Equivariant Neural Networks Utilizing Molecular Clusters for Accurate Molecular Crystal Lattice Energy Predictions.

Equivariant neural networks have emerged as prominent models in advancing the construction of interatomic potentials due to their remarkable data efficiency and generalization capabilities for out-of-distribution data. Here, we expand the utility of these networks to the prediction of crystal structures consisting of organic molecules. Traditional methods for computing crystal structure properties, such as plane-wave quantum chemical methods based on density functional theory (DFT), are prohibitively resource-intensive, often necessitating compromises in accuracy and the choice of exchange-correlation functional.

4f-Orbital mixing increases the magnetic susceptibility of Cp'Eu.

Traditional models of lanthanide electronic structure suggest that bonding is predominantly ionic, and that covalent orbital mixing is not an important factor in determining magnetic properties. Here, 4f orbital mixing and its impact on the magnetic susceptibility of Cp'Eu (Cp' = CHSiMe) was analyzed experimentally using magnetometry and X-ray absorption spectroscopy (XAS) methods at the C K-, Eu M-, and L-edges. Pre-edge features in the experimental and TDDFT-calculated C K-edge XAS spectra provided unequivocal evidence of C 2p and Eu 4f orbital mixing in the π-antibonding orbital of a' symmetry.

Inverse Design of Photonic Surfaces via High throughput Femtosecond Laser Processing and Tandem Neural Networks.

This work demonstrates a method to design photonic surfaces by combining femtosecond laser processing with the inverse design capabilities of tandem neural networks that directly link laser fabrication parameters to their resulting textured substrate optical properties. High throughput fabrication and characterization platforms are developed that generate a dataset comprising 35280 unique microtextured surfaces on stainless steel with corresponding measured spectral emissivities. The trained model utilizes the nonlinear one-to-many mapping between spectral emissivity and laser parameters.

A parallel, distributed memory implementation of the adaptive sampling configuration interaction method.

The many-body simulation of quantum systems is an active field of research that involves several different methods targeting various computing platforms. Many methods commonly employed, particularly coupled cluster methods, have been adapted to leverage the latest advances in modern high-performance computing. Selected configuration interaction (sCI) methods have seen extensive usage and development in recent years.

Computing the Many-Body Green's Function with Adaptive Variational Quantum Dynamics.

We present a method to compute the many-body real-time Green's function using an adaptive variational quantum dynamics simulation approach. The real-time Green's function involves the time evolution of a quantum state with one additional electron with respect to the ground state wave function that is first expressed as a linear-linear combination of state vectors. The real-time evolution and the Green's function are obtained by combining the dynamics of the individual state vectors in a linear combination.

PluginPlay: Enabling exascale scientific software one module at a time.

For many computational chemistry packages, being able to efficiently and effectively scale across an exascale cluster is a heroic feat. Collective experience from the Department of Energy's Exascale Computing Project suggests that achieving exascale performance requires far more planning, design, and optimization than scaling to petascale. In many cases, entire rewrites of software are necessary to address fundamental algorithmic bottlenecks.

Tris(carbene)borates; alternatives to cyclopentadienyls in organolanthanide chemistry.

The chemistry of the tris-carbene anion phenyltris(3-alkyl-imidazoline-2-yliden-1-yl)borate, [C3Me]- ligand, is initiated for f-block metal cations. Neutral, molecular complexes of the form are formed for cerium(III), while a separated ion pair forms for ytterbium(III). DFT/QTAIM computational analyses of the complexes and related tridentate tris(pyrazolyl)borate () - supported analogs demonstrates the anticipated strength of the σ donation and confirms greater covalency in the metal-carbon bonds of the [C3Me]- complexes in comparison with those in the TpMe,Me complexes.

Exploring finite temperature properties of materials with quantum computers.

Thermal properties of nanomaterials are crucial to not only improving our fundamental understanding of condensed matter systems, but also to developing novel materials for applications spanning research and industry. Since quantum effects arise at the nano-scale, these systems are difficult to simulate on classical computers. Quantum computers can efficiently simulate quantum many-body systems, yet current quantum algorithms for calculating thermal properties of these systems incur significant computational costs in that they either prepare the full thermal state on the quantum computer, or they must sample a number of pure states from a distribution that grows with system size.

Computing Free Energies with Fluctuation Relations on Quantum Computers.

As a central thermodynamic property, free energy enables the calculation of virtually any equilibrium property of a physical system, allowing for the construction of phase diagrams and predictions about transport, chemical reactions, and biological processes. Thus, methods for efficiently computing free energies, which in general is a difficult problem, are of great interest to broad areas of physics and the natural sciences. The majority of techniques for computing free energies target classical systems, leaving the computation of free energies in quantum systems less explored.

Mitigating Depolarizing Noise on Quantum Computers with Noise-Estimation Circuits.

A significant problem for current quantum computers is noise. While there are many distinct noise channels, the depolarizing noise model often appropriately describes average noise for large circuits involving many qubits and gates. We present a method to mitigate the depolarizing noise by first estimating its rate with a noise-estimation circuit and then correcting the output of the target circuit using the estimated rate.

The Effect of Geometry, Spin, and Orbital Optimization in Achieving Accurate, Correlated Results for Iron-Sulfur Cubanes.

