Selected Columns of the Density Matrix in an Atomic Orbital Basis I: An Intrinsic and Non-iterative Orbital Localization Scheme for the Occupied Space.

In this work, we extend the selected columns of the density matrix (SCDM) methodology [ 1463-1469]─a non-iterative and real-space procedure for generating localized occupied orbitals for condensed-phase systems─to the construction of local molecular orbitals (LMOs) in systems described using non-orthogonal atomic orbital (AO) basis sets. In particular, we introduce three different theoretical and algorithmic variants of SCDM (referred to as SCDM-M, SCDM-L, and SCDM-G) that can be used in conjunction with the AO basis sets used in standard quantum chemistry codebases. The SCDM-M and SCDM-L variants are based on a pivoted QR factorization of the Mulliken and Löwdin representations of the density matrix and are tantamount to selecting a well-conditioned set of projected atomic orbitals (PAOs) and projected (symmetrically-) orthogonalized atomic orbitals, respectively, as proto-LMOs that can be orthogonalized to exactly span the occupied space.

"Freedom of design" in chemical compound space: towards rational design of molecules with targeted quantum-mechanical properties.

The rational design of molecules with targeted quantum-mechanical (QM) properties requires an advanced understanding of the structure-property/property-property relationships (SPR/PPR) that exist across chemical compound space (CCS). In this work, we analyze these fundamental relationships in the sector of CCS spanned by small (primarily organic) molecules using the recently developed QM7-X dataset, a systematic, extensive, and tightly converged collection of 42 QM properties corresponding to ≈4.2M equilibrium and non-equilibrium molecular structures containing up to seven heavy/non-hydrogen atoms (including C, N, O, S, and Cl).

High-Throughput Condensed-Phase Hybrid Density Functional Theory for Large-Scale Finite-Gap Systems: The SeA Approach.

High-throughput electronic structure calculations (often performed using density functional theory (DFT)) play a central role in screening existing and novel materials, sampling potential energy surfaces, and generating data for machine learning applications. By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal DFT and furnish a more accurate description of the underlying electronic structure, albeit at a computational cost that often prohibits such high-throughput applications. To address this challenge, we have constructed a robust, accurate, and computationally efficient framework for high-throughput condensed-phase hybrid DFT and implemented this approach in the PWSCF module of Quantum ESPRESSO (QE).

Elucidating Cathodic Corrosion Mechanisms with Operando Electrochemical Transmission Electron Microscopy.

Cathodic corrosion represents an enigmatic electrochemical process in which metallic electrodes corrode under sufficiently reducing potentials. Although discovered by Fritz Haber in the 19th century, only recently has progress been made in beginning to understand the atomistic mechanisms of corroding bulk electrodes. The creation of nanoparticles as the end-product of the corrosion process suggests an additional length scale of complexity.

Uniting Nonempirical and Empirical Density Functional Approximation Strategies Using Constraint-Based Regularization.

In this work, we present a general framework that unites the two primary strategies for constructing density functional approximations (DFAs): nonempirical (NE) constraint satisfaction and empirical (E) data-driven optimization. The proposed method employs B-splines, bell-shaped spline functions with compact support, to construct each inhomogeneity correction factor (ICF). This choice offers several distinct advantages over traditional polynomial expansions by enabling explicit enforcement of linear and nonlinear constraints as well as ICF smoothness using Tikhonov and penalized B-splines (P-splines) regularization.

Electrocatalysis in Alkaline Media and Alkaline Membrane-Based Energy Technologies.

Hydrogen energy-based electrochemical energy conversion technologies offer the promise of enabling a transition of the global energy landscape from fossil fuels to renewable energy. Here, we present a comprehensive review of the fundamentals of electrocatalysis in alkaline media and applications in alkaline-based energy technologies, particularly alkaline fuel cells and water electrolyzers. Anion exchange (alkaline) membrane fuel cells (AEMFCs) enable the use of nonprecious electrocatalysts for the sluggish oxygen reduction reaction (ORR), relative to proton exchange membrane fuel cells (PEMFCs), which require Pt-based electrocatalysts.

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory-Based Molecular Dynamics II: Extensions to the Isobaric-Isoenthalpic and Isobaric-Isothermal Ensembles.

