Performance of Density Functionals for Excited-State Properties of Isolated Chromophores and Exciplexes: Emission Spectra, Solvatochromic Shifts, and Charge-Transfer Character.

This study assesses the performance of various meta-generalized gradient approximation (meta-GGA), global hybrid, and range-separated hybrid (RSH) density functionals in capturing the excited-state properties of organic chromophores and their excited-state complexes (exciplexes). Motivated by their uses in solar energy harvesting and photoredox CO2 reduction, we use oligo-(p-phenylenes) and their excited-state complexes with triethylamine as model systems. We focus on the fluorescence properties of these systems, specifically emission energies. We also consider solvatochromic shifts and wave function characteristics. The latter is described by using reduced quantities such as natural transition orbitals (NTOs) and exciton descriptors. The functionals are benchmarked against the experimental fluorescence spectra and the equation-of-motion coupled-cluster method with single and double excitations. Both in isolated chromophores and in exciplexes, meta-GGA functionals drastically underestimate the emission energies and exhibit significant exciton delocalization and anticorrelation between electron and hole motion. The performance of global hybrid functionals is strongly dependent on the percentage of exact exchange. Our study identifies RSH GGAs as the best-performing functionals, with ωPBE demonstrating the best agreement with experimental results. RSH meta-GGAs often overestimate emission energies in exciplexes and yield larger hole NTOs. Their performance can be improved by optimally tuning the range-separation parameter.

The Hydrogen Evolution Activity of BaZrS3, BaTiS3, and BaVS3 Chalcogenide Perovskites.

Chalcogenide perovskites are a class of materials with electronic and optoelectronic properties desirable for solar cells, infrared optics, and computing. The oxide counterparts of these chalcogenides have been studied extensively for their electrocatalytic and photoelectrochemical properties. As chalcogenide perovskites are more covalent, conductive, and stable, we hypothesize that they are more viable as electrocatalysts than oxide perovskites. The goal of this synthetic, experimental, and computational study is to examine the hydrogen evolution reaction (HER) activity of three Barium-based chalcogenides in perovskite and related structures: BaZrS3, BaTiS3, and BaVS3. Potential energy surfaces for hydrogen adsorption on surfaces of these materials are calculated using density functional theory and the computational hydrogen electrode model is used to contrast overpotentials with experiment. Although both experiments and computations agree that BaVS3 is the most active of the three materials, high overpotentials of these materials make them less viable than platinum for HER. Our work establishes a framework for future studies in the chemical and electrochemical properties of chalcogenide perovskites.

Simulating excited-state complex ensembles: Fluorescence and solvatochromism in amine-arene exciplexes.

Exciplexes are excited-state complexes formed as a result of partial charge transfer from the donor to the acceptor species when one moiety of the donor-acceptor pair is electronically excited. The arene-amine exciplex formed between oligo-(p-phenylene) (OPP) and triethylamine (TEA) is of interest in the catalytic photoreduction of CO2 because it can compete with complete electron transfer to the OPP catalyst. Therefore, formation of the exciplex can hinder the generation of a radical anion OPP·- necessary for subsequent CO2 reduction. We report an implementation of a workflow automating quantum-chemistry calculations that generate and characterize an ensemble of structures to represent this exciplex state. We use FireWorks, Pymatgen, and Custodian Python packages for high-throughput ensemble generation. The workflow includes time-dependent density functional theory optimization, verification of excited-state minima, and exciplex characterization with natural transition orbitals, exciton analysis, excited-state Mulliken charges, and energy decomposition analysis. Fluorescence spectra computed for these ensembles using Boltzmann-weighted contributions of each structure agree better with experiment than our previous calculations based on a single representative exciplex structure [Kron et al., J. Phys. Chem. A 126, 2319-2329 (2022)]. The ensemble description of the exciplex state also reproduces an experimentally observed red shift of the emission spectrum of [OPP-4-TEA]* relative to [OPP-3-TEA]*. The workflow developed here streamlines otherwise labor-intensive calculations that would require significant user involvement and intervention.

Controlling selectivity for dechlorination of poly(vinyl chloride) with (xantphos)RhCl.

