contributions are negligible for the studied Chromium nitride complex under experimental conditions—thereby validating the weak coupling assumption—the framework reveals that slightly stronger coupling could make three-phonon effects significant at room temperature.
This paper demonstrates that short-ranged machine learned interatomic potentials (MLIPs) fail to capture long-ranged electrostatic interactions, leading to unphysical "false metallization" in polar solvents like water, a flaw that is resolved only by explicitly including long-range electrostatics.
This study employs Population Annealing with an adaptive temperature schedule and structure-resolved analysis to robustly map the thermodynamic landscape and quantify free energy differences between competing structural basins in the 38-atom Lennard-Jones cluster.
This paper introduces an optimal-tuning scheme for multiconfigurational short-range density functional theory (MC-srDFT) that determines the system-specific range-separation parameter via the ionization potential derived from Extended Koopmans' Theorem, significantly improving the accuracy of static and dynamic dipole polarizabilities compared to standard universal parameters.