Benchmarking two-body contributions to crystal lattice energies and a range-dependent assessment of approximate methods.

Using the many-body expansion to predict crystal lattice energies (CLEs), a pleasantly parallel process, allows for flexibility in the choice of theoretical methods. Benchmark-level two-body contributions to CLEs of 23 molecular crystals have been computed using interaction energies of dimers with minimum inter-monomer separations (i.e., closest contact distances) up to 30 Å. In a search for ways to reduce the computational expense of calculating accurate CLEs, we have computed these two-body contributions with 15 different quantum chemical levels of theory and compared these energies to those computed with coupled-cluster in the complete basis set (CBS) limit. Interaction energies of the more distant dimers are easier to compute accurately and several of the methods tested are suitable as replacements for coupled-cluster through perturbative triples for all but the closest dimers. For our dataset, sub-kJ mol-1 accuracy can be obtained when calculating two-body interaction energies of dimers with separations shorter than 4 Å with coupled-cluster with single, double, and perturbative triple excitations/CBS and dimers with separations longer than 4 Å with MP2.5/aug-cc-pVDZ, among other schemes, reducing the number of dimers to be computed with coupled-cluster by as much as 98%.

Benchmark coupled-cluster lattice energy of crystalline benzene and assessment of multi-level approximations in the many-body expansion.

The many-body expansion (MBE) is promising for the efficient, parallel computation of lattice energies in organic crystals. Very high accuracy should be achievable by employing coupled-cluster singles, doubles, and perturbative triples at the complete basis set limit [CCSD(T)/CBS] for the dimers, trimers, and potentially tetramers resulting from the MBE, but such a brute-force approach seems impractical for crystals of all but the smallest molecules. Here, we investigate hybrid or multi-level approaches that employ CCSD(T)/CBS only for the closest dimers and trimers and utilize much faster methods like Møller-Plesset perturbation theory (MP2) for more distant dimers and trimers. For trimers, MP2 is supplemented with the Axilrod-Teller-Muto (ATM) model of three-body dispersion. MP2(+ATM) is shown to be a very effective replacement for CCSD(T)/CBS for all but the closest dimers and trimers. A limited investigation of tetramers using CCSD(T)/CBS suggests that the four-body contribution is entirely negligible. The large set of CCSD(T)/CBS dimer and trimer data should be valuable in benchmarking approximate methods for molecular crystals and allows us to see that a literature estimate of the core-valence contribution of the closest dimers to the lattice energy using just MP2 was overbinding by 0.5 kJ mol-1, and an estimate of the three-body contribution from the closest trimers using the T0 approximation in local CCSD(T) was underbinding by 0.7 kJ mol-1. Our CCSD(T)/CBS best estimate of the 0 K lattice energy is -54.01 kJ mol-1, compared to an estimated experimental value of -55.3 ± 2.2 kJ mol-1.

X-ray Fiber Diffraction and Computational Analyses of Stacked Hexads in Supramolecular Polymers: Insight into Self-Assembly in Water by Prospective Prebiotic Nucleobases.

Aqueous solutions of equimolar mixtures of 2,4,6-triaminopyrimidine (TAP) and carboxylic acid substituted cyanuric acid (CyCo6 or R-4MeCyCo6) monomers self-assemble into gel-forming supramolecular polymers. Macroscopic fibers drawn from these mixtures were analyzed by X-ray diffraction to determine their molecular structures. Computational methods were used to explore the intrinsic intermolecular interactions that contribute to the structure and stability of these assemblies. Both polymers are formed by the stacking of hexameric rosettes, (TAP/CyCo6)3 or (TAP/R-4MeCyCo6)3, respectively, into long, stiff, twisted stacks of essentially planar rosettes. Chiral, left-handed supramolecular polymers with a helical twist angle of -26.7° per hexad are formed when the pure enantiomer R-4MeCyCo6 is used. These hexad stacks pack into bundles with a hexagonal crystalline lattice organization perpendicular to the axis of the macroscopic fiber. Polymers formed from TAP and CyCo6, both of which are achiral, assemble into macroscopic domains that are packed as a centered rectangular lattice. Within these domains, the individual polymers exist as either right-handed or left-handed helical stacks, with twist angles of +15° or -15° per hexad, respectively. The remarkable ability of TAP and cyanuric acid derivatives to self-assemble in water, and the structural features of their supramolecular polymers reported here, provide additional support for the proposal that these heterocycles could have served as recognition units for an early form of nucleic acids, before the emergence of RNA.

Interaction of Polymers with Enzalutamide Nanodroplets-Impact on Droplet Properties and Induction Times.

Amorphous solid dispersions (ASDs), which consist of a drug dispersed in a polymeric matrix, are increasingly being applied to improve the in vivo performance of poorly water-soluble drugs delivered orally. The polymer is a critical component, playing several roles including facilitating drug release from the ASD, as well as delaying crystallization from the supersaturated solution generated upon dissolution. Certain ASD formulations dissolve to produce amorphous drug-rich nanodroplets. The interaction of the polymer with these nanodroplets is poorly understood but is thought to be important for inhibiting crystallization in these systems. In this study, the impact of ionic polymers on the crystallization kinetics of enzalutamide from supersaturated solutions containing different amounts of amorphous nanodroplets was evaluated by determination of nucleation induction times. The amount of the polymer associated with the drug nanodroplets was also determined. When comparing two polymers, hydroxypropylmethyl cellulose acetate succinate (HPMCAS) and Eudragit E PO, it was found that the crystallization tendency and physical properties of the drug nanodroplets varied in the presence of these two polymers. Both polymers distributed between the aqueous phase and the drug-rich nanodroplets. A greater amount of Eudragit E PO was associated with the drug-rich nanodroplets. Despite this, Eudragit E PO was a less-effective crystallization inhibitor than HPMCAS in systems containing nanodroplets. In conclusion, in supersaturated solutions containing amorphous nanodroplets, the extent of association of a polymer with the drug nanodroplet does not solely predict crystallization inhibition.

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.

Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.

Domain Separated Density Functional Theory for Reaction Energy Barriers and Optical Excitations.

We recently proposed domain separated density functional theory (DS-DFT), a framework that allows for the combination of different levels of theory for the computation of the electronic structure of molecules. This work discusses the application of DS-DFT to the computation of transition-state energy barriers and optical absorption spectra. We considered several hydrogen abstraction reactions and optical spectra of molecule/metal cluster systems, including the absorption of individual species such as carbon monoxide, methane, and molecular hydrogen to a Li6 cluster. We present and discuss two domain-separated methods: (i), the screened-density approximation (SDA) and (ii) linearly weighted exchange (LWE). We find that SDA, which is applied as a hybridization based on atomic domains, could be useful to computing energy barriers, whereas LWE is suited for the analysis of electronic properties such as ground-state gaps, excitation energies, and oscillator strengths.

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems.

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light-matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials).

Domain Separation in Density Functional Theory.

Research within density functional theory (DFT) has led to a large set of conceptual and computational methodologies to explore and understand the electronic structure of molecules and solids. Among the most commonly employed techniques in DFT are those of hybrid functionals, which are capable of producing accurate results for diverse properties, with notable exceptions. However, other techniques have been proposed to address limitations in the application of conventional hybrid functional techniques, especially to cases where a single reference is insufficient to achieve a proper description of the system of interest. In this paper we consider several previous developments in the field for the combination of local and nonlocal potentials and show that they can be formalized within the constrained-search Levy formalism, offering routes and ideas for the development of (nontraditional) density functionals, especially for treating strongly correlated regions of a molecule. The proposed formalism is centered around the idea of decomposing into domains the differential volume elements that are present in the definition of the electronic repulsion operator, which is contained in the electronic Hamiltonian, but this can also be applied to other operators as well. We show that the domain decomposition leads to a formulation that allows for the combination of different theories: DFT, correlated wave function theory, and Hartree-Fock, among others. This combination could accelerate the computation of electronic properties and allow for explicit inclusion, at the wave function level, of correlation effects, as in configuration-interaction theory. Our discussion covers both single- and multideterminantal methods. We demonstrate the approach through a simple application to the electronic structure of the methane and ethylene molecules, in which nonlocal exchange is applied to a given set of atoms, or domains, with the remaining atoms modeled with the local density approximation.

CrystaLattE: Automated computation of lattice energies of organic crystals exploiting the many-body expansion to achieve dual-level parallelism.