Reaction of poly(vinyl chloride) (PVC) with 5 equiv. of triethyl silane in THF, in the presence of in situ generated (xantphos)RhCl catalyst, results in partial reduction of PVC via hydrodechlorination to yield poly(vinyl chloride-co-ethylene). Increasing catalyst loading or using N,N-dimethylacetamide (DMA) as a solvent both diminished selectivity for hydrodechlorination, promoting competitive dehydrochlorination reactions. Reaction of PVC with 2 equiv. of sodium formate in THF in the presence of (xantphos)RhCl affords excellent selectivity for hydrodechlorination along with complete PVC dechlorination, yielding polyethylene-like polymers. Higher catalyst loadings were necessary to activate PVC towards reduction in this case. In contrast, reaction of PVC with 1 equiv. of NaH in DMA, in the presence of (xantphos)RhCl, exhibited good selectivity for dehydrochlorination, as well as much higher reaction rates. These results combined shed light on the interplay between critical reaction parameters that control PVC's mode of reactivity.

Nanoscale Iron Redistribution during Thermochemical Decomposition of CaTi1-x Fe x O3-δ Alters the Electrical Transport Pathway: Implications for Oxygen-Transport Membranes, Electrocatalysis, and Photocatalysis.

Potential applications of the earth-abundant, low-cost, and non-critical perovskite CaTi1-x Fe x O3-δ in electrocatalysis, photocatalysis, and oxygen-transport membranes have motivated research to tune its chemical composition and morphology. However, investigations on the decomposition mechanism(s) of CaTi1-x Fe x O3-δ under thermochemically reducing conditions are limited, and direct evidence of the nano- and atomic-level decomposition process is not available in the literature. In this work, the phase evolution of CaTi1-x Fe x O3-δ (x = 0-0.4) was investigated in a H2-containing atmosphere after heat treatments up to 600 °C. The results show that CaTi1-x Fe x O3-δ maintained a stable perovskite phase at low Fe contents while exhibiting a phase decomposition to Fe/Fe oxide nanoparticles as the Fe content increases. In CaTi0.7Fe0.3O3-δ and CaTi0.6Fe0.4O3-δ, the phase evolution to Fe/Fe oxide was greatly influenced by the temperature: Only temperatures of 300 °C and greater facilitated phase evolution. Fully coherent Fe-rich and Fe-depleted perovskite nanodomains were observed directly by atomic-resolution scanning transmission electron microscopy. Prior evidence for such nanodomain formation was not found, and it is thought to result from a near-surface Kirkendall-like phenomenon caused by Fe migration in the absence of Ca and Ti co-migration. Density functional theory simulations of Fe-doped bulk models reveal that Fe in an octahedral interstitial site is energetically more favorable than in a tetrahedral site. In addition to coherent nanodomains, agglomerated Fe/Fe oxide nanoparticles formed on the ceramic surface during decomposition, which altered the electrical transport mechanism. From temperature-dependent electrical conductivity measurements, it was found that heat treatment and phase decomposition change the transport mechanism from thermally activated p-type electronic conductivity through the perovskite to electronic conduction through the iron oxide formed by thermochemical decomposition. This understanding will be useful to those who are developing or employing this and similar earth-abundant functional perovskites for use under reducing conditions, at elevated temperatures, and when designing materials syntheses and processes.

Recent Advances toward Efficient Calculation of Higher Nuclear Derivatives in Quantum Chemistry.

In this paper, we provide an overview of state-of-the-art techniques that are being developed for efficient calculation of second and higher nuclear derivatives of quantum mechanical (QM) energy. Calculations of nuclear Hessians and anharmonic terms incur high costs and memory and scale poorly with system size. Three emerging classes of methods─machine learning (ML), automatic differentiation (AD), and matrix completion (MC)─have demonstrated promise in overcoming these challenges. We illustrate studies that employ unsupervised ML methods to reduce the need for multiple Hessian calculations in dynamics simulations and those that utilize supervised ML to construct approximate potential energy surfaces and estimate Hessians and anharmonic terms at reduced cost. By extension, if electronic structure operations could be written in a manner similar to functions underlying ML methods, rapid differentiation or AD routines can be employed to inexpensively calculate higher arbitrary-order derivatives. While ML approaches are typically black-box, we describe methods such as compressed sensing (CS) and MC, which explicitly leverage problem-specific mathematical properties of higher derivatives such as sparsity and low-rank, to complete higher derivative information using only a small, incomplete sample. The three classes of methods facilitate reliable predictions of observables ranging from infrared spectra to thermal conductivity and constitute a promising way forward in accurately capturing otherwise intractable higher-order responses of QM energy to nuclear perturbations.