In the previous paper of this series [Ko, H.-Y. , , 3757-3785], we presented a theoretical and algorithmic framework based on a localized representation of the occupied space that exploits the inherent sparsity in the real-space evaluation of the exact exchange (EXX) interaction in finite-gap systems.

NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts.

In this work, we present NENCI-2021, a benchmark database of ∼8000 Non-Equilibirum Non-Covalent Interaction energies for a large and diverse selection of intermolecular complexes of biological and chemical relevance. To meet the growing demand for large and high-quality quantum mechanical data in the chemical sciences, NENCI-2021 starts with the 101 molecular dimers in the widely used S66 and S101 databases and extends the scope of these works by (i) including 40 cation-π and anion-π complexes, a fundamentally important class of non-covalent interactions that are found throughout nature and pose a substantial challenge to theory, and (ii) systematically sampling all 141 intermolecular potential energy surfaces (PESs) by simultaneously varying the intermolecular distance and intermolecular angle in each dimer. Designed with an emphasis on close contacts, the complexes in NENCI-2021 were generated by sampling seven intermolecular distances along each PES (ranging from 0.

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package.

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods.

Expeditious synthesis of aromatic-free piperidinium-functionalized polyethylene as alkaline anion exchange membranes.

Alkaline anion exchange membranes (AAEMs) with high hydroxide conductivity and good alkaline stability are essential for the development of anion exchange membrane fuel cells to generate clean energy by converting renewable fuels to electricity. Polyethylene-based AAEMs with excellent properties can be prepared sequential ring-opening metathesis polymerization (ROMP) and hydrogenation of cyclooctene derivatives. However, one of the major limitations of this approach is the complicated multi-step synthesis of functionalized cyclooctene monomers.

Electron confinement meet electron delocalization: non-additivity and finite-size effects in the polarizabilities and dispersion coefficients of the fullerenes.

In this work, we used finite-field derivative techniques and density functional theory (DFT) to compute the static isotropic polarizability series (αl with l = 1, 2, 3) for the C60-C84 fullerenes and quantitatively assess the intrinsic non-additivity in these fundamental response properties. By comparing against classical models of the fullerenes as conducting spherical shells (or solid spheres) of uniform electron density, a detailed critical analysis of the derived effective scaling laws (α1 ∼ N1.2, α2 ∼ N2.

QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules.

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for ≈4.2 million equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures-comprised of constitutional/structural isomers and stereoisomers, e.

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles.

The molecular dipole moment (μ) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly-via the ground state electron density-from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML).

Dual electrocatalysis enables enantioselective hydrocyanation of conjugated alkenes.

Chiral nitriles and their derivatives are prevalent in pharmaceuticals and bioactive compounds. Enantioselective alkene hydrocyanation represents a convenient and efficient approach for synthesizing these molecules. However, a generally applicable method featuring a broad substrate scope and high functional group tolerance remains elusive.

Attracting Opposites: Promiscuous Ion-π Binding in the Nucleobases.

Ion-π interactions between the face of a molecular π-system and a cation or anion are among the strongest noncovalent interactions known, with applications throughout biochemistry and structural biology, molecular recognition and host-guest chemistry, as well as enzyme kinetics and organocatalysis. In this work, we examine the competing notions of selectivity and flexibility in this class of noncovalent interactions by investigating how certain π-systems can be promiscuous ion-π binders with the versatility to form favorable cation- and anion-π complexes. We focus our efforts on a detailed theoretical case study of the DNA/RNA nucleobases by first demonstrating that these π-systems are promiscuous ion-π binders with the biologically relevant Li/Na cations and F/Cl anions via benchmark-quality quantum-mechanical binding energy curves computed at the CCSD(T)/CBS level of theory.

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory Based Molecular Dynamics. 1. Theory, Algorithm, and Performance.

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal density functional theory (DFT) and thereby furnish a more accurate and reliable description of the underlying electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated with the evaluation of all required EXX quantities has limited the applicability of hybrid DFT in the treatment of large molecules and complex condensed-phase materials. To overcome this limitation, we describe a linear-scaling approach that utilizes a local representation of the occupied orbitals (e.

Competitive Adsorption as a Route to Area-Selective Deposition.

