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Ab initio predictions of chemical shifts and electric field gradient (EFG) tensor components are frequently used to help interpret solid-state nuclear magnetic resonance (NMR) experiments. Typically, these predictions employ density functional theory (DFT) with generalized gradient approximation (GGA) functionals, though hybrid functionals have been shown to improve accuracy relative to experiment. Here, the performance of a dozen models beyond the GGA approximation are examined for the prediction of solid-state NMR observables, including meta-GGA, hybrid, and double-hybrid density functionals and second-order Møller-Plesset perturbation theory (MP2). These models are tested on organic molecular crystal data sets containing 169 experimental 13C and 15N chemical shifts and 114 17O and 14N EFG tensor components. To make these calculations affordable, gauge-including projector augmented wave (GIPAW) Perdew-Burke-Ernzerhof (PBE) calculations with periodic boundary conditions are combined with a local intramolecular correction computed at the higher level of theory. Within the context of typical NMR property calculations performed on a static, DFT-optimized crystal structure, the benchmarking finds that the double-hybrid DFT functionals produce errors versus experiment that are no smaller than those of hybrid functionals in the best cases, and they can be larger. MP2 errors versus experiment are even bigger. Overall, no practical advantages are found for using any of the tested double-hybrid functionals or MP2 to predict experimental solid-state NMR chemical shifts and EFG tensor components for routine organic crystals, especially given the higher computational cost of those methods. This finding likely reflects error cancellation benefiting the hybrid functionals. Improving the accuracy of the predicted chemical shifts and EFG tensors relative to experiment would probably require more robust treatments of the crystal structures, their dynamics, and other factors.

Photomechanical molecular crystals have garnered attention for their ability to transform light into mechanical work, but difficulties in characterizing the structural changes and mechanical responses experimentally have hindered the development of practical organic crystal engines. This study proposes a new computational framework for predicting the solid-state crystal-to-crystal photochemical transformations entirely from first principles, and it establishes a photomechanical engine cycle that quantifies the anisotropic mechanical performance resulting from the transformation. The approach relies on crystal structure prediction, solid-state topochemical principles, and high-quality electronic structure methods. After validating the framework on the well-studied [4 + 4] cycloadditions in 9-methyl anthracene and 9-tert-butyl anthracene ester, the experimentally-unknown solid-state transformation of 9-carboxylic acid anthracene is predicted for the first time. The results illustrate how the mechanical work is done by relaxation of the crystal lattice to accommodate the photoproduct, rather than by the photochemistry itself. The large ∼107 J m-3 work densities computed for all three systems highlight the promise of photomechanical crystal engines. This study demonstrates the importance of crystal packing in determining molecular crystal engine performance and provides tools and insights to design improved materials in silico.

The ability to theoretically predict accurate NMR chemical shifts in solids is increasingly important due to the roles such shifts play in selecting among proposed model structures. Here, two theoretical methods are evaluated for their ability to assign 15 N shifts from guanosine dihydrate to one of the two independent molecules present in the lattice. The NMR data consist of 15 N shift tensors from 10 resonances. Analysis using periodic boundary or fragment methods consider a benchmark dataset to estimate errors and predict uncertainties of 5.6 and 6.2 ppm, respectively. Despite this high accuracy, only one of the five sites were confidently assigned to a specific molecule of the asymmetric unit. This limitation is not due to negligible differences in experimental data, as most sites exhibit differences of > 6.0 ppm between pairs of resonances representing a given position. Instead, the theoretical methods are insufficiently accurate to make assignments at most positions.

9-Anthracene carboxylic acid derivatives comprise a family of thermally reversible photomechanical molecular crystals. The photomechanical response relies on a [4 + 4] photodimerization followed by dissociation that occurs on timescales of seconds to minutes. A combined theoretical and experimental investigation is undertaken to better understand how chemical modification of the anthracene core influences energetics of both the isolated molecule and the crystal lattice. We use both density functional theory and dispersion-corrected Moller–Plesset perturbation theory computational methods to establish orbital energies, photodimerization reaction energies, and lattice energies for a set of substituted 9-anthracene carboxylic acid molecules. The calculations reveal that steric interactions play a dominant role in the ability to form photodimers and indicate an energetic threshold of 80–90 kJ per mole for the dimerization reaction. Examination of intermolecular bonding in a subset of fluorinated 9ACs revealed the absence of H⋯F intermolecular bond formation and energy differences that can explain observed trends in the dissociation kinetics and mechanical reset times. Fluorescence recovery after photobleaching experiments shows that the photodimer dissociation kinetics depend on the amount of initial photodimer, preventing a straightforward correlation between halogen atom substitution and dissociation rates using the Bell–Evans–Polanyi principle. The results clarify how molecular structure affects intermolecular interactions and photoreactivity in this family of molecular crystals, but the origin of the complex photodimer dissociation dynamics remains an open question.

