Kohn-Sham Density in a Slater Orbital Basis Set.

Finite, atom-centered Slater basis sets are used to determine approximate Kohn-Sham molecular orbitals. This is achieved by minimizing the kinetic energy plus the sum-squared difference between the Kohn-Sham density and the full configuration interaction density. As a result of the finite basis, a weight factor is introduced to balance the two minimization components. Results herein show that this can be done systematically, without sensitive dependence on the choice of scaling factor. In addition, the algorithm is applied to the LiH diatomic for fractional electron counts, where stretching the bond introduces significant reorganization of the electron density. The analysis will show the correct KS orbital structure and reveal the effects of correlation and electron locality on the KS solutions.

Substrate-Selective Catalysis Enabled Synthesis of Azaphilone Natural Products.

Achieving substrate-selectivity is a central element of nature's approach to synthesis. By relying on the ability of a catalyst to discriminate between components in a mixture, control can be exerted over which molecules will move forward in a synthesis. This approach can be powerful when realized but can be challenging to duplicate in the laboratory. In this work, substrate-selective catalysis is leveraged to discriminate between two intermediates that exist in equilibrium, subsequently directing the final cyclization to arrive at either the linear or angular tricyclic core common to subsets of azaphilone natural products. By using a flavin-dependent monooxygenase (FDMO) in sequence with an acyl transferase (AT), the conversion of several orcinaldehyde substrates directly to the corresponding linear tricyclic azaphilones in a single reaction vessel was achieved. Further, mechanistic studies support that a substrate equilibrium together with enzyme substrate selectivity play an import role in the selectivity of the final cyclization step. Using this strategy, five azaphilone natural products were synthesized for the first time as well as a number of unnatural derivatives thereof.

Green Light Promoted Iridium(III)/Copper(I)-Catalyzed Addition of Alkynes to Aziridinoquinoxalines Through the Intermediacy of Azomethine Ylides.

This manuscript describes the development of alkyne addition to the aziridine moiety of aziridinoquinoxalines using dual Ir(III)/Cu(I) catalytic system under green light-emitting diode (LED) photolysis (λmax =525 nm). This mild method features high levels of chemo- and regioselectivity and was used to generate 30 highly functionalized substituted dihydroquinoxalines in 36-98 % yield. This transformation was also carried asymmetrically using phthalazinamine-based chiral ligand to provide 9 chiral addition products in 96 : 4 to 86 : 14 e.r. The experimental and quantum chemical explorations of this reaction suggest a mechanism that involves Ir(III)-catalyzed triplet energy transfer followed by a ring-opening reaction ultimately leading to the formation of azomethine ylide intermediates. These azomethine intermediates undergo sequential protonation/copper(I) acetylide addition to provide the products.

Conformational Sampling over Transition-Metal-Catalyzed Reaction Pathways: Toward Revealing Atroposelectivity.

The Py-Conformational-Sampling (PyCoSa) technique is introduced as a systematic computational means to sample the configurational space of transition-metal-catalyzed stereoselective reactions. When applied to atroposelective Suzuki-Miyaura coupling to create axially chiral biaryl products, the results show a range of mechanistic possibilities that include multiple low-energy channels through which C-C bonds can be formed.

Simulating Electron Transfer Reactions in Solution: Radical-Polar Crossover.

Single-electron transfer (SET) promotes a wide variety of interesting chemical transformations, but modeling of SET requires a careful treatment of electronic and solvent effects to give meaningful insight. Therefore, a combined constrained density functional theory and molecular mechanics (CDFT/MM) tool is introduced specifically for SET-initiated reactions. Mechanisms for two radical-polar crossover reactions involving the organic electron donors tetrakis(dimethylamino)ethylene (TDAE) and tetrathiafulvalene (TTF) were studied with the new tool. An unexpected tertiary radical intermediate within the TDAE system was identified, relationships between kinetics and substitution in the TTF system were explained, and the impact of the solvent environments on the TDAE and TTF reactions were examined. The results highlight the need for including solvent dynamics when quantifying SET kinetics and thermodynamics, as a free energy difference of >20 kcal/mol was observed. Overall, the new method informs mechanistic analysis of SET-initiated reactions and therefore is envisioned to be useful for studying reactions in the condensed phase.

Exact and Model Exchange-Correlation Potentials for Open-Shell Systems.

