The Potential of Neural Network Potentials

ACS Physical Chemistry Au, Год журнала: 2024, Номер 4(3), С. 232 - 241

Опубликована: Март 21, 2024

In the next half-century, physical chemistry will likely undergo a profound transformation, driven predominantly by combination of recent advances in quantum and machine learning (ML). Specifically, equivariant neural network potentials (NNPs) are breakthrough new tool that already enabling us to simulate systems at molecular scale with unprecedented accuracy speed, relying on nothing but fundamental laws. The continued development this approach realize Paul Dirac's 80-year-old vision using mechanics unify physics providing invaluable tools for understanding materials science, biology, earth sciences, beyond. era highly accurate efficient first-principles simulations provide wealth training data can be used build automated computational methodologies, such as diffusion models, design optimization scale. Large language models (LLMs) also evolve into increasingly indispensable literature review, coding, idea generation, scientific writing.

Язык: Английский

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Herbal Products‐Powered Thermosensitive Hydrogel with Phototherapy and Microenvironment Reconstruction for Accelerating Multidrug‐Resistant Bacteria‐Infected Wound Healing

Advanced Healthcare Materials, Год журнала: 2024, Номер 13(15)

Опубликована: Фев. 28, 2024

Abstract Wound healing and infection remain significant challenges due to the ineffectiveness against multidrug‐resistant (MDR) bacteria complex oxidative wound microenvironments. To address these issues, thymoquinone‐reinforced injectable thermosensitive TQ@PEG‐PAF‐Cur hydrogels with dual functions of microenvironment reshaping photodynamic therapy are developed. The hydrogel comprises natural compound thymoquinone (TQ) poly (ethylene glycol)‐block‐poly (alanine‐co‐phenyl alanine) copolymers (PEG‐PAF) conjugated photosensitizer curcumin (Cur). incorporation TQ Cur reduces sol‐to‐gel transition temperature 30°C, compared PEG‐PAF (37°C), formation strong hydrogen bonding, matching temperature. Under blue light excitation, generates amounts reactive oxygen species such as H 2 O , 1O ·OH, exhibiting rapid efficient bactericidal capacities methicillin‐resistant Staphylococcus aureus broad spectrum β‐lactamases Escherichia coli via (PDT). Additionally, effectively inhibits expressions proinflammatory cytokines in skin tissue‐forming cells. As a result, composite can rapidly transform into gel cover wound, reshape microenvironment, accelerate vivo. This collaborative antibacterial strategy provides valuable insights guide development multifunctional materials for healing.

Язык: Английский

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Many-body interactions and deep neural network potentials for water

The Journal of Chemical Physics, Год журнала: 2024, Номер 160(14)

Опубликована: Апрель 8, 2024

We present a detailed assessment of deep neural network potentials developed within the Deep Potential Molecular Dynamics (DeePMD) framework and trained on MB-pol data-driven many-body potential energy function. Specific focus is directed at ability DeePMD-based to correctly reproduce accuracy across various water systems. Analyses bulk interfacial properties as well interactions characteristic elucidate inherent limitations in transferability predictive potentials. These can be traced back an incomplete implementation "nearsightedness electronic matter" principle, which may common throughout machine learning that do not include proper representation self-consistently determined long-range electric fields. findings provide further support for "short-blanket dilemma" faced by potentials, highlighting challenges achieving balance between computational efficiency rigorous, physics-based water. Finally, we believe our study contributes ongoing discourse development application models simulating systems, offering insights could guide future improvements field.

Язык: Английский

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Spin-State Splittings in 3d Transition-Metal Complexes Revisited: Benchmarking Approximate Methods for Adiabatic Spin-State Energy Differences in Fe(II) Complexes

Journal of Chemical Theory and Computation, Год журнала: 2022, Номер 18(12), С. 7442 - 7456

Опубликована: Ноя. 23, 2022

The CASPT2+δMRCI composite approach reported in a companion paper has been extended and used to provide high-quality reference data for series of adiabatic spin gaps (defined as ΔE = Equintet - Esinglet) [FeIIL6]2+ complexes (L CNH, CO, NCH, NH3, H2O), either at nonrelativistic level or including scalar relativistic effects. These highly accurate have evaluate the performance various more approximate methods. Coupled-cluster theory with singles, doubles, perturbative triples, CCSD(T), is found agree well new Werner-type but exhibits larger underestimates by up 70 kJ/mol π-acceptor ligands, due appreciable static correlation low-spin states these systems. Widely domain-based local CCSD(T) calculations, DLPNO-CCSD(T), are shown depend very sensitively on cutoff values construct localized domains, standard not sufficient. A large number density functional approximations evaluated against data. B2PLYP double hybrid gives smallest deviations, several functionals from different rungs usual ladder hierarchy give mean absolute deviations below 20 kJ/mol. This includes B97-D semilocal functional, PBE0* global 15% exact-exchange admixture, hybrids LH07s-SVWN LH07t-SVWN. Several further achieve errors 30 (M06L-D4, SSB-D, B97-1-D4, LC-ωPBE-D4, LH12ct-SsirPW92-D4, LH12ct-SsifPW92-D4, LH14t-calPBE-D4, LHJ-HFcal-D4, hybrids) thereby also still overall outperform uncorrected CASPT2. While admixture crucial factor favoring high-spin states, present evaluations confirm that other aspects can be important well. better-performing underestimate ligands overestimate them L H2O. In contrast previous suggestion, non-self-consistent (DFT) computations top Hartree-Fock orbitals promising path produce such complexes.