The exceptionally high carrier mobility of rubrene derives from the combination of its intrinsic electronic properties and favorable crystal packing that facilitates charge transport. Unlike the planar conformations adopted by rubrene single crystals, however, many rubrene derivatives crystallize with a twisted tetracene core and exhibit poor carrier mobility. Typical density functional theory (DFT) calculations suggest that the twisted conformation is preferred by ∼10–14 kJ mol−1 or more in the gas phase. However, the present work shows that those calculations overestimate the twisting energy by several kJ mol−1 due to density-driven delocalization error, and that the twisting energies are actually only ∼8–10 kJ mol−1 for typical rubrene derivatives when computed with higher-level correlated wave function models. This result has two significant implications for crystal engineering with rubrene derivatives: first, DFT calculations can erroneously predict polymorphs containing twisted rubrene conformations to be more stable, when in fact structures with planar conformations are preferred, as is demonstrated here for perfluororubrene. Second, the smaller twisting energies make it more likely that solid form screening could discover new planar-core polymorphs of rubrene derivatives that have previously been crystallized only in a twisted conformation. These in turn might exhibit better organic semiconducting properties.

Crystals composed of photoreactive molecules represent a new class of photomechanical materials with the potential to generate large forces on fast timescales. An example is the photodimerization of 9-tert-butyl-anthracene ester (9TBAE) in molecular crystal nanorods that leads to an average elongation of 8%. Previous work showed that this expansion results from the formation of a metastable crystalline product. In this article, it is shown how a novel combination of ensemble oriented-crystal solid-state NMR, X-ray diffraction, and first principles computational modeling can be used to establish the absolute unit cell orientations relative to the shape change, revealing the atomic-resolution mechanism for the photomechanical response and enabling the construction of a model that predicts an elongation of 7.4%, in good agreement with the experimental value. According to this model, the nanorod expansion does not result from an overall change in the volume of the unit cell, but rather from an anisotropic rearrangement of the molecular contents. The ability to understand quantitatively how molecular-level photochemistry generates mechanical displacements allows us to predict that the expansion could be tuned from +9% to −9.5% by controlling the initial orientation of the unit cell with respect to the nanorod axis. This application of NMR-assisted crystallography provides a new tool capable of tying the atomic-level structural rearrangement of the reacting molecular species to the mechanical response of a nanostructured sample., NMR crystallography establishes absolute unit-cell orientations relative to the shape change, revealing the atomic-resolution mechanism for the nanorod's photomechanical response.

Crystal structure prediction driven by density functional theory has become an increasingly useful tool for the pharmaceutical industry and others interested in understanding and controlling organi...

Molecular crystal structure prediction is increasingly being applied to study the solid form landscapes of larger, more flexible pharmaceutical molecules. Despite many successes in crystal structure prediction, van der Waals-inclusive density functional theory (DFT) methods exhibit serious failures predicting the polymorph stabilities for a number of systems exhibiting conformational polymorphism, where changes in intramolecular conformation lead to different intermolecular crystal packings. Here, the stabilities of the conformational polymorphs of o-acetamidobenzamide, ROY, and oxalyl dihydrazide are examined in detail. DFT functionals that have previously been very successful in crystal structure prediction perform poorly in all three systems, due primarily to the poor intramolecular conformational energies, but also due to the intermolecular description in oxalyl dihydrazide. In all three cases, a fragment-based dispersion-corrected second-order Moller-Plesset perturbation theory (MP2D) treatment of the crystals overcomes these difficulties and predicts conformational polymorph stabilities in good agreement with experiment. These results highlight the need for methods which go beyond current-generation DFT functionals to make crystal polymorph stability predictions truly reliable.

