Chemical Physics · Cross-listed from cond-mat.stat-mech
The Role of Concentration in Determining NaCl Nucleation Mechanism: A Story of Pathways Coexistence
Porhouy Minh and Sapna Sarupria
Deciphering the microscopic details of
crystal nucleation remains a key open problem in chemical physics. For aqueous sodium chloride (NaCl), the extent to which nucleation involves amorphous ion aggregation, and the supersaturation regime in which two-step-like behavior emerges, remains actively debated. In this work, we examine NaCl nucleation at 12, 13, and 14 mol/kg ($S = 3.2, 3.5, 3.8$) using unbiased path sampling with $\infty$RETIS. Through a combination of reaction coordinate analysis, joint and conditional probability distributions,
diffusion tensor analysis, and conditional free energy landscapes, we identify nucleation pathways without a priori mechanistic assumptions. While all concentrations are governed by the same reaction coordinate, indicating that
nucleus growth and structural ordering are central to crossing the barrier, the nature of reactive trajectories changes with supersaturation. At lower concentrations, nucleation mainly occurs via tightly coupled increases in cluster size and ordering, compatible with a one-step-like mechanism. As concentration increases, amorphous aggregation becomes increasingly decoupled from crystallization, and pathways involving substantial amorphous growth prior to crystallization become progressively more probable. Importantly, these pathways coexist within a single broad reaction channel rather than proceeding through distinct metastable intermediate states. Together, these results reconcile earlier, contradictory reports on NaCl nucleation mechanisms and support a view of nucleation as an ensemble of competing reactive pathways whose relative probabilities vary continuously with supersaturation. More broadly, our findings illustrate that substantial mechanistic diversity can emerge within a classical nucleation framework, without requiring distinct non-classical descriptions.
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Chemical Physics
Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential
Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal et al. (+10 more)
Electronic rearrangements associated with bond forming/breaking in catalytic enzymes require
quantum mechanical (QM) treatment beyond classical molecular mechanics (MM). Hybrid QM/MM methods enable tractable simulations but require system-specific setup and are sensitive to the QM region choice and treatment of the QM/MM interface. We demonstrate
quantum-accurate treatment of all-atom, complete enzymes in explicit solvent comprising up to 54k atoms and 1 microsecond of total simulation time using the machine-learned interatomic potential (MLIP) eSEN-omol. We reproduce experimental barrier trends for Claisen rearrangement in chorismate mutase, resolve critical intermediate states in PETase catalyzed
polymer depolymerization, and distinguish mechanistic alternatives for metal-activated phosphoryl transfer in nucleoside diphosphate kinase. We realize 1000x speedups relative to typical QM/MM calculations without system-specific tuning. These results establish MLIPs as a practical route to QM-accurate simulations of enzyme catalysis.
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All authors Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal, Siva Dasetty, Siddarth K. Achar, Misko Dzamba, Benjamin K. Miller, Leif D. Jacobson, C. Lawrence Zitnick, Brandon M. Wood, Zachary W. Ulissi, Daniel S. Levine, Andrew L. Ferguson
Chemical Physics
Multipole splats for optimized and inverted effective potentials
Matija Medvidović, Angel Rubio and Juan Carrasquilla
In modern density functional theory, effective
Hamiltonians are constructed to reproduce densities and forces of electrons at
equilibrium. However, their nonlocal potentials leave systematic errors in spectral properties and real-time dynamics. Access to local optimized or inverted effective potentials would remove this limitation, but the numerical fragility in finite orbital bases has long prevented their wide adoption. Here, we introduce multipole splats, a class of trial potentials that carry the correct asymptotic decay required to support the unoccupied spectrum. By connecting the computation of effective potentials to variational and supervised variants of
Hamiltonian learning, we recast both problems as stable nonlinear optimization formulated directly in standard orbital basis sets and applicable to any hybrid functional approximation. The resulting solver allows us to resolve spatial profiles of exchange-correlation potential errors during molecular dissociation and accurately reconstruct key excited states without empirical asymptotic corrections. We also show the deviation from the ionization potential
theorem for different exchange-correlation approximations on a
dataset of molecular systems. Multipole splats extract insights from established approximations and provide capacity for robust
dataset generation for downstream processing and learning.