Язык: Английский

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Data-Driven Many-Body Potential Energy Functions for Generic Molecules: Linear Alkanes as a Proof-of-Concept Application

Journal of Chemical Theory and Computation, Год журнала: 2022, Номер 19(14), С. 4494 - 4509

Опубликована: Сен. 16, 2022

We present a generalization of the many-body energy (MB-nrg) theoretical/computational framework that enables development data-driven potential functions (PEFs) for generic covalently bonded molecules, with arbitrary quantum mechanical accuracy. The "nearsightedness electronic matter" is exploited to define monomers as "natural building blocks" on basis their distinct chemical identity. molecules then expressed sum individual energies incrementally larger subsystems. MB-nrg PEFs represent low-order n-body energies, n = 1-4, using permutationally invariant polynomials derived from structure data carried out at an level theory, while all higher-order terms (n > 4) are represented by classical polarization term. As proof-of-concept application general framework, we linear alkanes. shown accurately reproduce reference harmonic frequencies, and scans alkanes, independently length. Since, construction, introduced here can be applied envision future computer simulations complex molecular systems PEFs,

Язык: Английский

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Data-driven many-body potentials from density functional theory for aqueous phase chemistry

Chemical Physics Reviews, Год журнала: 2023, Номер 4(1)

Опубликована: Янв. 10, 2023

Density functional theory (DFT) has been applied to modeling molecular interactions in water for over three decades. The ubiquity of chemical and biological processes demands a unified understanding its physics, from the single molecule thermodynamic limit everything between. Recent advances development data-driven machine-learning potentials have accelerated simulation aqueous systems with DFT accuracy. However, anomalous properties condensed phase, where rigorous treatment both local non-local many-body (MB) is order, are often unsatisfactory or partially missing models water. In this review, we discuss based on provide comprehensive description general theoretical/computational framework reference data. This framework, coined MB-DFT, readily enables efficient dynamics (MD) simulations small molecules, gas phases, while preserving accuracy underlying model. Theoretical considerations emphasized, including role that delocalization error plays MB-DFT possibility elevate near-chemical-accuracy through density-corrected formalism. described detail, along application MB-MD recent extension reactive solution within quantum mechanics/MB mechanics (QM/MB-MM) scheme, using as prototypical solvent. Finally, identify open challenges future directions QM/MB-MM phases.

Язык: Английский

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Identifying and embedding transferability in data-driven representations of chemical space

Chemical Science, Год журнала: 2024, Номер 15(28), С. 11122 - 11133

Опубликована: Янв. 1, 2024

We show that human intuition in the curation of training data introduces biases hamper model transferability. introduce a transferability assessment tool which rigorously measures and subsequently improves

Язык: Английский

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Molecular driving forces for water adsorption in MOF-808: A comparative analysis with UiO-66

The Journal of Chemical Physics, Год журнала: 2024, Номер 160(9)

Опубликована: Март 1, 2024

Metal–organic frameworks (MOFs), with their unique porous structures and versatile functionality, have emerged as promising materials for the adsorption, separation, storage of diverse molecular species. In this study, we investigate water adsorption in MOF-808, a prototypical MOF that shares same secondary building unit (SBU) UiO-66, elucidate how differences topology connectivity between two MOFs influence mechanism. To end, dynamics simulations were performed to calculate several thermodynamic dynamical properties MOF-808 function relative humidity (RH), from initial step full pore filling. At low RH, μ3-OH groups SBUs form hydrogen bonds molecules entering pores, which triggers filling these pores before other become engaged bonding molecules. Our analyses indicate filled by sequentially RH increases. A similar mechanism has been reported UiO-66. Despite similarity, our study highlights distinct framework characteristics process differently

Язык: Английский

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Delocalization error poisons the density-functional many-body expansion

Chemical Science, Год журнала: 2024, Номер 15(47), С. 19893 - 19906

Опубликована: Янв. 1, 2024

Self-interaction error leads to runaway accumulation when density functional theory is used in conjunction with the many-body expansion.

Язык: Английский

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Molecular Insights into the Influence of Ions on the Water Structure. I. Alkali Metal Ions in Solution

The Journal of Physical Chemistry B, Год журнала: 2024, Номер 128(8), С. 1953 - 1962

Опубликована: Фев. 19, 2024

In this study, we explore the impact of alkali metal ions (Li+, Na+, K+, Rb+, and Cs+) on hydration structure water using molecular dynamics simulations carried out with MB-nrg potential energy functions (PEFs). Our analyses include radial distribution functions, coordination numbers, dipole moments, infrared spectra molecules, calculated as a function solvation shells. The results collectively indicate highly local influence all hydrogen-bond network established by surrounding smallest most densely charged Li+ ion exerting pronounced effect. Remarkably, PEFs demonstrate excellent agreement available experimental data for position size first shells, underscoring their predictive models realistic ionic aqueous solutions across various thermodynamic conditions environments.

Язык: Английский

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