Ab initio nuclear magnetic resonance chemical shift prediction plays an important role in the determination or validation of crystal structures. The ability to predict chemical shifts more accurately can translate to increased confidence in the resulting chemical shift or structural assignments. Standard electronic structure predictions for molecular crystal structures neglect thermal expansion, which can lead to an appreciable underestimation of the molar volumes. This study examines this volume error and its impact on 68 13C- and 28 15N-predicted chemical shifts taken from 20 molecular crystals. It assesses the ability to recover more realistic room-temperature crystal structures using the quasi-harmonic approximation and how refining the structures impacts the chemical shifts. Several pharmaceutical molecular crystals are also examined in more detail. On the whole, accounting for quasi-harmonic expansion changes the 13C and 15N chemical shifts by 0.5 and 1.0 ppm on average. This, in turn, reduces the root-mean-square errors relative to experiment by 0.3 ppm for 13C and 0.7 ppm for 15N. Although the statistical impacts are modest, changes in individual chemical shifts can reach multiple ppm. Accounting for thermal expansion in molecular crystal chemical shift prediction may not be needed routinely, but the systematic trend toward improved accuracy with the experiment could be useful in cases where discrimination between structural candidates is challenging, as in the pharmaceutical theophylline.

Molecular crystal engineering seeks to tune the material properties by controlling the crystal packing. However, the range of achievable properties is constrained by the limited energy range of polymorphs which can be crystallized. Here, computational modeling highlights that a solid-state crystal-to-crystal chemical reaction in 9-tert-butyl anthracene ester (9TBAE) nanorods [Al-Kaysi et al., J. Am. Chem. Soc., 2006, 128, 15938] imparts “synthetic memory” into the crystal structure that allows reproducible formation of a highly metastable, yet long-lived polymorph. Specifically, whereas the vast majority of known polymorphs exhibit lattice energy differences below 10 kJ mol−1, the conformational polymorph formed via solid state reaction chemistry lies 14 kJ mol−1 higher in energy than the form grown from solution, according to calculations that combine a dispersion-corrected second-order Moller–Plesset perturbation theory (MP2D) treatment of the monomer and photodimer with a density functional theory treatment (B86bPBE-XDM) of the intermolecular interactions in the crystal. Moreover, the solid-state reaction environment traps a highly unstable intramolecular photodimer conformation which defies the conventional wisdom surrounding conformational polymorphs. These observations suggest that solid-state reaction chemistry represents an under-appreciated strategy for producing polymorphs that would likely be unobtainable otherwise.

Knowledge of molecular crystal sublimation equilibrium data is vital in many industrial processes, but this data can be difficult to measure experimentally for low-volatility species. Theoretical prediction of sublimation pressures could provide a useful supplement to experiment, but the exponential temperature dependence of sublimation (or any saturated vapor) pressure curve makes this challenging. An uncertainty of only a few percent in the sublimation enthalpy or entropy can propagate to an error in the sublimation pressure exceeding several orders of magnitude for a given temperature interval. Despite this fundamental difficulty, this paper performs some of the first ab initio predictions of sublimation pressure curves. Four simple molecular crystals (ethane, methanol, benzene, and imidazole) have been selected for a case study showing the currently achievable accuracy of quantum chemistry calculations. Fragment-based ab initio techniques and the quasi-harmonic approximation are used for calculations of cohesive and phonon properties of the crystals, while the vapor phase is treated by the ideal gas model. Ab initio sublimation pressure curves for model compounds are compared against their experimental counterparts. The computational uncertainties are estimated, weak points of the computational methodology are identified, and further improvements are proposed.

Standard nuclear magnetic resonance (NMR) spectroscopy experiments measure isotropic chemical shifts, but measuring the chemical shielding anisotropy (CSA) tensor can provide additional insights into solid state chemical structures. Interpreting the principal components of these tensors is facilitated by first-principles chemical shielding tensor predictions. Here, the ability to predict molecular crystal CSA tensor components for 13C and 15N nuclei with fragment-based electronic structure techniques is explored. Similar to what has been found previously for isotropic chemical shifts, the benchmarking demonstrates that fragment-based techniques can accurately reproduce CSA tensor components. The use of hybrid density functionals like PBE0 or B3LYP provide higher accuracy than generalized gradient approximation functionals like PBE. Unlike for planewave density functional techniques, hybrid density functionals can be employed routinely with modest computational cost in fragment approaches. Finally, good consistency between the regression parameters used to map either isotropic shieldings or CSA tensor components is demonstrated, providing further evidence for the quality of the models and highlighting that models trained for isotropic shifts can also be applied to CSA tensor components.