We present an algorithm to compute the lattice energies of molecular crystals based on the many-body cluster expansion. The required computations on dimers, trimers, etc., within the crystal are independent of each other, leading to a naturally parallel approach. The algorithm exploits the long-range three-dimensional periodic order of crystals to automatically detect and avoid redundant or unnecessary computations. For this purpose, Coulomb-matrix descriptors from machine learning applications are found to be efficient in determining whether two N-mers are identical. The algorithm is implemented as an open-source Python program, CrystaLattE, that uses some of the features of the Quantum Chemistry Common Driver and Databases library. CrystaLattE is initially interfaced with the quantum chemistry package Psi4. With CrystaLattE, we have applied the fast, dispersion-corrected Hartree-Fock method HF-3c to the lattice energy of crystalline benzene. Including all 73 symmetry-unique dimers and 7130 symmetry-unique trimers that can be formed from molecules within a 15 Å cutoff from a central reference monomer, HF-3c plus an Axilrod-Teller-Muto estimate of three-body dispersion exhibits an error of only -1.0 kJ mol-1 vs the estimated 0 K experimental lattice energy of -55.3 ± 2.2 kJ mol-1. The convergence of the HF-3c two- and three-body contributions to the lattice energy as a function of intermonomer distance is examined.

Phase Behavior of Drug-Hydroxypropyl Methylcellulose Amorphous Solid Dispersions Produced from Various Solvent Systems: Mechanistic Understanding of the Role of Polymer using Experimental and Theoretical Methods.

The vast majority of studies evaluating amorphous solid dispersions (ASDs) utilize solvent evaporation techniques as the preparation method. However, the impact of the solvent/cosolvent system properties on the polymer conformation and the phase behavior of the resultant drug/polymer blends is poorly understood. Herein, we investigate the influence of solvent properties on the phase behavior of ASDs containing itraconazole (ITZ) and hydroxypropylmethyl cellulose (HPMC) prepared using spin coating from binary/ternary cosolvent systems containing alkyl alcohols, dichloromethane (DCM), and water. The compatibility of the polymer with the cosolvent system was probed using high-resolution imaging techniques supported by molecular dynamics simulations. Solvent evaporation and evaporation rate profiles were tracked gravimetrically to understand the impact of the solvent composition on the evaporation process. Short-chain alcohols, including methanol (MeOH) and ethanol (EtOH), were found to induce drug-polymer demixing in the presence of water, with EtOH being less sensitive to moisture than MeOH owing to its ability to form an azeotrope with water. In contrast, water-induced mixing was observed when higher alcohols, including n-propanol (PrOH) and n-butanol (BuOH), were used as a cosolvent, due to the improved solubility of HPMC in the higher alcohols in the presence of water. Isopropanol (IPA) produced phase separated ASDs under wet and dry conditions with an increase in miscibility with faster evaporation rates in the presence of water. This solvent-triggered phase behavior highlights the importance of conducting a thorough screening of various solvents prior to the preparation of ASDs via solvent evaporation approaches such as spray drying.

Crystallization Inhibition Properties of Cellulose Esters and Ethers for a Group of Chemically Diverse Drugs: Experimental and Computational Insight.

Amorphous solid dispersions are widely used to enhance the oral bioavailability of poorly water-soluble drugs. Polymeric additives are commonly used to delay crystallization of the drug from the supersaturated solutions formed upon ASD dissolution by influencing the nucleation and growth of crystals. However, there is limited evidence regarding the mechanisms by which polymers stabilize supersaturated drug solutions. The current study used experiments and computational modeling to explore polymer-drug interactions in aqueous solutions. Nucleation induction times for supersaturated solutions of nine drugs in the presence of five newly synthesized cellulose-based polymers were evaluated. The polymers had carboxylic acids substituents with additional variations in the side-chain structure: (1) one with a single side chain and a carboxylic acid termination, (2) three with a branched side chain terminated with a carboxylic and an alcohol group (varying the cellulose linkage and the length of the hydrocarbon side chain), and (3) one with a branched side chain with two carboxylic acid end groups. The polymers with a short side chain and one carboxylic acid were effective, whereas the polymers with the two carboxylic acids or a long hydrocarbon chain were less effective. Atomic force microscopy experiments, evaluating polymer adsorption onto amorphous drug films, indicated that the effective polymers were uniformly spread across the surface. These results were supported by molecular dynamics simulations of a polymer chain in the presence of a drug aggregate in an aqueous environment, whereby the effective materials had a higher probability of establishing close contacts and more negative estimated free energies of interaction. The insights provided by this study provide approaches to design highly effective polymers to improve oral drug delivery.

Mechanistic Design of Chemically Diverse Polymers with Applications in Oral Drug Delivery.

