Towards improving the characteristics of high-energy pyrazines and their N-oxides

CONTEXT

Based on the methods of quantum chemistry and atom-atom potentials, the molecular and crystal structure of a number of high-energy pyrazines was modeled: unsubstituted diazines, as well as fully nitrated 1,4-diazabenzenes, their oxides and polymorphs. The enthalpies of formation, densities of molecular crystals, and some performance characteristics of these compounds were determined. The parameters of decomposition of substances were estimated. It has been established that tetranitropyrazine-1,4-dioxide has maximum energy content and excellent performance characteristics, which determine the prospects for using this compound as a high-energy one in the considered series of compounds.

METHODS

In this work, DFT calculations were conducted through the software Gaussian 09 using B3LYP functional with basis set aug-cc-PVDZ and the Grimme dispersion correction D2. For crystal structure optimization, the atom-atom potential methods with PMC program (Packing of Molecules in Crystal) were used. Charges for molecular electrostatic potential were fitted by FitMEP and enthalpies of formation in gas phase were assessed by G3B3.

Computational insight into the crystal structures of cubane and azacubanes

CONTEXT

Using quantum chemistry and atom-atom potential methods, the molecular and crystal structures of cubane 1 and all types of unsubstituted azacubanes 2-22 were calculated. Alternative possible polymorphs of cubane 1 have been proposed. The thermochemical properties of azacubanes in the gas and solid phases were assessed. Thermodynamic aspects of stability are considered, and a significant decrease in stability is revealed upon transition from cubane 1 to octaazacubane 22. It has been shown that the density and energetic properties of azacubanes depend nonlinearly on the number of nitrogen atoms in the structure and the density of octaazacubane 22 at room temperature is 1.546 g cm-3, which is significantly lower than the previously given estimate.

METHODS

In this work, DFT calculations were conducted through the software Gaussian 09 using B3LYP functional with basis set aug-cc-PVDZ and the Grimme dispersion correction D2. For crystal structure optimization, the atom-atom potential methods with PMC (packing of molecules in crystal) program were used. Charges for molecular electrostatic potential were fitted by FitMEP, and enthalpies of formation in gas phase were assessed by G3B3.

Substituted tetrazoles with N-oxide moiety: critical assessment of thermochemical properties

Modeling of the structure of molecules and simulation of crystal structure followed by the calculation of the enthalpies of formation for 21 salts of three high-energy tetrazole 1N-oxides: 5-nitro-1-hydroxy-1H-tetrazole 1a-1g, 5-trinitromethyl-1-hydroxy-1H-tetrazole 2a-2g and 6-amino-3-(1-hydroxy-1H-tetrazol-5-yl)-1,2,4,5-tetrazine 1,5-dioxide 3a-3g was performed. The methods of quantum chemistry and the method of atom-atom potentials were used. Structural search for optimal crystal packings was carried out in 11 most common space symmetry groups. The enthalpies of formation were obtained and analyzed using two different approaches: VBT and MICCM methods, which allowed to evaluate the quality of these calculation methods. In addition, the results obtained indicate high values of thermochemical characteristics for some of the considered compounds, which have a positive effect on their explosive properties and unveil their future application potential.

Is everything correct? The formation enthalpy estimation and data revision of nitrate and perchlorate salts

CONTEXT

  In modern searches for the structure of high-energy-density compounds with high operational, detonation, and physicochemical characteristics, a special place belongs to salts, which have a number of significant advantages over neutral compounds. The development of this area of HEDM is hampered by the lack of effective calculation schemes for estimating the enthalpy of formation DH_f⁰ of salts, as a key parameter in assessing the prospects for their use. Based on the author's method (MICCM), which is superior in accuracy to currently available calculation methods, the enthalpies of formation of various salts of nitrates and perchlorates for a promising class of high-energy amino-1,2,4-triazoles are calculated and the accuracy of calculations is estimated by other methods. Relationships between the thermochemical characteristics of salts depending on various cations are considered. Among the considered compounds, calculations of the enthalpies of salts of three amino-1,2,4-triazoles showed a significant discrepancy with the experimental data.

METHODS

Calculations DH_f⁰of salts were performed using three methods: volume-base thermodynamic (Jenkins/Bartlett method), the method of adding of ions contributions (MAIC, Matyushin's method), and the method of ions and cocrystals contribution mixing (MICCM, Khakimov's method). Calculations by the MICCM method were carried out on the basis of quantum chemistry methods (when estimating the enthalpies of formation in the gas phase) and the method of atom-atom potentials (AAP) when calculating the enthalpy of sublimation of salts. We have optimized all the structures in the gas phase using the Becke three hybrid exchange and Lee-Yang-Parr correlation functional with Grimme's dispersion correction, B3LYP-D2, and aug-cc-pVDZ basis set using the Gaussian16 software. The AAP calculations were performed using the FitMEP software packages (for adjusting the charges of the molecular electrostatic potential) and PMC (for the procedure for constructing crystal packings and searching for optimal ones).