The conventional approaches to the inverse density functional theory problem typically assume nondegeneracy of the Kohn-Sham (KS) eigenvalues, greatly hindering their use in open-shell systems. We present a generalization of the inverse density functional theory problem that can seamlessly admit degenerate KS eigenvalues. Additionally, we allow for fractional occupancy of the Kohn-Sham orbitals to also handle noninteracting ensemble-v-representable densities, as opposed to just noninteracting pure-v-representable densities. We present the exact exchange-correlation (XC) potentials for six open-shell systems─four atoms (Li, C, N, and O) and two molecules (CN and CH2)─using accurate ground-state densities from configuration interaction calculations. We compare these exact XC potentials with model XC potentials obtained using nonlocal (B3LYP, SCAN0) and local/semilocal (SCAN, PBE, PW92) XC functionals. Although the relative errors in the densities obtained from these DFT functionals are of O(10-3 to 10-2), the relative errors in the model XC potentials remain substantially large─O(10-1 to 100).

Tetrafluorenofulvalene as a sterically frustrated open-shell alkene.

Electronic and steric effects are known to greatly influence the structure, characteristics and reactivity of organic compounds. A typical π bond is weakened by oxidation (corresponding to the removal of electrons from bonding orbitals), by reduction (through addition of electrons to antibonding orbitals) and by unpairing of the bonding electrons, such as in the triplet state. Here we describe tetrafluorenofulvalene (TFF), a twisted, open-shell alkene for which these general rules do not hold. Through the synthesis, experimental characterization and computational analysis of its charged species spanning seven redox states, the central alkene bond in TFF is shown to become substantially stronger in the tri- and tetraanion, generated by chemical reduction. Furthermore, although its triplet state contains a weaker alkene bond than the singlet, in the quintet state its bond order increases substantially, yielding a flatter structure. This behaviour originates from the doubly bifurcated topology of the underlying spin system and can be rationalized by the balancing effects of benzenoid aromaticity and spin pairing.

A Perspective on Sustainable Computational Chemistry Software Development and Integration.

The power of quantum chemistry to predict the ground and excited state properties of complex chemical systems has driven the development of computational quantum chemistry software, integrating advances in theory, applied mathematics, and computer science. The emergence of new computational paradigms associated with exascale technologies also poses significant challenges that require a flexible forward strategy to take full advantage of existing and forthcoming computational resources. In this context, the sustainability and interoperability of computational chemistry software development are among the most pressing issues. In this perspective, we discuss software infrastructure needs and investments with an eye to fully utilize exascale resources and provide unique computational tools for next-generation science problems and scientific discoveries.

Oxidative Cross Dehydrogenative Coupling of N-Heterocycles with Aldehydes through C(sp3)-H Functionalization.

Existing methodologies for metal-catalyzed cross-couplings typically rely on preinstallation of reactive functional groups on both reaction partners. In contrast, C-H functionalization approaches offer promise in simplification of the requisite substrates; however, challenges from low reactivity and similar reactivity of various C-H bonds introduce considerable complexity. Herein, the oxidative cross dehydrogenative coupling of α-amino C(sp3)-H bonds and aldehydes to produce ketone derivatives is described using an unusual reaction medium that incorporates the simultaneous use of di-tert-butyl peroxide as an oxidant and zinc metal as a reductant. The method proceeds with a broad substrate scope, representing an attractive approach for accessing α-amino ketones through the formal acylation of C-H bonds α to nitrogen in N-heterocycles. A combination of experimental investigation and computational modeling provides evidence for a mechanistic pathway involving cross-selective nickel-mediated cross-coupling of α-amino radicals and acyl radicals.

Exchange correlation potentials from full configuration interaction in a Slater orbital basis.

Ryabinkin-Kohut-Staroverov (RKS) theory builds a bridge between wave function theory and density functional theory by using quantities from the former to produce accurate exchange-correlation potentials needed by the latter. In this work, the RKS method is developed and tested alongside Slater atomic orbital basis functions for the first time. To evaluate this approach, full configuration interaction computations in the Slater orbital basis are employed to give quality input to RKS, allowing full correlation to be present along with correct nuclei cusps and asymptotic decay of the wavefunction. SlaterRKS is shown to be an efficient algorithm to arrive at exchange-correlation potentials without unphysical artifacts in moderately-sized basis sets. Furthermore, enforcement of the nuclear cusp conditions will be shown to be vital for the success of the Slater-basis RKS method. Examples of weakly and strongly correlated molecular systems will demonstrate the main features of SlaterRKS.

Controlling Catalyst Behavior in Lewis Acid-Catalyzed Carbonyl-Olefin Metathesis.