In this work, we have explored the use of a third species during chemical vapor deposition (CVD) to direct thin-film growth to occur exclusively on one surface in the presence of another. Using a combination of density functional theory (DFT) calculations and experiments, including in situ surface analysis, we have examined the use of 4-octyne as a coadsorbate in the CVD of ZrO thin films on SiO and Cu surfaces. At sufficiently high partial pressures of the coadsorbate and sufficiently low substrate temperatures, we find that 4-octyne can effectively compete for adsorption sites, blocking chemisorption of the thin-film precursor, Zr[N(CHCH)], and preventing growth on Cu, while leaving growth unimpeded on SiO.

Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases.

While density functional theory (DFT) is often an accurate and efficient methodology for evaluating molecular properties such as energies and multipole moments, this approach often yields larger errors for response properties such as the dipole polarizability (α), which describes the tendency of a molecule to form an induced dipole moment in the presence of an electric field. In this work, we provide static α tensors (and other molecular properties such as total energy components, dipole and quadrupole moments, etc.) computed using quantum chemical (QC) and DFT methodologies for all 7,211 molecules in the QM7b database.

Reliable and practical computational description of molecular crystal polymorphs.

Reliable prediction of the polymorphic energy landscape of a molecular crystal would yield profound insight into drug development in terms of the existence and likelihood of late-appearing polymorphs. However, the computational prediction of molecular crystal polymorphs is highly challenging due to the high dimensionality of conformational and crystallographic space accompanied by the need for relative free energies to within 1 kJ/mol per molecule. In this study, we combine the most successful crystal structure sampling strategy with the most successful first-principles energy ranking strategy of the latest blind test of organic crystal structure prediction methods.

Accurate molecular polarizabilities with coupled cluster theory and machine learning.

The molecular dipole polarizability describes the tendency of a molecule to change its dipole moment in response to an applied electric field. This quantity governs key intra- and intermolecular interactions, such as induction and dispersion; plays a vital role in determining the spectroscopic signatures of molecules; and is an essential ingredient in polarizable force fields. Compared with other ground-state properties, an accurate prediction of the molecular polarizability is considerably more difficult, as this response quantity is quite sensitive to the underlying electronic structure description.

Influence of Pore Size on the van der Waals Interaction in Two-Dimensional Molecules and Materials.

Despite the importance of porous two-dimensional (2D) molecules and materials in advanced technological applications, the question of how the void space in these systems affects the van der Waals (vdW) scaling landscape has been largely unanswered. Analytical and numerical models presented herein demonstrate that the mere presence of a pore leads to markedly different vdW scaling across nonasymptotic distances, with certain relative pore sizes yielding effective power laws ranging from simple monotonic decay to the formation of minima, extended plateaus, and even maxima. These models are in remarkable agreement with first-principles approaches for the 2D building blocks of covalent organic frameworks (COFs), and reveal that COF macrocycle dimers and periodic bilayers exhibit unique vdW scaling behavior that is quite distinct from their nonporous analogs.

On the geometric dependence of the molecular dipole polarizability in water: A benchmark study of higher-order electron correlation, basis set incompleteness error, core electron effects, and zero-point vibrational contributions.

In this work, we investigate how geometric changes influence the static dipole polarizability () of a water molecule by explicitly computing the corresponding dipole polarizability surface (DPS) across 3125 total (1625 symmetry-unique) geometries using linear response coupled cluster theory including single, double, and triple excitations (LR-CCSDT) and the doubly augmented triple- basis set (d-aug-cc-pVTZ). Analytical formulae based on power series expansions of this surface are generated using linear least-squares analysis and provide highly accurate estimates of this quantity as a function of molecular geometry (i.e.

Unraveling substituent effects on the glass transition temperatures of biorenewable polyesters.

Converting biomass-based feedstocks into polymers not only reduces our reliance on fossil fuels, but also furnishes multiple opportunities to design biorenewable polymers with targeted properties and functionalities. Here we report a series of high glass transition temperature (T up to 184 °C) polyesters derived from sugar-based furan derivatives as well as a joint experimental and theoretical study of substituent effects on their thermal properties. Surprisingly, we find that polymers with moderate steric hindrance exhibit the highest T values.

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning.

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms.