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Timothy C. Berkelbach

Publications and source records attributed to Timothy C. Berkelbach.

At least 19 recordsLinked to original sources

Molecular spin qubits in a van der Waals bottle

Advancing quantum information technologies requires qubits whose coherence can be precisely engineered. Among the qubit platforms in development, molecular spin qubits (MSQs) stand out for their atomic scale tunability and chemical specificity, making them powerful candidates for sensing, simulation, and information processing. However, integrating MSQs into solid-state architectures without degrading their coherence remains a central challenge. Here, we introduce van der Waals (vdW) confinement within two-dimensional materials as a strategy for stabilizing quantum states in MSQs by engineering their local electronic, vibrational, and symmetry environments. Using cobaltocene as a model system, we show that confinement within vdW SnS2 and CdPS3 single crystals reorganizes the single-ion energy landscape and slows spin-lattice relaxation by over two orders of magnitude relative to unconfined cobaltocene. The confined MSQs adopt deterministic orientations and self-assemble into ordered, atomically precise superlattices, establishing vdW confinement as a pathway for integrating MSQs into functional quantum devices.

cond-mat.mtrl-sci

Wavefunction-based periodic quantum chemistry

High-accuracy molecular quantum chemistry offers a promising toolbox for applications to condensed-phase systems, but this field is difficult to enter due to its combination of topics from molecular quantum chemistry, solid-state physics, and numerical methods. Aiming to ease this transition, we present a comprehensive, pedagogical tutorial on periodic quantum chemistry calculations, using both mean-field and correlated theories. The subtleties of periodic Coulomb interactions are discussed in detail, focusing on the Ewald summation approach. We describe the two most popular periodic, one-electron basis functions---plane waves and periodic linear combinations of atomic orbitals---and we give formulas for all Hamiltonian integrals. Next, we explain the use of $k$-point sampling as a symmetry adaptation of supercell basis functions and the associated savings in computational costs as well as the use of density fitting and related approximations to further reduce costs. We present the working equations of a few example periodic quantum chemistry methods, including Hartree-Fock theory, perturbation theory, and coupled-cluster theory, and we discuss their finite-size errors and convergence to the physically relevant thermodynamic limit. Finally, we briefly discuss local correlation and quantum embedding theories, which are especially appropriate for periodic systems due to their lattice translational symmetries.

physics.chem-ph

High-performance parallel implementation of high-order coupled-cluster theories

High-order coupled-cluster theories with iterative triples (CCSDT), perturbative quadruples [CCSDT(Q)], and iterative quadruples (CCSDTQ) provide benchmark-quality correlation energies, but their steep computational scalings, $O(N^8), O(N^9)$, and $O(N^{10})$, together with the large memory requirements of high-order amplitude tensors, have historically limited their application to small molecules. In this work, we develop efficient open-source implementations of spin-restricted CCSDT (RCCSDT), RCCSDT(Q), RCCSDTQ, and spin-unrestricted CCSDT (UCCSDT) within the PySCF package. The shared-memory implementation combines compact triangular storage of the highest-order amplitude tensors with the multithreaded tensor contraction backend pytblis, enabling efficient use of modern many-core CPU architectures. This design delivers near-ideal thread scaling up to 90 cores and achieves wall times shorter than or comparable to existing single-node implementations for representative benchmark molecules. We further extend RCCSDT, RCCSDT(Q), and RCCSDTQ to distributed-memory architectures using MPI-based algorithms. By distributing compact high-order amplitudes across MPI ranks and overlapping communication with computation through nonblocking data transfers, the distributed implementation achieves near-ideal strong scaling on up to 32 nodes, corresponding to approximately 3,000 CPU cores. These developments substantially extend the practical reach of canonical high-order CC theory, enabling CCSDT(Q) calculations with approximately 100 correlated electrons in 450 orbitals and CCSDTQ calculations with approximately 50 correlated electrons in 115 orbitals. Applications to $π$-stacked noncovalent dimers, the CO dissociation energy of Cr(CO)$_6$, and the Cope rearrangement of semibullvalene demonstrate that canonical high-order CC benchmarks are now feasible for chemically realistic molecular systems.

physics.chem-ph

Reaching the thermodynamic limit of periodic CCSD cohesive energies and band gaps

The high computational cost of periodic coupled-cluster theory has limited the density of Brillouin zone sampling, yielding finite-size errors that need to be removed by extrapolation. Here we report the development and application of a distributed-memory software implementation of periodic coupled-cluster theory with single and double excitations (CCSD) that runs efficiently on up to 12 nodes with 96 cores each. This new implementation allows ground-state and excited-state calculations in which the Brillouin zone is sampled with up to $6^3=216$ $k$-points, allowing us to reliably extrapolate to the thermodynamic limit. For eight simple semiconductors and insulators, we report the cohesive energy and band gap, which are converged to 0.1 eV, providing definitive benchmark numbers for the CCSD level of theory. Compared to experimental values, average errors for the cohesive energy are 0.1-0.2 eV (typically an underestimate), and average errors for the band gap are about 0.4 eV (typically an overestimate).

physics.chem-ph

How reproducible are first-principles simulations of liquid water?

Liquid water is fundamentally important, and its accurate computer simulation has been the driving force for myriad methodological developments. Ab initio molecular dynamics with forces obtained from density functional theory (DFT) is now a standard tool widely used by researchers. However, we reveal that previous studies of liquid water using the same widely-used density functional (revPBE-D3) exhibit significant discrepancies with one another, varying by over 20% in the diffusion coefficient and 10% in the density, raising fundamental questions about reproducibility. By combining modern long-range machine-learning interatomic potentials that enable robust statistical sampling with carefully converged DFT training data, we resolve these discrepancies, achieving consensus across six diverse community codes. Our predictions differ markedly from previous literature: we show that most previous results overestimate the density and underestimate the diffusion coefficient of revPBE-D3 water due to basis set incompleteness and pseudopotential inconsistencies, coupled with limitations in statistical sampling (in some cases). These benchmark values provide a reliable reference for validating current and future implementations of DFT-based ab initio molecular dynamics. Reaching agreement establishes confidence and credibility and serves as a prerequisite for the systematic assessment of new density functionals and numerical approximations.

physics.chem-ph

The Python Simulations of Chemistry Framework: 10 years of an open-source quantum chemistry project

Over the past decade, the Python-based Simulations of Chemistry Framework (PySCF) has developed into a widely used open-source platform for electronic structure theory and quantum chemical method development. This article reviews the major advances since the previous overview in 2020, covering new modules and methodology, infrastructure changes, and performance benchmarks.

physics.chem-ph

Adsorption energies and decomposition barrier heights for ethylene carbonate on the surface of lithium from cluster-based quantum chemistry

For ethylene carbonate on the (100) surface of lithium, we calculate the adsorption energy in two binding motifs as well as the barrier height for a ring-opening decomposition reaction. We validate a scheme for producing results in the thermodynamic limit by correcting results obtained on finite lithium clusters containing only 40-100 atoms, which enables the use of hybrid density functionals, the random-phase approximation, and correlated wavefunction theories such as coupled-cluster theory and auxiliary-field quantum Monte Carlo. We find that the high-level theories agree to within 2-5 kcal/mol and can therefore serve as benchmarks for more affordable methods. Using our reference data, we demonstrate that generalized gradient approximation functionals, such as PBE, are not sufficiently accurate for reaction barrier heights, and we identify $ω$B97X-V as an especially promising functional for the interfacial chemistry of electrolyte solvents at lithium metal anodes.

cond-mat.mtrl-sci

Practical and accurate density functionals for transition-metal heterogeneous catalysis

Density functional theory (DFT) underpins modern atomistic simulations of transition-metal surfaces. It can predict key properties linked to catalytic performance, such as adsorption energies and barrier heights, enabling new paradigms in rational catalyst design. These applications require reliable density functionals, however achieving transition-metal chemical accuracy (13 kJ/mol) on these properties remains challenging. We introduce a framework for designing new functionals tailored to catalytic processes on transition-metal surfaces, building on recent non-self-consistent approaches. Within this framework, we develop a hybrid and a double-hybrid functional that achieve unprecedented accuracy, with the latter reaching transition-metal chemical accuracy on average across 39 experimental adsorption reactions. In addition, both functionals demonstrate balanced performance for 17 barrier heights and correct qualitative failures of standard functionals, including CO adsorption on Pt(111) and graphene on Ni(111). They are computationally efficient, readily integrated into existing DFT codes, and supported by open-source workflows to facilitate adoption. More broadly, this framework provides a systematic route towards improved functionals for heterogeneous catalysis and complex materials.