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Chemical Physics
Balanced and broadly-normed meta-generalized gradient approximation
Yanyong Wang, Chandra Shahi, John P. Perdew et al. (+1 more)
Conventional semi-local density functional approximations for the exchange-correlation energy systematically underestimate fundamental band gaps. Advanced meta-generalized gradient approximations (meta-GGAs) can partially overcome this limitation through their orbital dependence via the kinetic energy density. In principle, the flexible meta-GGA form should allow for balanced performance across diverse properties. However, atomization energies, reaction barrier heights, and
lattice constants, as well as band gaps, exhibit different sensitivities to the large parameter space of meta-GGA functionals. In this work, we explore the space of appropriate norms that guide the r$^2$SCAN-type functional construction through the interpolation function connecting two fundamental paradigms: the one-electron limit and the uniform electron gas limit. We introduce local modifications to a strongly-smoothed interpolation function and investigate their impact on functional performance. To further probe the limits of the meta-GGA framework, we include
spin-unpolarized bonded systems among the set of norms. The resulting bonded-norm bn-r$^2$SCAN meta-GGA achieves balance: band-gap predictions approaching the accuracy of the ultra-nonlocal LAK meta-GGA and
lattice constants of nearly r$^2$SCAN accuracy.
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All authors Yanyong Wang, Chandra Shahi, John P. Perdew, Adrienn Ruzsinszky
Chemical Physics · Cross-listed from math-ph
The inverse problem of time-dependent density functional theory on the torus
Asbjørn Bækgaard Lauritsen, Mathieu Lewin and Jakob Oldenburg
We prove that, for any given sufficiently regular one-particle density, there exists a unique external potential for which the solution to the many-body Schrödinger equation has this prescribed density. This implies in particular that one can exactly reproduce the time-dependent density of an interacting system using non-interacting electrons, which is at the heart of time-dependent density functional theory. Our result covers the Coulomb interaction and densities arising from extended
nuclei.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Time-Dependent Density Functional Theory with Coulomb Interactions
Asbjørn Bækgaard Lauritsen, Mathieu Lewin and Jakob Oldenburg
We provide the first fully rigorous justification of time-dependent density functional theory in the continuum: Given a time-dependent density, we prove that there exists an external potential, unique up to a time-dependent constant, such that the corresponding Schrödinger equation reproduces the given density. This potential can be obtained with an iteration scheme. Our argument covers Coulomb interactions and does not need any Taylor expansion in time. It instead requires analyticity in space for the density and potential, which is compatible with extended
nuclei.
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Chemical Physics
Orbital choice in constructing model Hamiltonians
David W. O. Sousa and Elvira R. Sayfutyarova
Model
Hamiltonians (e.g., the Hubbard or Heisenberg models) provide a simple yet physically meaningful description of complex electronic phenomena through a small number of parameters, such as electron hopping integrals or
magnetic exchange couplings. Their construction typically exploits the local nature of electron correlation effects and therefore relies on localized orbitals. Although many localization schemes are available, the resulting localized orbitals depend not only on the chosen localization functional but also on the orbital space to which the localization procedure is applied. These choices are often treated as technical details and are rarely discussed explicitly. Here, we demonstrate that different, chemically reasonable choices of localized orbitals can lead to substantially different model
Hamiltonian parameters, even when they produce nearly identical electronic energies. Using Density
Matrix Downfolding, we systematically investigate how the localization functional and, more importantly, the choice of model orbital space affect effective
Hamiltonians derived from ab initio calculations for representative $\pi$-conjugated systems and transition metal complexes.