Iron-sulfur clusters comprise an important functional motif in the catalytic centers of biological systems, capable of enabling important chemical transformations at ambient conditions. This remarkable capability derives from a notoriously complex electronic structure that is characterized by a high density of states that is sensitive to geometric changes. The spectral sensitivity to subtle geometric changes has received little attention from correlated, large active space calculations, owing partly to the exceptional computational complexity for treating these large and correlated systems accurately.

Reactions of U with H, D, and HD Studied by Guided Ion Beam Tandem Mass Spectrometry and Theory.

The kinetic energy-dependent reactions of the atomic actinide uranium cation (U) with H, D, and HD were examined by guided ion beam tandem mass spectrometry. An average 0 K bond dissociation energy of (U - H) = 2.48 ± 0.

From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape.

Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. As the hardware and software have evolved, so have the theoretical and computational chemistry methods and algorithms. Parallel computers clearly changed the common computing paradigm in the late 1970s and 80s, and the field has again seen a paradigm shift with the advent of graphical processing units.

Quantum Algorithm for High Energy Physics Simulations.

Simulating quantum field theories is a flagship application of quantum computing. However, calculating experimentally relevant high energy scattering amplitudes entirely on a quantum computer is prohibitively difficult. It is well known that such high energy scattering processes can be factored into pieces that can be computed using well established perturbative techniques, and pieces which currently have to be simulated using classical Markov chain algorithms.

On the Efficient Evaluation of the Exchange Correlation Potential on Graphics Processing Unit Clusters.

The predominance of Kohn-Sham density functional theory (KS-DFT) for the theoretical treatment of large experimentally relevant systems in molecular chemistry and materials science relies primarily on the existence of efficient software implementations which are capable of leveraging the latest advances in modern high-performance computing (HPC). With recent trends in HPC leading toward increasing reliance on heterogeneous accelerator-based architectures such as graphics processing units (GPU), existing code bases must embrace these architectural advances to maintain the high levels of performance that have come to be expected for these methods. In this work, we purpose a three-level parallelism scheme for the distributed numerical integration of the exchange-correlation (XC) potential in the Gaussian basis set discretization of the Kohn-Sham equations on large computing clusters consisting of multiple GPUs per compute node.

Resource-Efficient Chemistry on Quantum Computers with the Variational Quantum Eigensolver and the Double Unitary Coupled-Cluster Approach.

Applications of quantum simulation algorithms to obtain electronic energies of molecules on noisy intermediate-scale quantum (NISQ) devices require careful consideration of resources describing the complex electron correlation effects. In modeling second-quantized problems, the biggest challenge confronted is that the number of qubits scales linearly with the size of the molecular basis. This poses a significant limitation on the size of the basis sets and the number of correlated electrons included in quantum simulations of chemical processes.

Chemistry on Quantum Computers with Virtual Quantum Subspace Expansion.

Simulating chemical systems on quantum computers has been limited to a few electrons in a minimal basis. We demonstrate experimentally that the virtual quantum subspace expansion (Takeshita, T.; 2020, 10, 011004, 10.

Stochastic resolution of identity second-order Matsubara Green's function theory.

We develop a stochastic resolution of identity representation to the second-order Matsubara Green's function (sRI-GF2) theory. Using a stochastic resolution of the Coulomb integrals, the second order Born self-energy in GF2 is decoupled and reduced to matrix products/contractions, which reduces the computational cost from O(N) to O(N) (with N being the number of atomic orbitals). The current approach can be viewed as an extension to our previous work on stochastic resolution of identity second order Møller-Plesset perturbation theory [T.

Prediction of atomization energy using graph kernel and active learning.

Data-driven prediction of molecular properties presents unique challenges to the design of machine learning methods concerning data structure/dimensionality, symmetry adaption, and confidence management. In this paper, we present a kernel-based pipeline that can learn and predict the atomization energy of molecules with high accuracy. The framework employs Gaussian process regression to perform predictions based on the similarity between molecules, which is computed using the marginalized graph kernel.

Reductive activation of neptunyl and plutonyl oxo species with a hydroxypyridinone chelating ligand.

Oxo group activation with reduction of neptunyl(vi) and plutonyl(vi) to tetravalent hydroxo species by the hydroxypyridinone siderophore derivative 3,4,3-LI-(1,2-HOPO) was investigated in the gas-phase via electrospray ionization mass spectrometry, in solution via Raman spectroscopy, and computationally via density functional theory. Dissociation of the gas-phase tetravalent complexes resulted in actinide-hydroxo bond cleavage.

Pushing configuration-interaction to the limit: Towards massively parallel MCSCF calculations.

A new large-scale parallel multiconfigurational self-consistent field (MCSCF) implementation in the open-source NWChem computational chemistry code is presented. The generalized active space approach is used to partition large configuration interaction (CI) vectors and generate a sufficient number of batches that can be distributed to the available cores. Massively parallel CI calculations with large active spaces can be performed.

Heptavalent Actinide Tetroxides NpO and PuO: Oxidation of Pu(V) to Pu(VII) by Adding an Electron to PuO.

The highest known actinide oxidation states are Np(VII) and Pu(VII), both of which have been identified in solution and solid compounds. Recently a molecular Np(VII) complex, NpO(NO), was prepared and characterized in the gas phase. In accord with the lower stability of heptavalent Pu, no Pu(VII) molecular species has been identified.