Toward routine Kohn–Sham inversion using the “Lieb-response” approach DOI Open Access
Tim Gould

The Journal of Chemical Physics, Journal Year: 2023, Volume and Issue: 158(6)

Published: Feb. 8, 2023

Kohn-Sham (KS) inversion, in which the effective KS mean-field potential is found for a given density, provides insights into nature of exact density functional theory (DFT) that can be exploited development approximations. Unfortunately, despite significant and sustained progress both software libraries, inversion remains rather difficult practice, especially finite basis sets. The present work presents method, dubbed "Lieb-response" approach, naturally works with existing Fock-matrix DFT infrastructure sets, numerically efficient, directly meaningful matrix energy quantities pure-state ensemble systems. Some additional yields potential. It thus enables routine even systems, as illustrated variety problems within this work, outputs used embedding schemes or machine learning effect sets on also analyzed investigated.

Language: Английский

Many-body interactions and deep neural network potentials for water DOI Creative Commons
Yaoguang Zhai,

Richa Rashmi,

Etienne Palos

et al.

The Journal of Chemical Physics, Journal Year: 2024, Volume and Issue: 160(14)

Published: April 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.

Language: Английский

Citations

11

Herbal Products‐Powered Thermosensitive Hydrogel with Phototherapy and Microenvironment Reconstruction for Accelerating Multidrug‐Resistant Bacteria‐Infected Wound Healing DOI
Gang Zhao, Guanghua Lu, Huizhen Fan

et al.

Advanced Healthcare Materials, Journal Year: 2024, Volume and Issue: 13(15)

Published: Feb. 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.

Language: Английский

Citations

9

Spin-State Splittings in 3d Transition-Metal Complexes Revisited: Benchmarking Approximate Methods for Adiabatic Spin-State Energy Differences in Fe(II) Complexes DOI
Marc Reimann, Martin Kaupp

Journal of Chemical Theory and Computation, Journal Year: 2022, Volume and Issue: 18(12), P. 7442 - 7456

Published: Nov. 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.

Language: Английский

Citations

34

Data-Driven Many-Body Potential Energy Functions for Generic Molecules: Linear Alkanes as a Proof-of-Concept Application DOI
Ethan F. Bull-Vulpe, Marc Riera, Sigbjørn Løland Bore

et al.

Journal of Chemical Theory and Computation, Journal Year: 2022, Volume and Issue: 19(14), P. 4494 - 4509

Published: Sept. 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,

Language: Английский

Citations

30

Data-driven many-body potentials from density functional theory for aqueous phase chemistry DOI Open Access
Etienne Palos, Saswata Dasgupta, Eleftherios Lambros

et al.

Chemical Physics Reviews, Journal Year: 2023, Volume and Issue: 4(1)

Published: Jan. 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.

Language: Английский

Citations

22

Delocalization error poisons the density-functional many-body expansion DOI Creative Commons
Dustin R. Broderick, John M. Herbert

Chemical Science, Journal Year: 2024, Volume and Issue: 15(47), P. 19893 - 19906

Published: Jan. 1, 2024

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

Language: Английский

Citations

8

Molecular Insights into the Influence of Ions on the Water Structure. I. Alkali Metal Ions in Solution DOI
Roya Savoj, Henry Agnew, Ruihan Zhou

et al.

The Journal of Physical Chemistry B, Journal Year: 2024, Volume and Issue: 128(8), P. 1953 - 1962

Published: Feb. 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.

Language: Английский

Citations

7

Molecular driving forces for water adsorption in MOF-808: A comparative analysis with UiO-66 DOI
Hilliary O. Frank, Francesco Paesani

The Journal of Chemical Physics, Journal Year: 2024, Volume and Issue: 160(9)

Published: March 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

Language: Английский

Citations

7

Deep Mind 21 functional does not extrapolate to transition metal chemistry DOI Creative Commons
Heng Zhao, Tim Gould, Stefan Vuckovic

et al.

Physical Chemistry Chemical Physics, Journal Year: 2024, Volume and Issue: 26(16), P. 12289 - 12298

Published: Jan. 1, 2024

The development of density functional approximations stands at a crossroads: while machine-learned functionals show potential to surpass their human-designed counterparts, extrapolation unseen chemistry lags behind.

Language: Английский

Citations

6

Identifying and embedding transferability in data-driven representations of chemical space DOI Creative Commons
Tim Gould, Bun Chan, Stephen G. Dale

et al.

Chemical Science, Journal Year: 2024, Volume and Issue: 15(28), P. 11122 - 11133

Published: Jan. 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

Language: Английский

Citations

6