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Chemical Physics · Cross-listed from physics.comp-ph
Structure-Informed Bayesian Inference of Anomalous Transport and Hidden Molecular Trapping in Amorphous Media
Andrey Ananev, Maria Potapova, Nikolay Kondratyuk et al. (+2 more)
Molecular
diffusion in fluctuating amorphous and macromolecular media governs key transport processes across soft-matter physics, energy storage, and biological membranes. Extracting localized trapping states from single-particle tracking trajectories remains a fundamental challenge; because thermal structural breathing continuously reconfigures pore boundaries, conventional
geometric algorithms suffer from severe systematic biases, erroneously merging distinct localized states during cyclic molecular returns. Here, we address this deadlock by shifting the paradigm from local
geometric recurrence to a structure-informed
Bayesian regularization. Leveraging discrete Morse theory, we extract the time-invariant topological skeleton of the fluctuating host
matrix to construct robust, gas-specific physical priors that account for individual molecular dimensions. Trajectory steps are sequentially partitioned via a two-stage probabilistic refinement that dynamically adapts to the transport landscape. Benchmarked against a rigorous environment where synthetic particles explore the actual interconnected
matrix graph, our approach eliminates systemic biases, restricting macroscopic trapping parameter deviations to just a few percent under optimal linear $O(N)$ computational scaling. Applied to hydrogen and methane transport within a type-I kerogen
matrix, serving as a prototype for highly tortuous, flexible macromolecular networks, the method successfully decodes the hidden microscopic mechanisms of confined
diffusion. To ensure immediate broad impact, the documented open-source code and data are made publicly available, offering an accessible strategy readily adaptable to a broad spectrum of tracking phenomena, from ion transport in battery
polymers to
protein trafficking within cellular environments.
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All authors Andrey Ananev, Maria Potapova, Nikolay Kondratyuk, Timur Vostroknutov, Aleksey Khlyupin
Chemical Physics
Examination of Cluster Based Methods to Fermionic Systems
Jeffrey Keyes and Carlos Jimenez-Hoyos
We present the cluster mean field(cMF) and its extensions into perturbation theory(cPT) and coupled cluster(cCC) methods for fermionic systems. We discuss how the commutation rules for fermionic systems modifies the method as well as other computational details. We then perform calculations on the Hubbard model and a few select conjugated molecules to demonstrate the efficacy of the method. We will also use these examples to compare cluster methods to CAS-SCF.
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Chemical Physics · Cross-listed from cond-mat.str-el
Examining Convergence of Cluster Perturbation Theory and Cluster Coupled Cluster for J1-J2 Heisenberg Spin Lattices
Jeffrey Keyes and Carlos Jimenez-Hoyos
In previous work, it was shown that using the cluster mean field(cMF) wavefunction as the zeroth order wavefunction for perturbation theory and coupled cluster produces a reasonable approximation for the J 1-J 2 Heisenberg model in the thermodynamic limit(TDL). However, this work was limited to cPT4 and cCCSD. The central claim of cMF is that it takes strongly correlated systems and makes them weakly correlated so that PT weakly correlated methods can be used. To confirm that this claim is true, it is important to show that the PT and CC series converge. In this paper, we extend the previous calculations to cPT7 and cCCSDTQ5 where we show that the energy is converging. We also discuss how to perform cluster based calculations efficiently in the thermodynamic limit, which is crucial for these more expensive calculations.
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Chemical Physics
Competing Ring-Opening and Hofmann Elimination Pathways in Aqueous TEMPO Catholytes: A First-Principles Study
Line Mouaffac, Maiwenn Souetre, Guillaume Jeanmairet et al. (+1 more)
Aqueous redox-flow batteries based on TEMPO derivatives are promising for large-scale energy storage, but their practical use is limited by the chemical instability of the oxidized N -oxoammonium state. In this work, we investigate the degradation of five TEMPO derivatives using ab initio molecular dynamics combined with enhanced sampling. Two proposed degradation mechanisms, ring opening and Hofmann elimination, are examined and their corresponding activation free energies are compared. For all derivatives considered, ring opening exhibits a lower activation free energy than Hofmann elimination, identifying it as the kinetically preferred degradation pathway. The magnitude of the ring-opening barrier, however, varies significantly between molecules, showing that different functionalizations strongly influence its stability toward degradation. The predicted preference for ring opening is consistent with available experimental studies, which have identified or inferred ring-opening degradation for several TEMPO-based catholytes. These results provide an atomistic picture of degradation pathways that are difficult to resolve experimentally and highlight the importance of molecular structure in controlling the kinetic stability of TEMPO derivatives in aqueous electrolytes.