cond-mat.mtrl-sci

Markov State Models for Tracking Reaction Dynamics on Catalytic Nanoparticles

Markov state models (MSMs) are a powerful tool to analyze and coarse-grain complex dynamical data into interpretable kinetic processes. This capability is particularly important in heterogeneous catalysis, where a medley of reactants and intermediates interact on surfaces that might simultaneously experience structural fluctuations. For these very complex systems, standard transition state theory (TST) approaches are no longer appropriate, motivating alternative approaches that can retain dynamical complexity while providing physical insight. With machine learned interatomic potentials being more and more ubiquitous, directly simulating complex catalytic systems with molecular dynamics (MD) is becoming increasingly feasible. Extending MSMs to dynamically coarse grain MD simulation data of catalytic processes, we analyze hydrogen dynamics on rhodium catalysts with slab and nanoparticle geometries over a range of hydrogen surface concentrations. Somewhat counterintuitively, nanoparticle features, such as corners and edges, effectively slow down the association/dissociation process, and the cooperative behavior of hydrogen-hydrogen interactions leads to a non-monotonic concentration dependence of the rates, which would not be predicted with standard TST.

cond-mat.stat-mech

Size-Consistent Adiabatic Connection Functionals via Orbital-Based Matrix Interpolation

We introduce a size-consistent and orbital-invariant formalism for constructing correlation functionals based on the adiabatic connection for density functional theory (DFT). By constructing correlation energy matrices for the weak and strong correlation limits in the space of occupied orbitals, our method, which we call orbital-based size-consistent matrix interpolation (OSMI), avoids previous difficulties in the construction of size-consistent adiabatic connection functionals. We design a simple, nonempirical adiabatic connection and a one-parameter strong-interaction limit functional, and we show that the resulting method reproduces the correlation energy of the uniform electron gas over a wide range of densities. When applied to subsets of the GMTKN55 thermochemistry database, OSMI is more accurate on average than MP2 and nonempirical density functionals. Most notably, OSMI provides excellent predictions of the barrier heights we tested, with average errors of less than 2 kcal mol$^{-1}$. Finally, we find that OSMI improves the trade-off between fractional spin and fractional charge errors for bond dissociation curves compared to DFT and MP2. The fact that OSMI provides a good description of molecular systems and the uniform electron gas, while also maintaining low self-interaction error and size-consistency, suggests that it could provide a framework for studying heterogeneous chemical systems.

physics.chem-ph

Reaction dynamics of lithium-mediated electrolyte decomposition using machine learning potentials

We study the ring-opening decomposition of ethylene carbonate in the presence of a single lithium atom and on the surface of lithium metal. Combining accurate electronic structure theory, enhanced sampling, and machine learning, we fine-tune the MACE-MP0 foundation model and apply the resulting machine learning potentials to obtain statistically converged free energy profiles and reaction rates. We confirm that the level of electronic structure theory is important, and inaccurate density functionals can overestimate the reaction rate by up to nine orders of magnitude. We also find that harmonic transition state theory underestimates reaction rates by about one order of magnitude. For the surface reaction, we find and characterize a new, ultrafast decomposition pathway wherein the carbonyl is deeply inserted into the lithium surface and bent by about 70$^\circ$. This reaction, which occurs in a few tens of picoseconds, generates a ring-opened intermediate that is a precursor for CO or CO$_2$ formation; by contrast, an alternative pathway that yields CO$_3^{2-}$ and ethylene is found to be non-competitive, occurring on a timescale of tens of nanoseconds.

physics.chem-ph

Exact mid-IR quantum vibrational spectra of neutral water clusters

We use selected configuration interaction to calculate the zero-temperature mid-infrared (2800-3800 cm$^{-1}$) vibrational spectra of a water monomer, dimer, trimer, and hexamer in its cage and prism geometries. We use the recently introduced, accurate q-AQUA-pol potential energy surface along with the n-mode representation of the potential to facilitate grid-based quadrature and integral storage. Within selected configuration interaction, we introduce a new approach to the calculation of spectra that is complementary to eigenstate enumeration. In the new approach, we calculate the spectrum using the response-vector method, and the system of linear equations is solved using a basis of configurations that are optimally selected at each frequency of interest. We compare our spectra to previous studies, and highlight limitations of the local monomer approximation. To the best of our knowledge, our hexamer spectra are the most accurate ones reported to date.

physics.chem-ph

Core binding energies of solids with periodic EOM-CCSD

We report the core binding energies of K-edge and L-edge transitions in simple semiconducting and insulating solids using periodic equation-of-motion coupled-cluster theory with single and double excitations (EOM-CCSD). In our all-electron calculations, we use triple zeta basis sets with core correlation, and we sample the Brillouin zone using up to 4x4x4 k-points. Our final numbers, which are obtained through composite corrections and extrapolation to the thermodynamic limit, exhibit errors of about 2 eV when compared to experimental values. This level of accuracy from CCSD is about the same as it is for molecules. A low-scaling approximation to EOM-CCSD performs marginally worse at lower cost, with errors of about 3 eV.

physics.chem-ph

Strong anharmonicity dictates ultralow thermal conductivities of type-I clathrates