The ability to predict not only what organic crystal structures might occur but also the thermodynamic conditions under which they are the most stable would be extremely useful for discovering and designing new organic materials. The present study takes a step in that direction by predicting the temperature- and pressure-dependent phase boundary between the α and β polymorphs of resorcinol using density functional theory (DFT) and the quasi-harmonic approximation. To circumvent the major computational bottleneck associated with computing a well-converged phonon density of states via the supercell approach, a recently developed approximation is employed, which combines a supercell phonon density of states from dispersion-corrected third-order density functional tight binding [DFTB3-D3(BJ)] with frequency corrections derived from a smaller B86bPBE-XDM functional DFT phonon calculation on the crystallographic unit cell. This mixed DFT/DFTB quasi-harmonic approach predicts the lattice constants and unit cell volumes to within 1%–2% at lower pressures. It predicts the thermodynamic phase boundary in almost perfect agreement with the experiment, although this excellent agreement does reflect fortuitous cancellation of errors between the enthalpy and entropy of transition.

The ability to theoretically predict accurate NMR chemical shifts in solids is increasingly important due to the role such shifts play in selecting among proposed model structures. Herein, two theoretical methods are evaluated for their ability to assign

First-principles prediction of nuclear magnetic resonance chemical shifts plays an increasingly important role in the interpretation of experimental spectra, but the required density functional theory (DFT) calculations can be computationally expensive. Promising machine learning models for predicting chemical shieldings in general organic molecules have been developed previously, though the accuracy of those models remains below that of DFT. The present study demonstrates how much higher accuracy chemical shieldings can be obtained via the Δ-machine learning approach, with the result that the errors introduced by the machine learning model are only one-half to one-third the errors expected for DFT chemical shifts relative to experiment. Specifically, an ensemble of neural networks is trained to correct PBE0/6-31G chemical shieldings up to the target level of PBE0/6-311+G(2d,p). It can predict

The structure of nitrogen phase $\ensuremath{\zeta}$ remains unknown decades after it was first observed spectroscopically, despite numerous experimental and theoretical investigations. The present computational study performs crystal structure prediction using ab initio random structure searching and density functional theory to identify candidate structures. These candidates are then analyzed for consistency with experiment in terms of their simulated x-ray diffraction patterns and Raman spectra. While none of the structures generated here is a clear match for the phase-$\ensuremath{\zeta}$ experimental data, several of the candidates do exhibit features in common with the experiments and could provide an interesting starting point for future studies. The techniques here also rule out several candidate $\ensuremath{\zeta}$ nitrogen structures that have been identified previously. Finally, one of the structures might be considered a candidate for phase $\ensuremath{\kappa}$, whose structure is also unknown.

Ab initio nuclear magnetic resonance chemical shift prediction provides an important tool for interpreting and assigning experimental spectra, but it becomes computationally prohibitive in large systems. The computational costs can be reduced considerably by fragmentation of the large system into a series of contributions from many smaller subsystems. However, the presence of charged functional groups and the need to partition the system across covalent bonds create complications in biomolecules that typically require the use of large fragments and careful descriptions of the electrostatic environment. The present work shows how a model that combines chemical shielding contributions from non-overlapping monomer and dimer fragments embedded in a polarizable continuum model provides a simple, easy-to-implement, and computationally inexpensive approach for predicting chemical shifts in complex systems. The model's performance proves rather insensitive to the continuum dielectric constant, making the selection of the optimal embedding dielectric less critical. The PCM-embedded fragment model is demonstrated to perform well across systems ranging from molecular crystals to proteins.

Noncovalent interactions govern many important areas of chemistry, ranging from biomolecules to molecular crystals. Here, an accurate and computationally inexpensive dispersion-corrected second-order Møller-Plesset perturbation theory model (MP2D) is presented. MP2D recasts the highly successful dispersion-corrected MP2C model in a framework based on Grimme's D3 dispersion correction, combining Grimme's D3 dispersion coefficients with new analogous uncoupled Hartree-Fock ones and five global empirical parameters. MP2D is faster than MP2C, and unlike MP2C, it is suitable for geometry optimizations and can describe both intra- and intermolecular noncovalent interactions with high accuracy. MP2D approaches the accuracy of higher-level ab initio wave function techniques and out-performs a widely used hybrid dispersion-corrected density functional on a range of intermolecular, intramolecular, and thermochemical benchmarks.

Organic crystals frequently adopt multiple distinct polymorphs exhibiting different properties. The ability to predict not only what crystal forms might occur, but under what experimental thermodynamic conditions those polymorphs are stable would be immensely valuable to the pharmaceutical industry and others. Starting only from knowledge of the experimental crystal structures, this study successfully predicts the methanol crystal polymorph phase diagram from first-principles quantum chemistry, mapping out the thermodynamic regions of stability for three polymorphs over the range 0-400 K and 0-6 GPa. The agreement between the predicted and experimental phase diagrams corresponds to predicting the relative polymorph free energies to within ∼0.5 kJ mol-1 accuracy, which is achieved by employing fragment-based second-order Moller-Plesset perturbation theory and coupled cluster theory plus a quasi-harmonic treatment of the phonons.

Quasi-harmonic approaches provide an economical route to modeling the temperature dependence of molecular crystal structures and properties. Several studies have demonstrated good performance of these models, at least for rigid molecules, when using fragment-based approaches with correlated wavefunction techniques. Many others have found success employing dispersion-corrected density functional theory (DFT). Here, a hierarchy of models in which the energies, geometries, and phonons are computed either with correlated methods or DFT are examined to identify which combinations produce useful predictions for properties such as the molar volume, enthalpy, and entropy as a function of temperature. The results demonstrate that refining DFT geometries and phonons with single-point energies based on dispersion-corrected second-order Møller-Plesset perturbation theory can provide clear improvements in the molar volumes and enthalpies compared to those obtained from DFT alone. Predicted entropies, which are governed by vibrational contributions, benefit less clearly from the hybrid schemes. Using these hybrid techniques, the room-temperature thermochemistry of acetaminophen (paracetamol) is predicted to address the discrepancy between two experimental sublimation enthalpy measurements.

NMR studies measuring the chemical shift tensors are increasingly being employed to assign structure in difficult-to-crystallize solids. For small organic molecules, such studies usually focus on 13C sites, but proteins and peptides are more commonly described using 15N amide sites. An important and often neglected consideration when measuring shift tensors is the evaluation of their accuracy against benchmark standards, where available. Here we measure 15N tensors in the dipeptide glycylglycine at natural abundance using the slow-spinning FIREMAT method with SPINAL-64 decoupling. The accuracy of these 15N tensors is evaluated by comparing to benchmark single crystal NMR 15N measurements and found to be statistically indistinguishable. These FIREMAT experimental results are further used to evaluate the accuracy of theoretical predictions of tensors from four different density functional theory (DFT) methods that include lattice effects. The best theoretical approach provides an rms difference of 3.9 ppm and is obtained from a fragment-based method and the PBE0 density functional.

To investigate the performance of quasi-harmonic electronic structure methods for modeling molecular crystals at finite temperatures and pressures, thermodynamic properties are calculated for the low-temperature α polymorph of crystalline methanol. Both density functional theory (DFT) and ab initio wavefunction techniques up to coupled cluster theory with singles, doubles, and perturbative triples (CCSD(T)) are combined with the quasi-harmonic approximation to predict energies, structures, and properties. The accuracy, reliability, and uncertainties of the individual quantum-chemical methods are assessed via detailed comparison of calculated and experimental data on structural properties (density) and thermodynamic properties (isobaric heat capacity). Performance of individual methods is also studied in context of the hierarchy of the quantum-chemical methods. The results indicate that while some properties such as the sublimation enthalpy and thermal expansivity can be modeled fairly well, other properties such as the molar volume and isobaric heat capacities are harder to predict reliably. The errors among the energies, structures, and phonons are closely coupled, and most accurate predictions here appear to arise from fortuitous error compensation among the different contributions. This study highlights how sensitive molecular crystal property predictions can be to the underlying model approximations and the significant challenges inherent in first-principles predictions of solid state structures and thermochemistry.

Solid carbon dioxide exhibits a rich phase diagram at high pressures. Metastable phase III is formed by compressing dry ice above ∼10-12 GPa. Phase VII occurs at similar pressures but higher temperatures, and its stability region is disconnected from III on the phase diagram. Comparison of large-basis-set quasi-harmonic second-order Møller-Plesset perturbation theory calculations and experiment suggests that the long-accepted structure of phase III is problematic. The experimental phase III and VII structures both relax to the same phase VII structure. Furthermore, Raman spectra predicted for phase VII are in good agreement with those observed experimentally for both phase III and VII, while those for the purported phase III structure agree poorly with experimental observations. Crystal structure prediction is employed to search for other potential structures which might account for phase III, but none are found. Together, these results suggest that phases III and VII are likely identical.