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All authors Line Mouaffac, Maiwenn Souetre, Guillaume Jeanmairet, Mathieu Salanne
Chemical Physics
TSBench: A physics-grounded benchmark for evaluating LLM understanding of chemical reaction mechanisms
Xiaohu Xu and Tong Zhu
Understanding a chemical reaction requires mapping a symbolic reactant-product description onto the three-dimensional pathway through which atoms rearrange, yet chemistry
benchmarks for large
language models (LLMs) largely probe factual knowledge and text-based
reasoning. Here we introduce TSBench, a
benchmark in which an LLM
agent uses structure-editing tools to construct three-dimensional transition-state (TS) guesses verified by an automated
quantum-chemical pipeline, yielding a physics-grounded pass/fail verdict. Across 546 evaluations of seven frontier LLMs on 78 elementary reactions, the aggregate success rate rose from 50.4% to 66.8% under diagnosis-driven revision; the best models approached 90% on the simplest reactions, yet performance dropped sharply with mechanistic complexity. Most failed attempts produced locally plausible saddle points whose reaction paths led to the wrong reactant-product pair, revealing local
geometric intuition without a robust grasp of the global reaction coordinate. TSBench establishes a mechanism-level yardstick for LLM
agents in mechanism-sensitive tasks such as synthesis planning and autonomous experimentation.
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Chemical Physics · Cross-listed from quant-ph
Explicit block encodings of rate matrices for simulating polymerization kinetics on quantum computers
Yuhei Ikeda, Hokuto Iwakiri, Soichiro Nishio et al. (+1 more)
Predicting how molecular weight distribution and monomer sequence evolve during polymerization is central to
polymer science, yet classical approaches face a trade-off between molecular resolution and computational cost: for copolymers, the number of distinguishable species grows exponentially with chain length.
Quantum computing offers a potential alternative, provided the non-
unitary rate
matrices governing the kinetics can be embedded into
unitary quantum circuits, a task known as block encoding. Here we construct explicit block-encoding
circuits for two kinetic models of living polymerization: Model A, single-monomer polymerization, whose lower-bidiagonal rate
matrix is encoded via a sparse-oracle construction and a two-term linear combination of
unitaries (LCU) decomposition; and Model B, two-monomer copolymerization, where a bijective labeling of
polymer species by an integer index (the m-index) yields a structured sparse
matrix encoded via either a five-term LCU or a sparse-oracle construction. Numerical simulations with the sparse-oracle encodings reproduce the classical time
evolution for reactivity ratios drawn from reported olefin copolymerization systems spanning near-random ($r_1 r_2 \simeq 1$) and blocky ($r_1 r_2 > 1$) microstructures, and the LCU encodings are verified by explicit reconstruction of the encoded
matrix block. Resource estimation shows that both implementations require only $O(\log N)$
qubits in the
matrix dimension $N$ (an exponential
memory saving over the classical state space), with gate counts growing gradually, reaching $10^4$ to $10^5$ gates at $10^3$ system
qubits. These results establish a concrete
quantum circuit foundation for simulating polymerization kinetics on fault-tolerant
quantum hardware, and a first step toward exploiting exponential state-space compression for high-dimensional
polymer reaction networks.
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All authors Yuhei Ikeda, Hokuto Iwakiri, Soichiro Nishio, Kentaro Matsumoto
Chemical Physics · Cross-listed from cond-mat.mes-hall
From London to Morse via Binnig, Quate, and Gerber
Sofia Alonso Perez, Matthew O. Blunt, Frederick Carlisle et al. (+30 more)
In their landmark paper introducing the atomic force microscope [Phys. Rev. Lett. 56, 930 (1986)], Binnig, Quate, and Gerber presciently anticipated that the technique would ultimately be capable of probing interactions running the gamut from weak van der Waals interactions to strong covalent bonding. They also highlighted that the tip-sample forces central to AFM are present, and often highly influential, in scanning tunnelling microscopy; indeed, this realisation directly inspired the invention of the force microscope. In this perspective for the Forty Years of AFM special issue, we review selected aspects of two decades of work from our group at the University of Nottingham that span the force range highlighted by BQG and are united by a common, central theme: the probe as active participant rather than passive observer. Our selection of results also covers length- and correlation-scales from the microscopic right down to the single chemical bond limit, tracking a spectrum of interactions from van der Waals/Hamaker forces, through hydrogen bonding, to covalent bonds and, finally, atom-by-atom assembly of metal clusters via vertical tip-sample transfer. Echoing BQG's own observations on the prevalence of probe-sample forces in STM, we also discuss recent evidence that tip-induced heterogeneity underpins first-passage dynamics in molecular
diffusion and highlight the challenges in acquiring non-invasive measurements of
diffusion barriers for adsorbed molecules that are readily perturbed by the probe. We close with a perspective on machine learning's growing role in automating tip-driven atomic and molecular manipulation.
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All authors Sofia Alonso Perez, Matthew O. Blunt, Frederick Carlisle, Neil R. Champness, Janette L. Dunn, Matthew Edmondson, Rowan Evers, Connor Fields, Subhashis Gangopadhyay, James Hayton, Samuel P. Jarvis, Filipe Junqueira, Lev Kantorovich, Brian Kiraly, Natalio Krasnogor, Ioannis Lekkas, Morten Møller, Philip Moriarty, Chris Pakes, Emmanuelle Pauliac-Vaujour, Oliver Phillips, Adrian Radocea, Philipp Rahe, Mohammad Abdur Rashid, Hongqian Sang, Alex Saywell, Nikhil Seeja Sivakumar, Peter Sharp, Andrew Stannard, Julian Stirling, Adam Sweetman, Simon Taylor, Richard A.J. Woolley
Chemical Physics · Cross-listed from cs.LG
MLIP Detective: Active Failure Mode Discovery Beyond Benchmark Scores for Machine-Learning Interatomic Potentials
Ryuhei Okuno, Nontawat Charoenphakdee, Kaoru Hisama et al. (+1 more)
Universal machine-learning interatomic potentials (u-MLIPs) aim to generalize across diverse configurations.
Benchmarks enable reproducible evaluation but may not expose failures outside their predefined scope. Here, we show that physics-informed search can complement
benchmark-based evaluation by uncovering hidden failure modes. We introduce MLIP Detective, an agentic framework for active failure mode discovery. Starting from
benchmark evidence, MLIP Detective generates falsifiable, physics-informed failure hypotheses, screens them with inexpensive simulations, and escalates only the most suspicious cases to human experts together with proposed verification protocols. Without issue-specific prompting, MLIP Detective identified and characterized a systematic anomaly in MACE-MPA-0: the model predicted some relaxed adsorbate-surface systems involving O- or F-containing adsorbates to be higher in energy than their corresponding separated fragments. Using cross-model comparisons, MLIP Detective further inferred a likely training-data origin for the anomaly, consistent with recent reports.
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All authors Ryuhei Okuno, Nontawat Charoenphakdee, Kaoru Hisama, Yuta Tsuboi
Chemical Physics
Fixed-Dimensional Latent Flow for Generating Variable-Size 3D Molecules
Weichi Yao, Cameron Gruich, Bryan R. Goldsmith et al. (+1 more)
Molecular size is coupled to composition, structure, and function, yet most 3D molecular generators require a predefined atom count. We introduce Equivariant-Free
Transformer-Autoencoded Latent Flow Matching, a two-stage framework that samples a fixed-dimensional latent vector using flow matching and uses an autoregressive
Transformer to determine molecular size, atom types, coordinates, and chemical attributes. Canonical atom ordering and rigid-pose
alignment enable
Transformers without equivariant layers, while decoded attributes guide bond reconstruction. On PCQM4Mv2, unconditional generation yields 87.9% unique, novel molecules passing sanitization and PoseBusters checks, exceeding baselines with lower end-to-end training and sampling time and higher end-to-end throughput. Across ten target HOMO-LUMO gaps, internal ranking retains 30% of screened candidates and increases the density functional theory-verified hit rate within 0.1 eV from 25.0% to 52.4%, while largely preserving novelty and diversity. These results demonstrate fixed-dimensional latent generation with autoregressive decoding as a practical approach to molecular design without prespecifying size.
