arXiv subjects

Benjamin X. Shi

Publications and source records attributed to Benjamin X. Shi.

24 records · Page 2Linked to original sources

arXiv2024

Nuclear quantum effects induce superionic proton transport in nanoconfined water

Recent work has suggested that nanoconfined water may exhibit superionic proton transport at lower temperatures and pressures than bulk water. Using first-principles-level simulations, we study the role of nuclear quantum effects in inducing this superionicity in nanoconfined water. We show that nuclear quantum effects increase the ionic conductivity of nanoconfined hexatic water, leading to superionic behaviour at lower temperatures and pressures than previously thought possible. Our work suggests that superionic water may be accessible in graphene nanocapillary experiments.

cond-mat.mtrl-sci↗

arXiv2024

Data-efficient fine-tuning of foundational models for first-principles quality sublimation enthalpies

Calculating sublimation enthalpies of molecular crystal polymorphs is relevant to a wide range of technological applications. However, predicting these quantities at first-principles accuracy -- even with the aid of machine learning potentials -- is a challenge that requires sub-kJ/mol accuracy in the potential energy surface and finite-temperature sampling. We present an accurate and data-efficient protocol based on fine-tuning of the foundational MACE-MP-0 model and showcase its capabilities on sublimation enthalpies and physical properties of ice polymorphs. Our approach requires only a few tens of training structures to achieve sub-kJ/mol accuracy in the sublimation enthalpies and sub 1 % error in densities for polymorphs at finite temperature and pressure. Exploiting this data efficiency, we explore simulations of hexagonal ice at the random phase approximation level of theory at experimental temperatures and pressures, calculating its physical properties, like pair correlation function and density, with good agreement with experiments. Our approach provides a way forward for predicting the stability of molecular crystals at finite thermodynamic conditions with the accuracy of correlated electronic structure theory.

cond-mat.mtrl-sci↗

arXiv2024

Going for Gold(-Standard): Attaining Coupled Cluster Accuracy in Oxide-Supported Nanoclusters

The structure of oxide-supported metal nanoclusters plays an essential role in their sharply enhanced catalytic activity over bulk metals. Simulations provide the atomic-scale resolution needed to understand these systems. However, the sensitive mix of metal-metal and metal-support interactions which govern their structure puts stringent requirements on the method used, requiring going beyond standard density functional theory (DFT). The method of choice is coupled cluster theory [specifically CCSD(T)], but its computational cost has so far prevented applications. In this work, we showcase two approaches to make CCSD(T) accuracy readily achievable in oxide-supported nanoclusters. First, we leverage the SKZCAM protocol to provide the first benchmarks of oxide-supported nanoclusters, revealing that it is specifically metal-metal interactions that are challenging to capture with DFT. Second, we propose a CCSD(T) correction ($Δ$CC) to the metal-metal interaction errors in DFT, reaching comparable accuracy to the SKZCAM protocol at significantly lower cost. This forges a path towards studying larger systems at reliable accuracy, which we highlight by identifying a ground state structure in agreement with experiments for Au$_{20}$ on MgO; a challenging system where DFT models have yielded conflicting predictions.

cond-mat.mtrl-sci↗

arXiv2024

To Pair or not to Pair? Machine-Learned Explicitly-Correlated Electronic Structure for NaCl in Water

The extent of ion pairing in solution is an important phenomenon to rationalise transport and thermodynamic properties of electrolytes. A fundamental measure of this pairing is the potential of mean force (PMF) between solvated ions. The relative stabilities of the paired and solvent shared states in the PMF and the barrier between them are highly sensitive to the underlying potential energy surface. However direct application of accurate electronic structure methods is challenging, since long simulations are required. We develop wavefunction based machine learning potentials with the Random Phase Approximation (RPA) and second order Moller-Plesset (MP2) perturbation theory for the prototypical system of Na and Cl ions in water. We show both methods in agreement, predicting the paired and solvent shared states to have similar energies (within 0.2 kcal/mol). We also provide the same benchmarks for different DFT functionals as well as insight into the PMF based on simple analyses of the interactions in the system.

physics.chem-ph↗

arXiv2023

Direct Imaging of Charge Redistribution due to Bonding at Atomic Resolution via Electron Ptychography

Phase imaging in electron microscopy is sensitive to the local potential, including charge redistribution from bonding. We demonstrate that electron ptychography provides the necessary sensitivity to detect this subtle effect by directly imaging the charge redistribution in single layer boron nitride. Residual aberrations can be measured and corrected post-collection, and simultaneous atomic number contrast imaging provides unambiguous sub-lattice identification. Density functional theory calculations confirm the detection of charge redistribution.

cond-mat.mtrl-sci↗

arXiv2022

Accurate and efficient structure factors in ultrasoft pseudopotential and projector augmented wave DFT

Structure factors obtained from diffraction experiments are one of the most important quantities for characterizing the electronic and structural properties of materials. Methods for calculating this quantity from plane-wave density functional theory (DFT) codes are typically prohibitively expensive to perform, requiring the electron density to be constructed and evaluated on dense real-space grids. Making use of the projector functions found in both the Vanderbilt ultrasoft pseudopotential and projector augmented wave methods, we implement an approach to calculate structure factors which avoids the use of a dense grid by separating the rapidly changing contributions to the electron density and treating them on logarithmic radial grids. This approach is successfully validated against structure factors obtained from all-electron DFT and experiments for three prototype systems, allowing structure factors to be obtained at all-electron accuracy at a fraction of the cost of previous approaches for plane-wave DFT.

cond-mat.mtrl-sci↗