Widely used crystal structure prediction models based on density functional theory can perform poorly for conformational polymorphs, but a new model corrects those polymorph stability rankings., Molecular crystal structure prediction is increasingly being applied to study the solid form landscapes of larger, more flexible pharmaceutical molecules. Despite many successes in crystal structure prediction, van der Waals-inclusive density functional theory (DFT) methods exhibit serious failures predicting the polymorph stabilities for a number of systems exhibiting conformational polymorphism, where changes in intramolecular conformation lead to different intermolecular crystal packings. Here, the stabilities of the conformational polymorphs of o-acetamidobenzamide, ROY, and oxalyl dihydrazide are examined in detail. DFT functionals that have previously been very successful in crystal structure prediction perform poorly in all three systems, due primarily to the poor intramolecular conformational energies, but also due to the intermolecular description in oxalyl dihydrazide. In all three cases, a fragment-based dispersion-corrected second-order Møller–Plesset perturbation theory (MP2D) treatment of the crystals overcomes these difficulties and predicts conformational polymorph stabilities in good agreement with experiment. These results highlight the need for methods which go beyond current-generation DFT functionals to make crystal polymorph stability predictions truly reliable.

The $\ensuremath{\lambda}$ phase of nitrogen was reported in 2016 and is one of more than a dozen high-pressure solid nitrogen forms that have been discovered. However, its crystal structure could not be solved unambiguously from powder diffraction alone; rather the reported structure was determined by combining experimental monoclinic lattice parameters with atomic positions from an earlier, computationally predicted structure that had similar unit cell dimensions. Here, we revisit this structure using density functional theory and higher-level fragment-based second-order M\o{}ller-Plesset perturbation theory (MP2) and coupled cluster singles, doubles, and perturbative triples [CCSD(T)]. Crystal structure prediction is performed to demonstrate that the reported $P{2}_{1}/c$ structure is indeed the likeliest candidate for the $\ensuremath{\lambda}$ phase. Furthermore, we provide further evidence for the structural assignment by demonstrating reasonable agreement between its predicted and experimental structural parameters and Raman spectra. Finally, the thermodynamic stability of the $\ensuremath{\lambda}$ phase relative to other phases has been uncertain, but the calculations do suggest that it may be the thermodynamically most stable phase for at least part of the pressure range over which it has been observed.

A fast, straightforward method for computing NMR chemical shieldings of crystalline solids is proposed. The method combines the advantages of both conventional approaches: periodic calculations using plane-wave basis sets and molecular computational approaches. The periodic calculations capture the periodic nature of crystalline solids, but the computational level of the electronic structure calculation is limited to general-gradient-approximation (GGA) density functionals. It is demonstrated that a correction to the GGA result calculated on an isolated molecule at a higher level of theory significantly improves the correlations between experimental and calculated chemical shifts while adding almost no additional computational cost. Corrections calculated with a hybrid density functional improved the accuracy of 13C, 15N and 17O chemical shift predictions significantly and allowed identifying errors in previously published experimental data. Applications of the approach to crystalline isocytosine, methacrylamide, and testosterone are presented.

Phonon contributions to organic crystal structures and thermochemical properties can be significant, but computing a well-converged phonon density of states with lattice dynamics and periodic density functional theory (DFT) is often computationally expensive due to the need for large supercells. Using semi-empirical methods like density functional tight binding (DFTB) instead of DFT can reduce the computational costs dramatically, albeit with noticeable reductions in accuracy. This work proposes approximating the phonon density of states via a relatively inexpensive DFTB supercell treatment of the phonon dispersion that is then corrected by shifting the individual phonon modes according to the difference between the DFT and DFTB phonon frequencies at the Γ-point. The acoustic modes are then computed at the DFT level from the elastic constants. In several small-molecule crystal test cases, this combined approach reproduces DFT thermochemistry with kJ/mol accuracy and 1-2 orders of magnitude less computational effort. Finally, this approach is applied to computing the free energy differences between the five crystal polymorphs of oxalyl dihydrazide.

Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid-state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13C and 15N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study., Fragment-based electronic structure methods allow nuclear magnetic resonance chemical shifts to be predicted with higher accuracy and lower computational cost. Higher-accuracy chemical shifts lead to increased discrimination between correct and incorrect structural assignments in the NMR crystallography of polymorphic molecular crystals.