New Method for Predicting the Enthalpy of Salt Formation

A new efficient method for calculating the enthalpies of salt formation is proposed. The method is based on a fundamentally new cocrystal model, consisting of a mixture of cations and anions and a "quasi-salt" of neutral components, in fact, of the salt itself, and the enthalpy of formation is calculated as the average value between the enthalpies of formation of these two structural components. Unlike correlation and additive schemes, this method is based on the construction of a real physical model of a salt crystal, for which the molecular geometry of the ions and neutral salt components is preliminarily optimized by quantum chemistry methods. Further, based on the obtained data, the initial models of crystal lattices in the statistically most probable structural classes are constructed with their subsequent optimization by the method of Atom-Atom potentials. For a number of compounds of various chemical classes, the effectiveness of the method for estimating the enthalpy of salts is shown, which surpasses the known methods in terms of calculation accuracy.

Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization

Artificial intelligence and specifically machine learning applications are nowadays used in a variety of scientific applications and cutting-edge technologies, where they have a transformative impact. Such an assembly of statistical and linear algebra methods making use of large data sets is becoming more and more integrated into chemistry and crystallization research workflows. This review aims to present, for the first time, a holistic overview of machine learning and cheminformatics applications as a novel, powerful means to accelerate the discovery of new crystal structures, predict key properties of organic crystalline materials, simulate, understand, and control the dynamics of complex crystallization process systems, as well as contribute to high throughput automation of chemical process development involving crystalline materials. We critically review the advances in these new, rapidly emerging research areas, raising awareness in issues such as the bridging of machine learning models with first-principles mechanistic models, data set size, structure, and quality, as well as the selection of appropriate descriptors. At the same time, we propose future research at the interface of applied mathematics, chemistry, and crystallography. Overall, this review aims to increase the adoption of such methods and tools by chemists and scientists across industry and academia.

Di- and trioxides of triazolotetrazine: Computational prediction of crystal structures and estimation of physicochemical characteristics

Simulation of crystal structures of series 1(2)-R-1(2)H-[1,2,3]triazolo[4,5-e][1,2,3,4]tetrazine 5,7-dioxides, 1,5,7-trioxides, 4,6-dioxides and 3,4,6-trioxides was carried out using an original technique based on the method of atom-atom potentials and quantum chemistry. The effect of the position of the substituent in the triazole ring on the change in the crystal structures of these compounds and their thermochemical characteristics was studied for the first time. For some of synthesized compounds, thermochemical characteristics were investigated and differential scanning calorimetry curves were obtained. Detonation parameters were calculated, on the basis of which the prospects for the use of the considered compounds were assessed.

Crystal Structure Prediction Using an Age-Fitness Multiobjective Genetic Algorithm and Coordination Number Constraints

Crystal structure prediction (CSP) has emerged as one of the most important approaches for discovering new materials. CSP algorithms based on evolutionary algorithms and particle swarm optimization have discovered a great number of new materials. However, these algorithms based on ab initio calculation of free energy are inefficient. Moreover, they have severe limitations in terms of scalability. We recently proposed a promising crystal structure prediction method based on atomic contact maps, using global optimization algorithms to search for the Wyckoff positions by maximizing the match between the contact map of the predicted structure and the contact map of the true crystal structure. However, our previous contact-map-based CSP algorithms have two major limitations: (1) the loss of search capability due to getting trapped in local optima; (2) it only uses the connection of atoms in the unit cell to predict the crystal structure, ignoring the chemical environment outside the unit cell, which may lead to unreasonable coordination environments. Herein, we propose a novel multiobjective genetic algorithm for contact-map-based crystal structure prediction by optimizing three objectives, including contact map match accuracy, individual age, and coordination number match. Furthermore, we assign the age values to all the individuals of the GA and try to minimize the age, aiming to avoid the premature convergence problem. Our experimental results show that compared to our previous CMCrystal algorithm, our multiobjective crystal structure prediction algorithm (CMCrystalMOO) can reconstruct the crystal structure with higher quality and alleviate the problem of premature convergence. The source code is open sourced and can be accessed at https://github.com/usccolumbia/MOOCSP.

Quest: structure and properties of BTF–nitrobenzene cocrystals with different ratios of components

Using the methods of quantum chemistry and AAP, the structure of BTF cocrystals with nitrobenzene, 1,2-, 1,3-, 1,4-dinitrobenzene, 1,3,5-trinitrobenzene, and hexanitrobenzene with different ratios of components (1 : 1, 1 : 2, 1 : 3, 2 : 1, 3 : 1) is modeled.