Toward Efficient Direct Dynamics Studies of Chemical Reactions: A Novel Matrix Completion Algorithm.

This paper describes the development and testing of a polynomial variety-based matrix completion (PVMC) algorithm. Our goal is to reduce computational effort associated with reaction rate coefficient calculations using variational transition state theory with multidimensional tunneling (VTST-MT). The algorithm recovers eigenvalues of quantum mechanical Hessians constituting the minimum energy path (MEP) of a reaction using only a small sample of the information, by leveraging underlying properties of these eigenvalues. In addition to the low-rank property that constitutes the basis for most matrix completion (MC) algorithms, this work introduces a polynomial constraint in the objective function. This enables us to sample matrix columns unlike most conventional MC methods that can only sample elements, which makes PVMC readily compatible with quantum chemistry calculations as sampling a single column requires one Hessian calculation. For various types of reactions─SN2, hydrogen atom transfer, metal-ligand cooperative catalysis, and enzyme chemistry─we demonstrate that PVMC on average requires only six to seven Hessian calculations to accurately predict both quantum and variational effects.

Organic photoredox catalysts for CO2 reduction: Driving discovery with genetic algorithms.

This work implements a genetic algorithm (GA) to discover organic catalysts for photoredox CO2 reduction that are both highly active and resistant to degradation. The lowest unoccupied molecular orbital energy of the ground state catalyst is chosen as the activity descriptor and the average Mulliken charge on all ring carbons is chosen as the descriptor for resistance to degradation via carboxylation (both obtained using density functional theory) to construct the fitness function of the GA. We combine the results of multiple GA runs, each based on different relative weighting of the two descriptors, and rigorously assess GA performance by calculating electron transfer barriers to CO2 reduction. A large majority of GA predictions exhibit improved performance relative to experimentally studied o-, m-, and p-terphenyl catalysts. Based on stringent cutoffs imposed on the average charge, barrier to electron transfer to CO2, and excitation energy, we recommend 25 catalysts for further experimental investigation of viability toward photoredox CO2 reduction.

A matrix completion algorithm for efficient calculation of quantum and variational effects in chemical reactions.

This work examines the viability of matrix completion methods as cost-effective alternatives to full nuclear Hessians for calculating quantum and variational effects in chemical reactions. The harmonic variety-based matrix completion (HVMC) algorithm, developed in a previous study [S. J. Quiton et al., J. Chem. Phys. 153, 054122 (2020)], exploits the low-rank character of the polynomial expansion of potential energy to recover vibrational frequencies (square roots of eigenvalues of nuclear Hessians) constituting the reaction path using a small sample of its entities. These frequencies are essential for calculating rate coefficients using variational transition state theory with multidimensional tunneling (VTST-MT). HVMC performance is examined for four SN2 reactions and five hydrogen transfer reactions, with each H-transfer reaction consisting of at least one vibrational mode strongly coupled to the reaction coordinate. HVMC is robust and captures zero-point energies, vibrational free energies, zero-curvature tunneling, and adiabatic ground state and free energy barriers as well as their positions on the reaction coordinate. For medium to large reactions involving H-transfer, with the sole exception of the most complex Ir catalysis system, less than 35% of total eigenvalue information is necessary for accurate recovery of key VTST-MT observables.

Modeling and Characterization of Exciplexes in Photoredox CO2 Reduction: Insights from Quantum Chemistry and Fluorescence Spectroscopy.

Interactions between excited-state arenes and amines can lead to the formation of structures with a distinct emission behavior. These excited-state complexes or exciplexes can reduce the ability of the arene to participate in other reactions, such as CO2 reduction, or increase the likelihood of degradation via Birch reduction. Exciplex geometries are necessary to understand photophysical behavior and probe degradation pathways but are challenging to calculate. We establish a detailed computational protocol for calculation, verification, and characterization of exciplexes. Using fluorescence spectroscopy, we first demonstrate the formation of exciplexes between excited-state oligo-(p-phenylene) (OPP), shown to successfully carry out CO2 reduction, and triethylamine. Time-dependent density functional theory is employed to optimize the geometries of these exciplexes, which are validated by comparing both emission energies and their solvatochromism with the experiment. Excited-state energy decomposition analysis confirms the predominant role played by charge transfer interactions in the red shift of emissions relative to the isolated excited-state OPP*. We find that although the exciplex emission frequency depends strongly on solvent dielectric, the extent of charge separation in an exciplex does not. Our results also suggest that the formation of solvent-separated ionic radical states upon complete electron transfer competes with exciplex formation in higher-dielectric solvents, thereby leading to reduced exciplex emission intensities in fluorescence experiments.

A computational study of the mechanism of chloroalkane dechlorination with Rh(I) complexes.

This work utilizes density functional theory and the energetic span model to determine steps constituting the catalytic cycle and turnover frequencies, respectively, for C(sp3)-Cl activation and dechlorination by model Rh(I) complexes containing POP-Pincer ligands with the aid of Na salts. The steps in the catalytic cycle with NaHCO2 as the hydrogen carrier are (i) rotation of the Rh-Cl bond out of the ligand plane, (ii) metal insertion into the C-Cl bond, (iii) formate binding and removal of one Cl as NaCl, (iv) formation and removal of CO2 from formate-bound Rh, and (v) hydrogenation of the alkyl bound to Rh to form an alkane, followed by Rh-Cl rotation to restore the catalyst resting state. We find that the the turnover-determining states and TOFs for monochloropropane (MCP) dechlorination depend strongly on the hydrogen carrier, with significantly higher TOF for NaH than NaHCO2. Therefore, NaH may be a promising salt for alkylchloride dechlorination with Rh(I) complexes.

Photoredox Chemistry with Organic Catalysts: Role of Computational Methods.

Organic catalysts have the potential to carry out a wide range of otherwise thermally inaccessible reactions via photoredox routes. Early demonstrated successes of organic photoredox catalysts include one-electron CO2 reduction and H2 generation via water splitting. Photoredox systems are challenging to study and design owing to the sheer number and diversity of phenomena involved, including light absorption, emission, intersystem crossing, partial or complete charge transfer, and bond breaking or formation. Designing a viable photoredox route therefore requires consideration of a host of factors such as absorption wavelength, solvent, choice of electron donor or acceptor, and so on. Quantum chemistry methods can play a critical role in demystifying photoredox phenomena. Using one-electron CO2 reduction with phenylene-based chromophores as an illustrative example, this perspective highlights recent developments in quantum chemistry that can advance our understanding of photoredox processes and proposes a way forward for driving the design and discovery of organic catalysts.

Perspective and challenges in electrochemical approaches for reactive CO2 separations.

The desire toward decarbonization and renewable energy has sparked research interests in reactive CO2 separations, such as direct air capture that utilize electricity as opposed to conventional thermal and pressure swing processes, which are energy-intensive, cost-prohibitive, and fossil-fuel dependent. Although the electrochemical approaches in CO2 capture that support negative emissions technologies are promising in terms of modularity, smaller footprint, mild reaction conditions, and possibility to integrate into conversion processes, their practice depends on the wider availability of renewable electricity. This perspective discusses key advances made in electrolytes and electrodes with redox-active moieties that reversibly capture CO2 or facilitate its transport from a CO2-rich side to a CO2-lean side within the last decade. In support of the discovery of new heterogeneous electrode materials and electrolytes with redox carriers, the role of computational chemistry is also discussed.

Probing the Ligand Exchange of N-Heterocyclic Carbene-Capped Ag2S Nanocrystals with Amines and Carboxylic Acids.

N-Heterocyclic carbenes (NHCs) are versatile L-type ligands that have been shown to stabilize coinage metal chalcogenide nanocrystals, such as Ag2S, remarkably well. However, very little research has been done on the interaction between NHC ligands and coinage metal chalcogenide nanocrystal surfaces and subsequent ligand exchange reactions. Herein, solution 1H nuclear magnetic resonance methods were used to monitor ligand exchange reactions on stoichiometric Ag2S nanocrystal platforms with various primary amine and carboxylic acid ligands. Despite the introduction of new ligands, the native NHC ligands remain tightly bound to the Ag2S nanocrystal surface and are not displaced at room temperature. Primary amine and carboxylic acid ligands demonstrated quantitative ligand exchange only after the samples had been heated with an excess incoming ligand, which implies a strong NHC-Ag binding energy. Density functional theory affirms that a model NHC ligand binds the strongest to a Ag12S6 cluster surface, followed by amine and carboxylic acid binding; computational analysis is therefore in line with the absence of NHC displacement observed in experiments. Both the bulky sterics of the C14-alkyl chains on the NHC and the high energies for the binding of NHC to the Ag2S surface contribute to the superior colloidal stability over conventional long-chain amine or carboxylic acid ligands (many months vs hours to days).