The photodimerization of 9-tert-butyl-anthracene ester in molecular crystal nanorods can cause expansions of up to 15%. This expansion results from the formation of a metastable crystalline intermediate, the solid-state reacted dimer (SSRD). In this paper, a combination of powder X-ray diffraction, solid-state nuclear magnetic resonance, and computational modeling is used to determine the crystal structure of the SSRD intermediate. An ensemble of six possible structures is obtained, which differ only in small packing details that lead to different crystal space groups. The structure with the best overall agreement with the experimental data belongs to the Pccn space group and, like the other members of the ensemble, retains a packing motif close to that of the monomer crystal. This crystal structure allows us to conclude that the SSRD crystal density is slightly greater than that of the monomer crystal and that gross changes in the volume or unit cell parameters of the SSRD are not responsible for the photoinduced expansion.

The temperature-dependence of the crystalline carbon dioxide (phase I) structure, thermodynamics, and mechanical properties are predicted in excellent agreement with experiment over a 200 K temperature range using high-level electronic structure calculations., Molecular crystal structures, thermodynamics, and mechanical properties can vary substantially with temperature, and predicting these temperature-dependencies correctly is important for many practical applications in the pharmaceutical industry and other fields. However, most electronic structure predictions of molecular crystal properties neglect temperature and/or thermal expansion, leading to potentially erroneous results. Here, we demonstrate that by combining large basis set second-order Møller–Plesset (MP2) or even coupled cluster singles, doubles, and perturbative triples (CCSD(T)) electronic structure calculations with a quasiharmonic treatment of thermal expansion, experimentally observable properties such as the unit cell volume, heat capacity, enthalpy, entropy, sublimation point and bulk modulus of phase I crystalline carbon dioxide can be predicted in excellent agreement with experiment over a broad range of temperatures. These results point toward a promising future for ab initio prediction of molecular crystal properties at real-world temperatures and pressures.

Simulation determined the crystal energy landscape of a set of molecular crystals, predicting ultrahigh surface area solids with high methane storage. These were then synthesized, showing the potential of computational structure-property mapping.

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Small changes in steric bulk at the terminus of bis-iminopyridine ligands can effect large changes in the spin state of self-assembled Fe(II)-iminopyridine cage complexes. If the added bulk is properly matched with ligands that are either sufficiently flexible to allow twisted octahedral geometries at the Fe centers or can assemble with unusual mer configurations at the metals, room temperature high spin Fe(II) cages can be synthesized. These complexes maintain their high spin state in solution at low temperatures and have been characterized by X-ray crystallographic and computational methods. The high spin M2L3 meso-helicate and M4L6 cage complexes display longer N-Fe bond distances and larger interligand N-Fe-N bond angles than their diamagnetic counterparts, and these structural changes invert the ligand selectivity in narcissistic self-sorting and accelerate subcomponent exchange rates. The paramagnetic cages can be easily converted to diamagnetic cages by subcomponent exchange under mild conditions, and the intermediates of the exchange process can be visualized in situ by NMR analysis.

To accelerate the evaluation of the self-consistent polarization in large condensed-phase systems with polarizable force fields, the new divide-and-conquer Jacobi iterations (DC-JI) solver is adapted for periodic boundary conditions with particle-mesh Ewald and implemented in a massively parallel fashion within the Tinker-HP software package. DC-JI captures the mutual polarization of close-range interactions within subclusters of atoms using Cholesky decomposition and couples in the polarization effects between these clusters iteratively. Iterative convergence is accelerated with direct inversion of the iterative subspace (DIIS) extrapolation. Compared to widely used preconditioned conjugate gradient (PCG) or conventional Jacobi iterations (JI/DIIS) algorithms, DC-JI/DIIS solves the polarization equations ∼20-30% faster in protein systems ranging from ∼10,000-175,000 atoms run on hundreds of processor cores. This translates to ∼10-15% speed-ups in the number of nanoseconds of simulation time that can be achieved per day. Not only is DC-JI/DIIS faster than PCG, but it also gives more energetically robust solutions for a given convergence threshold. These improvements make numerically robust polarizable force field simulations more computationally tractable for chemical systems of interest.