Lewis acid-catalyzed carbonyl-olefin metathesis has introduced a new means for revealing the behavior of Lewis acids. In particular, this reaction has led to the observation of new solution behaviors for FeCl3 that may qualitatively change how we think of Lewis acid activation. For example, catalytic metathesis reactions operate in the presence of superstoichiometric amounts of carbonyl, resulting in the formation of highly ligated (octahedral) iron geometries. These structures display reduced activity, decreasing catalyst turnover. As a result, it is necessary to steer the Fe-center away from inhibiting pathways to improve the reaction efficiency and augment yields for recalcitrant substrates. Herein, we examine the impact of the addition of TMSCl to FeCl3-catalyzed carbonyl-olefin metathesis, specifically for substrates that are prone to byproduct inhibition. Through kinetic, spectroscopic, and colligative experiments, significant deviations from the baseline metathesis reactivity are observed, including mitigation of byproduct inhibition as well as an increase in the reaction rate. Quantum chemical simulations are used to explain how TMSCl induces a change in catalyst structure that leads to these kinetic differences. Collectively, these data are consistent with the formation of a silylium catalyst, which induces the reaction through carbonyl binding. The FeCl3 activation of Si-Cl bonds to give the silylium active species is expected to have significant utility in enacting carbonyl-based transformations.

Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit.

Machine learning models are increasingly being utilized to predict outcomes of organic chemical reactions. A large amount of reaction data is used to train these models, which is in stark contrast to how expert chemists discover and develop new reactions by leveraging information from a small number of relevant transformations. Transfer learning and active learning are two strategies that can operate in low-data situations, which may help fill this gap and promote the use of machine learning for tackling real-world challenges in organic synthesis. This Perspective introduces active and transfer learning and connects these to potential opportunities and directions for further research, especially in the area of prospective development of chemical transformations.

Formal Cross-Coupling of Amines and Carboxylic Acids to Form sp3-sp2 Carbon-Carbon Bonds.

Amines and carboxylic acids are abundant synthetic building blocks that are classically united to form an amide bond. To access new pockets of chemical space, we are interested in the development of amine-acid coupling reactions that complement the amide coupling. In particular, the formation of carbon-carbon bonds by formal deamination and decarboxylation would be an impactful addition to the synthesis toolbox. Here, we report a formal cross-coupling of alkyl amines and aryl carboxylic acids to form C(sp3)-C(sp2) bonds following preactivation of the amine-acid building blocks as a pyridinium salt and N-acyl-glutarimide, respectively. Under nickel-catalyzed reductive cross-coupling conditions, a diversity of simple and complex substrates are united in good to excellent yield, and numerous pharmaceuticals are successfully diversified. High-throughput experimentation was leveraged in the development of the reaction and the discovery of performance-enhancing additives such as phthalimide, RuCl3, and GaCl3. Mechanistic investigations suggest phthalimide may play a role in stabilizing productive Ni complexes rather than being involved in oxidative addition of the N-acyl-imide and that RuCl3 supports the decarbonylation event, thereby improving reaction selectivity.

Advances in Parallel Heat Bath Configuration Interaction.

Heat-bath configuration interaction (HCI) is a deterministic method that approaches the full CI limit at greatly reduced computational cost. In this work, computational improvements to the HCI algorithm are introduced targeting speed, parallel efficiency, and memory requirements. The new implementation introduces a hash function to distribute determinants and takes advantage of MPI and OpenMP for parallelism allowing for a (22e,168o) active space to be studied, which explicitly includes 2.39 × 107 variational determinants and 8.95 × 1010 perturbative determinants. Benchmarks show up to 86% parallel efficiency of the perturbative step on 32 nodes (4096 cores) and a total efficiency of 74%. The new HCI implementation is benchmarked for accuracy against prior results and applied to study the triplet-quintet gap in the challenging [FeO(NH3)5]2+ complex.

Conformer-RL: A deep reinforcement learning library for conformer generation.

Conformer-RL is an open-source Python package for applying deep reinforcement learning (RL) to the task of generating a diverse set of low-energy conformations for a single molecule. The library features a simple interface to train a deep RL conformer generation model on any covalently bonded molecule or polymer, including most drug-like molecules. Under the hood, it implements state-of-the-art RL algorithms and graph neural network architectures tuned specifically for molecular structures. Conformer-RL is also a platform for researching new algorithms and neural network architectures for conformer generation, as the library contains modular class interfaces for RL environments and agents, allowing users to easily swap components with their own implementations. Additionally, it comes with tools to visualize and save generated conformers for further analysis. Conformer-RL is well-tested and thoroughly documented with tutorials for each of the functionalities mentioned above, and is available on PyPi and Github: https://github.com/ZimmermanGroup/conformer-rl.

The numerical evaluation of Slater integrals on graphics processing units.