Type-I clathrate solids have attracted significant interest due to their ultralow thermal conductivities and subsequent promise for thermoelectric applications, yet the mechanisms underlying these properties are not well understood. Here, we extend the framework of vibrational dynamical mean-field theory (VDMFT) to calculate temperature-dependent thermal transport properties of $X_8$Ga$_{16}$Ge$_{30}$, where $X=$ Ba, Sr, using a many-body Green's function approach. We find that nonresonant scattering between cage acoustic modes and rattling modes leads to a reduction of acoustic phonon lifetimes and thus thermal conductivities. Moreover, we find that the moderate temperature dependence of conductivities above 300 K, which is consistent with experimental measurements, cannot be reproduced by standard perturbation theory calculations, which predict a $T^{-1}$ dependence. Therefore, we conclude that nonperturbative anharmonic effects, including four- and higher-phonon scattering processes, are responsible for the ultralow thermal conductivities of type-I clathrates.

cond-mat.mtrl-sci

Improved energies and wave function accuracy with Weighted Variational Monte Carlo

Neural network parametrizations have increasingly been used to represent the ground and excited states in variational Monte Carlo (VMC) with promising results. However, traditional VMC methods only optimize the wave function in regions of peak probability. The wave function is uncontrolled in the tails of the probability distribution, which can limit the accuracy of the trained wavefunction approximation. To improve the approximation accuracy in the probability tails, this paper interprets VMC as a gradient flow in the space of wave functions, followed by a projection step. From this perspective, arbitrary probability distributions can be used in the projection step, allowing the user to prioritize accuracy in different regions of state space. Motivated by this theoretical perspective, the paper tests a new weighted VMC method on the antiferromagnetic Heisenberg model for a periodic spin chain. Compared to traditional VMC, weighted VMC reduces the error in the ground state energy by a factor of 2 and it reduces the errors in the local energies away from the mode by large factors of $10^2$--$10^4$.

physics.comp-ph

Ab initio quantum many-body description of superconducting trends in the cuprates

Using a systematic ab initio quantum many-body approach that goes beyond low-energy models, we directly compute the superconducting pairing order and estimate the pairing gap of several doped cuprate materials and structures within a purely electronic picture. We find that we can correctly capture two well-known trends: the pressure effect, where the pairing order and gap increase with intra-layer pressure, and the layer effect, where the pairing order and gap vary with the number of copper-oxygen layers. From these calculations, we observe that the strength of superexchange and the covalency at optimal doping are the best descriptors for these trends. Our microscopic analysis further identifies that strong short-range spin fluctuations and multi-orbital charge fluctuations drive the development of the pairing order. Our work illustrates the possibility of a material-specific ab initio understanding of unconventional high-temperature superconducting materials.

cond-mat.supr-con

Efficient Implementation of the Random Phase Approximation with Domain-based Local Pair Natural Orbitals

We present an efficient implementation of the random phase approximation (RPA) for molecular systems within the domain-based local pair natural orbital (DLPNO) framework. With optimized parameters, DLPNO-RPA achieves approximately 99.9% accuracy in the total correlation energy compared to a canonical implementation, enabling highly accurate reaction energies and potential energy surfaces to be computed while substantially reducing computational costs. As an application, we demonstrate the capability of DLPNO-RPA to efficiently calculate basis set-converged binding energies for a set of large molecules, with results showing excellent agreement with high-level reference data from both coupled cluster and diffusion Monte Carlo. This development paves the way for the routine use of RPA-based methods in molecular quantum chemistry.

physics.chem-ph

Diabatic states of charge transfer with constrained charge equilibration

Charge transfer (CT) processes that are electronically non-adiabatic are ubiquitous in chemistry, biology, and materials science, but their theoretical description requires diabatic states or adiabatic excited states. For complex systems, these latter states are more difficult to calculate than the adiabatic ground state. Here, we propose a simple method to obtain diabatic states, including energies and charges, by constraining the atomic charges within the charge equilibration framework. For two-state systems, the exact diabatic coupling can be determined, from which the adiabatic excited-state energy can also be calculated. The method can be viewed as an affordable alternative to constrained density functional theory (CDFT), and so we call it constrained charge equilibration (CQEq). We test the CQEq method on the anthracene-tetracyanoethylene CT complex and the reductive decomposition of ethylene carbonate on a lithium metal surface. We find that CQEq predicts diabatic energies, charges, and adiabatic excitation energies in good agreement with CDFT, and we propose that CQEq is promising for combination with machine learning force fields to study non-adiabatic CT in the condensed phase.

physics.chem-ph