A framework for constructing linear free energy relationships to design molecular transition metal catalysts.

A computational framework for ligand-driven design of transition metal complexes is presented in this work. We propose a general procedure for the construction of active site-specific linear free energy relationships (LFERs), which are inspired from Hammett and Taft correlations in organic chemistry and grounded in the activation strain model (ASM). Ligand effects are isolated and quantified in terms of their contribution to interaction and strain energy components of ASM. Scalar descriptors that are easily obtainable are then employed to construct the complete LFER. We successfully demonstrate proof-of-concept by constructing and applying an LFER to CH activation with enzyme-inspired [Cu2O2]2+ complexes. The key benefit of using ASM is a built-in compensation or error cancellation between LFER prediction of interaction and strain terms, resulting in accurate barrier predictions for 37 of the 47 catalysts examined in this study. The LFER is also transferable with respect to level of theory and flexible towards the choice of reference system. The absence of interaction-strain compensation or poor model performance for the remaining systems is a consequence of the approximate nature of the chosen interaction energy descriptor and LFER construction of the strain term, which focuses largely on trends in substrate and not catalyst strain.

Adsorbate-assisted migration of the metal atom in atomically dispersed catalysts: An ab initio molecular dynamics study.

We present a phenomenological study of dynamical evolution of the active site in atomically dispersed catalysts in the presence of reaction intermediates associated with CO oxidation and low-temperature water-gas shift reaction. Using picosecond ab initio molecular dynamics, we probe the initiation of adsorbate-induced diffusion of atomically dispersed platinum on rutile TiO2(110). NVT trajectories spanning 5 ps at 500 K reveal that the dynamical stability of the metal atom is governed by its local coordination to the support and adsorbate. Adsorbates that bind the strongest to Pt typically also lead to the fastest diffusion of the metal atom, and all adsorbates weaken Pt-support interactions, resulting in higher diffusion coefficients compared to bare Pt. We note, however, the absence of quantitative correlations between adsorption characteristics (Pt Bader charge, adsorbate binding energy) and ensemble-averaged quantities (diffusion coefficients). A recurring structural motif identified in several trajectories is a near-linear coordination between support oxygen, Pt, and specific adsorbates. These geometries, on account of enhanced metal support interactions, stabilize Pt and inhibit migration over picosecond timescales. We also identify hydrogen bonding events between the adsorbate and support for OH-containing groups. In the case of OH-bound Pt, for instance, we believe that short-lived H-bonds between OH and support promote Pt migration in the beginning of the NVT trajectory, while the subsequent formation of a near-linear geometry stabilizes the Pt atom despite the continued formation of short-lived hydrogen bonds. These observations are consistent with prior studies that report stabilization of isolated metal atoms in the presence of hydroxyl groups.

A matrix completion algorithm to recover modes orthogonal to the minimum energy path in chemical reactions.

Structured statistical methods are promising for recovering or completing information from noisy and incomplete data with high fidelity. In particular, matrix completion exploits underlying structural properties such as rank or sparsity. Our objective is to employ matrix completion to reduce computational effort associated with the calculation of multiple quantum chemical Hessians, which are necessary for identification of temperature-dependent free energy maxima under canonical variational transition state theory (VTST). We demonstrate proof-of-principle of an algebraic variety-based matrix completion method for recovering missing elements in a matrix of transverse Hessian eigenvalues constituting the minimum energy path (MEP) of a reaction. The algorithm, named harmonic variety-based matrix completion (HVMC), utilizes the fact that the points lying on the MEP of a reaction step constitute an algebraic variety in the reaction path Hamiltonian representation. We demonstrate that, with as low as 30% random sampling of matrix elements for the largest system in our test set (46 atoms), the complete matrix of eigenvalues can be recovered. We further establish algorithm performance for VTST rate calculations by quantifying errors in zero-point energies and vibrational free energies. Motivated by this success, we outline next steps toward developing a practical HVMC algorithm, which utilizes a gradient-based sampling protocol for low-cost VTST rate computations.