This article presents SlaterGPU, a graphics processing unit (GPU) accelerated library that uses OpenACC to numerically compute Slater-type orbital (STO) integrals. The electron repulsion integrals (ERI) are computed under the RI approximation using the Coulomb potential of the Slater basis function. To fully realize the performance capabilities of modern GPUs, the Slater integrals are evaluated in mixed-precision, resulting in speedups for the ERIs of over 80×. Parallelization on multiple GPUs allows for integral throughput of over 3 million integrals per second. This places STO integral throughput within reach of single-threaded, conventional Gaussian integration schemes. To test the quality of the integrals, the fluorine exchange reaction barrier in fluoromethane was computed using heat-bath configuration interaction (HBCI). In addition, the singlet-triplet gap of cyclobutadiene was examined using HBCI in a triple- ζ , polarized basis set. These benchmarks demonstrate the library's ability to generate the full set of integrals necessary for configuration interaction with up to 6 h functions in the auxiliary basis.

Predicting reaction conditions from limited data through active transfer learning.

Transfer and active learning have the potential to accelerate the development of new chemical reactions, using prior data and new experiments to inform models that adapt to the target area of interest. This article shows how specifically tuned machine learning models, based on random forest classifiers, can expand the applicability of Pd-catalyzed cross-coupling reactions to types of nucleophiles unknown to the model. First, model transfer is shown to be effective when reaction mechanisms and substrates are closely related, even when models are trained on relatively small numbers of data points. Then, a model simplification scheme is tested and found to provide comparative predictivity on reactions of new nucleophiles that include unseen reagent combinations. Lastly, for a challenging target where model transfer only provides a modest benefit over random selection, an active transfer learning strategy is introduced to improve model predictions. Simple models, composed of a small number of decision trees with limited depths, are crucial for securing generalizability, interpretability, and performance of active transfer learning.

State-specific solvation for restricted active space spin-flip (RAS-SF) wave functions based on the polarizable continuum formalism.

The restricted active space spin-flip (RAS-SF) formalism is a particular form of single-reference configuration interaction that can describe some forms of strong correlation at a relatively low cost and which has recently been formulated for the description of charge-transfer excited states. Here, we introduce both equilibrium and nonequilibrium versions of a state-specific solvation correction for vertical transition energies computed using RAS-SF wave functions, based on the framework of a polarizable continuum model (PCM). Ground-state polarization is described using the solvent's static dielectric constant and in the nonequilibrium solvation approach that polarization is modified upon vertical excitation using the solvent's optical dielectric constant. Benchmark calculations are reported for well-studied models of photo-induced charge transfer, including naphthalene dimer, C2H4⋯C2F4, pentacene dimer, and perylene diimide (PDI) dimer, several of which are important in organic photovoltaic applications. For the PDI dimer, we demonstrate that the charge-transfer character of the excited states is enhanced in the presence of a low-dielectric medium (static dielectric constant ɛ0 = 3) as compared to a gas-phase calculation (ɛ0 = 1). This stabilizes mechanistic traps for singlet fission and helps to explain experimental singlet fission rates. We also examine the effects of nonequilibrium solvation on charge-separated states in an intramolecular singlet fission chromophore, where we demonstrate that the energetic ordering of the states changes as a function of solvent polarity. The RAS-SF + PCM methodology that is reported here provides a framework to study charge-separated states in solution and in photovoltaic materials.

Glycosyl Exchange of Unactivated Glycosidic Bonds: Suppressing or Embracing Side Reactivity in Catalytic Glycosylations.

While developing boron-catalyzed glycosylations using glycosyl fluoride donors and trialkylsilyl ether acceptors, competing pathways involving productive glycosylation or glycosyl exchange were observed. Experimental and computational mechanistic studies suggest a novel mode of reactivity where a dioxolenium ion is a key intermediate that promotes both pathways through addition to either a silyl ether or to the acetal of an existing glycosidic linkage. Modifications in catalyst structure enable either pathway to be favored, and with this understanding, improved multicomponent iterative couplings and glycosyl exchange processes were demonstrated.

Heavy atom oriented orbital angular momentum manipulation in metal-free organic phosphors.

Metal-free purely organic phosphors (POPs) are emerging materials for display technologies, solid-state lighting, and chemical sensors. However, due to limitations in contemporary design strategies, the intrinsic spin-orbit coupling (SOC) efficiency of POPs remains low and their emission lifetime is pinned in the millisecond regime. Here, we present a design concept for POPs where the two main factors that control SOC-the heavy atom effect and orbital angular momentum-are tightly coupled to maximize SOC. This strategy is bolstered by novel natural-transition-orbital-based computational methods to visualize and quantify angular momentum descriptors for molecular design. To demonstrate the effectiveness of this strategy, prototype POPs were created having efficient room-temperature phosphorescence with lifetimes pushed below the millisecond regime, which were enabled by boosted SOC efficiencies beyond 102 cm-1 and achieved record-high efficiencies in POPs. Electronic structure analysis shows how discrete tuning of heavy atom effects and orbital angular momentum is possible within the proposed design strategy, leading to a strong degree of control over the resulting POP properties.