Polymers play a key role in stabilizing amorphous drug formulations, a recent strategy employed to improve solubility and bioavailability of drugs delivered orally. However, the molecular mechanism of stabilization is unclear, therefore, the rational design of new crystallization-inhibiting excipients remains a substantial challenge. This article presents a combined experimental and computational approach to elucidate the molecular features that improve the effectiveness of cellulose polymers as solution crystallization inhibitors, a crucial first step toward their rational design. Polymers with chemically diverse substituents including carboxylic acids, esters, ethers, alcohols, amides, amines, and sulfides were synthesized. Measurements of nucleation induction times of the model drug, telaprevir, show that the only effective polymers contained carboxylate groups in combination with an optimal hydrocarbon chain length. Computational results indicate that polymer conformation as well as solvation free energy are important determinants of effectiveness at inhibiting crystallization and show that simulations are a promising predictive tool in the screening of polymers. This study suggests that polymers need to have an adequate hydrophilicity to promote solvation in an aqueous environment, and sufficient hydrophobic regions to drive interactions with the drug. Particularly, the right balance between key substituent groups and lengths of hydrocarbon side chains is needed to create effective materials.

Ground-State Charge Transfer: Lithium-Benzene and the Role of Hartree-Fock Exchange.

Most approximations to the exchange-correlation functional of Kohn-Sham density functional theory lead to delocalization errors that undermine the description of charge-transfer phenomena. We explore how various approximate functionals and charge-distribution schemes describe ground-state atomic-charge distributions in the lithium-benzene complex, a model system of relevance to carbon-based supercapacitors. To understand the trends, we compare Hartree-Fock (HF) and correlated post-HF calculations, confirming that the HOMO-LUMO gap is narrower in semilocal functionals but widened by hybrid functionals with large fractions of HF exchange. For semilocal functionals, natural bond orbital (NBO) and Mulliken schemes yield opposite pictures of how charge transfer occurs. In PBE, for example, when lithium and benzene are <1.5 Å apart, NBO yields a positive charge on the lithium atom, but the Mulliken scheme yields a negative charge. Furthermore, the partial charges in conjugated materials depend on the interplay between the charge-distribution scheme employed and the underlying exchange-correlation functional, being critically sensitive to the admixture of HF exchange. We analyze and explain why this happens, discuss implications, and conclude that hybrid functionals with an admixture of about one-fourth of HF exchange are particularly useful in describing charge transfer in the lithium-benzene model.

Connection between Hybrid Functionals and Importance of the Local Density Approximation.

The exchange-correlation (XC) local density approximation (LDA) is the original density functional used to investigate the electronic structure of molecules and solids within the formulation of Kohn and Sham. The LDA is fundamental for the development of density-functional approximations. In this work we consider the generalized Kohn-Sham (GKS) theory of hybrid functionals. The GKS formalism is an extension of the Kohn-Sham theory for electronic ground states and leads to a vast set of alternative density functionals, which can be estimated by the LDA and related methods. Herein we study auxiliary electronic systems with parametrized interactions and derive (i) a set of exact equations relating the GKS XC energies in the parameter space and (ii) a formal relation between the parameters and the standard XC derivative discontinuity. In view of the new results and previously reported findings, we discuss why the inclusion of Fock exchange, and its long-range-corrected form (in the ground-state calculations and in linear-response Kohn-Sham equations), dominate over the generalized gradient corrections to enhance the quality of the fundamental gap and to enhance excitation-energy estimations. As an example, we show that the adiabatic CAM-LDA0 (a functional with 1/4 global and 1/2 long-range Hartree-Fock interaction, respectively, a range separation factor of 1/3, and pure LDA exchange and correlation) works for electronic excitations as well as the adiabatic CAM-B3LYP functional.

Excited-state charge polarization and electronic structure of mixed-cation halide perovskites: the role of mixed inorganic-organic cations in CsFAPbI3.