A strained, “springloaded” Fe2L3 iminopyridine mesocate shows highly variable reactivity upon postassembly reaction with competitive diamines. The strained assembly is reactive toward transimination in minutes at ambient temperature and allows observation of kinetically trapped intermediates in the self-assembly pathway. When diamines are used that can only form less favored cage products upon full equilibration, trapped ML3 fragments with pendant, “hanging” NH2 groups are selectively formed instead. Slight variations in diamine structure have large effects on the product outcome: less rigid diamines convert the mesocate to more favored self-assembled cage complexes under mild conditions and allow observation of heterocomplex intermediates in the displacement pathway. The mesocate allows control of equilibrium processes and direction of product outcomes via small, iterative changes in added subcomponent structure and provides a method of accessing metal-ligand cage structures not normally observed in mult...

Molecular dipoles present important, but underutilized, methods for guiding electron transfer (ET) processes. While dipoles generate fields of Gigavolts per meter in their vicinity, reported differences between rates of ET along versus against dipoles are often small or undetectable. Herein we show unprecedentedly large dipole effects on ET. Depending on their orientation, dipoles either ensure picosecond ET, or turn ET completely off. Furthermore, favorable dipole orientation makes ET possible even in lipophilic medium, which appears counterintuitive for non-charged donor-acceptor systems. Our analysis reveals that dipoles can substantially alter the ET driving force for low solvent polarity, which accounts for these unique trends. This discovery opens doors for guiding forward ET processes while suppressing undesired backward electron transduction, which is one of the holy grails of photophysics and energy science.

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Subtle differences in ligand coordination angle and rigidity lead to high fidelity sorting between individual components displaying identical coordination motifs upon metal-mediated self-assembly. Narcissistic self-sorting can be achieved between highly similar ligands that vary minimally in rigidity and internal coordination angle upon combination with Fe(ii) ions and 2-formylpyridine. Selective, sequential cage formation can be precisely controlled in a single flask from a mix of three different core ligands (and 33 total components) differing only in the hybridization of one group that is uninvolved in the metal coordination process.

Fragment-based methods predict nuclear magnetic resonance (NMR) chemical shielding tensors in molecular crystals with high accuracy and computational efficiency. Such methods typically employ electrostatic embedding to mimic the crystalline environment, and the quality of the results can be sensitive to the embedding treatment. To improve the quality of this embedding environment for fragment-based molecular crystal property calculations, we borrow ideas from the embedded ion method to incorporate self-consistently polarized Madelung field effects. The self-consistent reproduction of the Madelung potential (SCRMP) model developed here constructs an array of point charges that incorporates self-consistent lattice polarization and which reproduces the Madelung potential at all atomic sites involved in the quantum mechanical region of the system. The performance of fragment- and cluster-based 1H, 13C, 14N, and 17O chemical shift predictions using SCRMP and density functionals like PBE and PBE0 are assessed. ...

Traditional electron-transfer dissociation (ETD) experiments operate through a complex combination of hydrogen abundant and hydrogen deficient fragmentation pathways, yielding c and z ions, side-chain losses, and disulfide bond scission. Herein, a novel dissociation pathway is reported, yielding homolytic cleavage of carbon-iodine bonds via electronic excitation. This observation is very similar to photodissociation experiments where homolytic cleavage of carbon-iodine bonds has been utilized previously, but ETD activation can be performed without addition of a laser to the mass spectrometer. Both loss of iodine and loss of hydrogen iodide are observed, with the abundance of the latter product being greatly enhanced for some peptides after additional collisional activation. These observations suggest a novel ETD fragmentation pathway involving temporary storage of the electron in a charge-reduced arginine side chain. Subsequent collisional activation of the peptide radical produced by loss of HI yields spectra dominated by radical-directed dissociation, which can be usefully employed for identification of peptide isomers, including epimers. Graphical Abstract ᅟ.

NMR studies measuring chemical shift tensors are increasingly being employed to assign structure in difficult-to-crystallize solids. For small organic molecules, such studies usually focus on

Molecular crystal structure has major impacts on the physical properties of the crystal. Crystal packing is governed by a balance between inter- and intramolecular interactions. Modeling molecular crystals theoretically requires careful description of the noncovalent interactions, including exchange, electrostatics polarization, and van der Waals dispersion. This chapter discusses different electronic structure methods used to model molecular crystals, including periodic density functional theory, periodic second-order Moller–Plesset perturbation theory, and fragment-based methods. It then reviews various applications of these techniques to predicting a variety of molecular crystal properties. Examples include modeling finite-temperature effects on crystal volumes, thermochemistry, and mechanical properties, predicting stable crystal phases, and applications to vibrational and nuclear magnetic resonance spectroscopies.