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All authors Weichi Yao, Cameron Gruich, Bryan R. Goldsmith, Yixin Wang
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Band Structure Modulation of ZrO2 Nanoparticles for Control of CO Adsorption Properties: A Combined Density Functional Theory - Density Functional Tight Binding Study
Kexin Chen, William Dawson, Aulia Sukma Hutama et al. (+4 more)
We present a combined density functional theory (DFT) and density functional tight binding (DFTB) study of zirconia (ZrO2) nanoparticles of experimentally relevant sizes of several nanometers and their interactions with the CO molecule. A hybrid DFTB - Force Field (DFTB-FF) framework is developed, whereby band structure calculations rely on an existing Slater-Koster framework, while the accuracy of structural optimization and adsorption properties is controlled by the introduction of classical long-range interatomic potentials into DFTB instead of the traditional repulsive potentials. Additionally, coordination-dependent Zr-C potentials are introduced to account for the distinct local chemical environments of bulk-like facet sites and under-coordinated tip and edge sites, thereby improving the description of CO adsorption. This hybrid DFTB-FF approach substantially improves the robustness of geometry optimization and provides a practical strategy for extending the applicability of DFTB to complex oxide nanostructures. The calculations reveal that termination stoichiometry can be used to engineer intrinsic, p-type, or n-type electronic structures and thereby tune the adsorption activity of zirconia nanoparticles. While stoichiometric nanoparticles do not activate the C-O bond, low-coordinated sites in Zr-rich (n-type) nanoparticles exhibit chemisorption accompanied by charge donation into a CO antibonding LUMO-derived orbital, resulting in C-O bond activation. These results demonstrate that stoichiometry-controlled electronic structure and under-coordinated surface sites introduced by nanostructuring play a key role in governing the adsorption strength and reactivity of zirconia nanoparticles.
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All authors Kexin Chen, William Dawson, Aulia Sukma Hutama, Takahito Nakajima, Keisuke Kameda, Manabu Ihara, Sergei Manzhos
Chemical Physics · Cross-listed from quant-ph
Classical Active-Space Hybrid Quantum Subspace Expansion (CASH-QSE): Quantum Corrections without Remeasuring the Classically Calculable Energy
Artur F. Izmaylov
The wave function prepared by a variational
quantum eigensolver (VQE) can contain a substantial classically tractable component, yet its energy contribution is sampled on the
quantum device. Representing the wave function as a combination of a classical reference and separately prepared
quantum states allows the reference energy to be evaluated without
quantum sampling. However, near-linear dependence among these components can amplify measurement errors and destabilize the resulting energy estimate. We introduce Classical Active-Space Hybrid
Quantum Subspace Expansion (CASH-QSE), which retains a complete-active-space self-consistent field (CASSCF) reference classically and uses occupation structure to construct
quantum states exactly orthogonal to the reference and to one another. The energy follows from an ordinary Hermitian
eigenvalue problem without overlap measurements, while the same occupation constraints simplify the measured operators. Using full configuration interaction to guide component selection, we test CASH-QSE along H$_2$O and N$_2$ bond-stretching coordinates spanning weakly to strongly correlated regimes. The
benchmarks use STO–3G for both molecules and a restricted cc-pVDZ orbital space for H$_2$O. CASH-QSE reaches chemical accuracy while limiting the largest complete measurement
circuits to a few hundred all-to-all logical controlled-NOT gates. In favorable cases, it also reduces the idealized final-energy sampling cost by several orders of magnitude relative to VQE with an adaptive derivative-assembled pseudo-Trotter ansatz (ADAPT-VQE).
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Chemical Physics
Construction of downfolded Hamiltonians from projective transcorrelation
Seiichiro Ten-no
Projective transcorrelation recovers the short-range electron correlation by a similarity transformation with a geminal function $f(r_{12})$, at the cost of an effective
Hamiltonian containing a 3-body term. We replace the term by an effective operator of rank at most two, obtained from the two-body cumulant (2C) approximation to the three-particle reduced density
matrix. The 2C 3-body energy is written without cumulants, and the effective one- and two-body interactions are derived as its partial derivatives with respect to the reduced density
matrices. The truncation is assessed on the atomization and reaction energies of the HEAT set with CCSD(T), and on the CAS-pTC model, whose downfolded
Hamiltonian is held on a
qubit register with the number of Pauli strings reduced from the sixth power of the orbital count to the fourth.
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