Mixed-cation perovskite materials have shown great potential for sunlight harvesting and have surpassed unmixed perovskite materials in solar cell efficiency and stability. The role of mixed monovalent cations in the enhanced optoelectronic properties and excited state response, however, are still elusive from a theoretical perspective. Herein, through time dependent density functional theory calculations of mixed cation perovskites, we report the electronic structure of Cs formamidinium (FA) mixed cationic lead iodide (Cs0.17FA0.87PbI3) in comparison to the corresponding single monovalent cation hybrid perovskite. The results show that the Cs0.17FA0.87PbI3 and FAPbI3 had negligible differences in the optical band gap, and partial and total density of states in comparison to a single cation perovskite, while the effective mass of carriers, the local atomic density of states, the directional transport, and the structural distortions were significantly different. A lattice-distortion-induced asymmetry in the ground-state charge density is found, and originates from the co-location of caesium atoms in the lattice and signifies the effect on the charge density upon cation mixing and corresponding symmetry breaking. The excited-state charge response and induced polarizabilities are quantified, and discussed in terms of their importance for effective light absorption, charge separation, and final solar cell performance. We also quantify the impact of such polarizabilities on the dynamics of the structure of the perovskites and the implications this has for hot carrier cooling. The results shed light on the mechanism and origin of the enhanced performance in mixed-cation perovskite-based devices and their merits in comparison to single cation perovskites.

Machine Learning on a Robotic Platform for the Design of Polymer-Protein Hybrids.

Polymer-protein hybrids are intriguing materials that can bolster protein stability in non-native environments, thereby enhancing their utility in diverse medicinal, commercial, and industrial applications. One stabilization strategy involves designing synthetic random copolymers with compositions attuned to the protein surface, but rational design is complicated by the vast chemical and composition space. Here, a strategy is reported to design protein-stabilizing copolymers based on active machine learning, facilitated by automated material synthesis and characterization platforms. The versatility and robustness of the approach is demonstrated by the successful identification of copolymers that preserve, or even enhance, the activity of three chemically distinct enzymes following exposure to thermal denaturing conditions. Although systematic screening results in mixed success, active learning appropriately identifies unique and effective copolymer chemistries for the stabilization of each enzyme. Overall, this work broadens the capabilities to design fit-for-purpose synthetic copolymers that promote or otherwise manipulate protein activity, with extensions toward the design of robust polymer-protein hybrid materials.

Machine-Assisted Discovery of Chondroitinase ABC Complexes toward Sustained Neural Regeneration.

Among the many molecules that contribute to glial scarring, chondroitin sulfate proteoglycans (CSPGs) are known to be potent inhibitors of neuronal regeneration. Chondroitinase ABC (ChABC), a bacterial lyase, degrades the glycosaminoglycan (GAG) side chains of CSPGs and promotes tissue regeneration. However, ChABC is thermally unstable and loses all activity within a few hours at 37 °C under dilute conditions. To overcome this limitation, the discovery of a diverse set of tailor-made random copolymers that complex and stabilize ChABC at physiological temperature is reported. The copolymer designs, which are based on chain length and composition of the copolymers, are identified using an active machine learning paradigm, which involves iterative copolymer synthesis, testing for ChABC thermostability upon copolymer complexation, Gaussian process regression modeling, and Bayesian optimization. Copolymers are synthesized by automated PET-RAFT and thermostability of ChABC is assessed by retained enzyme activity (REA) after 24 h at 37 °C. Significant improvements in REA in three iterations of active learning are demonstrated while identifying exceptionally high-performing copolymers. Most remarkably, one designed copolymer promotes residual ChABC activity near 30%, even after one week and notably outperforms other common stabilization methods for ChABC. Together, these results highlight a promising pathway toward sustained tissue regeneration.

Molecular Dynamics of a Water-Absorbent Nanoscale Material Based on Chitosan.

Although hydrogels have been widely investigated for their use in materials science, nanotechnology, and novel pharmaceuticals, mechanistic details explaining their water-absorbent features are not well understood. We performed an all-atom molecular dynamics study of the structural transformation of chitosan nanohydrogels due to water absorption. We analyzed the conformation of dry, nanoscaled chitosan, the structural modifications that emerge during the process of water inclusion, and the dynamics of this biopolymer in the presence of nature's solvent. Two sets of nanoscaled, single-chained chitosan models were simulated: one to study the swelling dependence upon the degree of self-cross-linking and other to observe the response with respect to the degree of protonation. We verified that nanohydrogels keep their ability to absorb water and grow, regardless of their degree of cross-linking. Noteworthy, we found that the swelling behavior of nanoscaled chitosan is pH-dependent, and it is considerably more limited than that of larger scale hydrogels. Thus, our study suggests that properties of nanohydrogels are significantly different from those of larger hydrogels. These findings might be important in the design of novel controlled-release and targeted drug-delivery systems based on chitosan.