Crystal structure prediction of materials with high symmetry using differential evolution

Crystal structure determines properties of materials. With the crystal structure of a chemical substance, many physical and chemical properties can be predicted by first-principles calculations or machine learning models. Since it is relatively easy to generate a hypothetical chemically valid formula, crystal structure prediction becomes an important method for discovering new materials. In our previous work, we proposed a contact map-based crystal structure prediction method, which uses global optimization algorithms such as genetic algorithms to maximize the match between the contact map of the predicted structure and the contact map of the real crystal structure to search for the coordinates at the Wyckoff positions (WP), demonstrating that known geometric constraints (such as the contact map of the crystal structure) help the crystal structure reconstruction. However, when predicting the crystal structure with high symmetry, we found that the global optimization algorithm has difficulty to find an effective combination of WP that satisfies the chemical formula, which is mainly caused by the inconsistency between the dimensionality of the contact map of the predicted crystal structure and the dimensionality of the contact map of the target crystal structure. This makes it challenging to predict the crystal structures of high-symmetry crystals. In order to solve this problem, here we propose to use PyXtal to generate and filter random crystal structures with given symmetry constraints based on the information such as chemical formulas and space groups. With contact map as the optimization goal, we use differential evolution algorithms to search for non-special coordinates at the WP to realize the structure prediction of high-symmetry crystal materials. Our experimental results show that our proposed algorithm CMCrystalHS can effectively solve the problem of inconsistent contact map dimensions and predict the crystal structures with high symmetry.

Nitrodiaziridines: Unattainable yet, but Desired Energetic Materials

Using quantum chemical methods and the original technique based on atom-atom potential methods, the molecular and crystal structure simulation of all possible structural forms of nitrodiaziridines were carried out. The possible pathways of thermal decomposition of nitrodiaziridines were modeled, and the most stable forms were identified. Thermodynamic stability, physicochemical characteristics, and detonation properties were also estimated. The obtained results enable a huge potential of the nitrodiaziridine-based compounds as high-energy materials for a variety of applications.

Contact map based crystal structure prediction using global optimization

Crystal structure prediction is now playing an increasingly important role in the discovery of new materials or crystal engineering.

Time for quartet: the stable 3 : 1 cocrystal formulation of FTDO and BTF – a high-energy-density material

A computer simulation of cocrystal structures of [1,2,5]oxadiazolo[3,4-e][1,2,3,4]tetrazine 4,6-dioxide (FTDO) with benzotrifuroxan (BTF) in ratios of (3–1 : 1) was performed. Theoretically and experimentally was shown: a (3 : 1) cocrystal is formed.

Chirality and stereoisomerism of organic multicomponent crystals in the CSD

Multicomponent crystals in the CSD are classified into 49 subclasses based on chirality and residue type.

Correlations and statistical analysis of solvent molecule hydrogen bonding – a case study of dimethyl sulfoxide (DMSO)

A statistical study of the correlation between predicted solubility of DMSO solvates and hydrogen bonds between solvent and host molecules.

Assessment of the Stoichiometry of Multicomponent Crystals Using Only X-ray Powder Diffraction Data

Knowledge of the unit cell volume of a crystalline form and the expected space filling requirements of an API molecule can be used to determine if a crystalline material is likely to be multicomponent, such as a solvate, hydrate, salt, or a co-crystal. The unit cell information can be readily accessed from powder diffraction data alone utilizing powder indexing methodology. If the unit cell has additional space not likely attributable to the API entity, then there is either a void or another component within the crystal lattice. This "leftover" space can be used to determine the likely stoichiometry of the additional component. A simple approach for calculating the expected required volume for a given molecule within a crystal using an atom based additive approach will be discussed. Coupling this estimation with the actual unit cell volumes and space group information obtained from powder indexing allows for the rapid evaluation of the likely stoichiometry of multicomponent crystals using diffraction data alone. This approach is particularly useful for the early assessment of new phases during salt, co-crystal, and polymorph screening, and also for the characterization of stable and unstable solvates.

Perindoprilat monohydrate

The title compound [systematic name: (1S)-2-((S)-{1-[(2S,3aS,7aS)-2-carboxyoctahydro-1H-indol-1-yl]-1-oxopropan-2-yl}azaniumyl)pentanoate monohydrate], C(17)H(28)N(2)O(5)·H(2)O, (I)·H(2)O, the active metabolite of the antihypertensive and cardiovascular drug perindopril, was obtained during polymorphism screening of perindoprilat. It crystallizes in the chiral orthorhombic space group P2(1)2(1)2(1), the same as the previously reported ethanol disolvate [Pascard, Guilhem, Vincent, Remond, Portevin & Laubie (1991). J. Med. Chem. 34, 663-669] and dimethyl sulfoxide hemisolvate [Bojarska, Maniukiewicz, Sieroń, Fruziński, Kopczacki, Walczyński & Remko (2012). Acta Cryst. C68, o341-o343]. The asymmetric unit of (I)·H(2)O contains one independent perindoprilat zwitterion and one water molecule. These interact via strong hydrogen bonds to give a cyclic R(2)(2)(7) synthon, which provides a rigid molecular conformation. The geometric parameters of all three forms are similar. The conformations of the perhydroindole group are almost identical, but the n-alkyl chain has conformational freedom. A three-dimensional hydrogen-bonding network of O-H···O and N-H···O interactions is observed in the crystal structure of (I)·H(2)O, similar to the other two solvates, but because of the presence of different solvents the three crystal structures have diverse packing motifs. All three solvatomorphs are additionally stabilized by nonclassical weak C-H···O contacts.