DFT Calculations for the HONO Elimination Process of CL-20 Conformers

The HONO elimination process is regarded to be an important initial decomposition process of energetic nitramines. Four CL-20 conformers based on the ε-CL-20 were obtained by the optimization at the m062x/cc-pvtz level in this study, and the Transition State (TS) and Intrinsic Reaction Coordinate (IRC) calculations were carried out at the same level. In addition, the rate coefficients and activation energy of the HONO elimination process were evaluated using conventional transition state theory (TST) and canonical variational transition state theory (CVT) with Eckart and small-curvature tunneling (SCT) methods to correct the transmission coefficients for the quantum tunneling effect. The calculation results have shown that the HONO elimination process concerning the nitro groups located on six numbered rings is the hardest to happen, and it seems that the longer distance between nitro groups and the adjacent hydrogen atom would result in the higher barrier energy; the HONO elimination process is most likely to happen for the axial positioning of nitro groups located on five numbered rings and most unlikely to happen for the ones located on six numbered rings; CL-20 II and CL-20 IV conformers are the most unstable one and most stable one concerning the reaction difficulty of the HONO elimination process.

Quantum chemical study of reaction mechanism between plutonium and Nitrogen

The study of the reaction between plutonium and nitrogen is helpful to further understand the interaction between plutonium and air gas molecules. For the nitridation reaction of plutonium, there is no report on the microscopic reaction mechanism of this system at present. Therefore, the microcospic mechanism of gas phase reaction of Pu with N 2 is studied in this paper based on the density functional theory (DFT) using different functions. In this paper, the geometry of stationary points on the potential energy surface is optimized. In addition, the transition states are verified by the frequency analysis method and the intrinsic reaction coordinate (IRC) method. Finally, we obtain the reaction potential energy curve and the micro reaction pathways. The analysis of reaction mechanism shows that the reaction of Pu with N 2 has two pathways. The pathway-1 (Pu+N 2 →R1→TS1→PuN 2 ) has a T-shaped transition state and the pathway-2 (Pu+N 2 →R 2 →TS 2 →PuN+N) has a L-shaped transition state. Moreover, both transition states have only one virtual frequency. The energy analysis shows that pathway-1 is the main reaction pathway. The nature of the Pu-N bonding evolution along the pathways is studied by atoms in molecules (AIM) and electron localization function (ELF) topological approaches. In order to analyse the role of 5f orbital of plutonium atom in the reaction, the variation of density of state along the pathways is performed. The results show that the 5f orbital makes major contributions to the formation of Pu-N bonds. Meanwhile, the influence of different temperatures on the reaction rate is revealed by calculating the rate constants of the two reaction pathways.

Active Machine Learning for Chemical Dynamics Simulations. I. Estimating the Energy Gradient

Ab initio molecular dymamics (AIMD) simulation studies are a direct way to visualize chemical reactions and help elucidate non-statistical dynamics that does not follow the intrinsic reaction coordinate. However, due to the enormous amount of the ab initio energy gradient calculations needed for AIMD, it has been largely restrained to limited sampling and low level of theory (i.e., density functional theory with small basis sets). To overcome this issue, a number of machine learning (ML) methods have been employed to predict the energy gradient of the system of interest. In this manuscript, we outline the theoretical foundations of a novel ML method which trains from a varying set of atomic positions and their energy gradients, called interpolating moving ridge regression (IMRR), and directly predicts the energy gradient of a new set of atomic positions. Several key theoretical findings are presented regarding the inputs used to train IMRR and the predicted energy gradient. A hyperparameter used to guide IMRR is rigorously examined as well. The method is then applied to three bimolecular reactions studied with AIMD, including HBr+ + CO2, H2S + CH, and C4H2 + CH, to demonstrate IMRR’s performance on different chemical systems of different sizes. This manuscript also compares the computational cost of the energy gradient calculation with IMRR vs. ab initio, and the results highlight IMRR as a viable option to greatly increase the efficiency of AIMD.

Active Machine Learning for Chemical Dynamics Simulations. I. Estimating the Energy Gradient

Ab initio molecular dymamics (AIMD) simulation studies are a direct way to visualize chemical reactions and help elucidate non-statistical dynamics that does not follow the intrinsic reaction coordinate. However, due to the enormous amount of the ab initio energy gradient calculations needed for AIMD, it has been largely restrained to limited sampling and low level of theory (i.e., density functional theory with small basis sets). To overcome this issue, a number of machine learning (ML) methods have been employed to predict the energy gradient of the system of interest. In this manuscript, we outline the theoretical foundations of a novel ML method which trains from a varying set of atomic positions and their energy gradients, called interpolating moving ridge regression (IMRR), and directly predicts the energy gradient of a new set of atomic positions. Several key theoretical findings are presented regarding the inputs used to train IMRR and the predicted energy gradient. A hyperparameter used to guide IMRR is rigorously examined as well. The method is then applied to three bimolecular reactions studied with AIMD, including HBr+ + CO2, H2S + CH, and C4H2 + CH, to demonstrate IMRR’s performance on different chemical systems of different sizes. This manuscript also compares the computational cost of the energy gradient calculation with IMRR vs. ab initio, and the results highlight IMRR as a viable option to greatly increase the efficiency of AIMD.

Active Machine Learning for Chemical Dynamics Simulations. I. Estimating the Energy Gradient

Ab initio molecular dymamics (AIMD) simulation studies are a direct way to visualize chemical reactions and help elucidate non-statistical dynamics that does not follow the intrinsic reaction coordinate. However, due to the enormous amount of the ab initio energy gradient calculations needed for AIMD, it has been largely restrained to limited sampling and low level of theory (i.e., density functional theory with small basis sets). To overcome this issue, a number of machine learning (ML) methods have been employed to predict the energy gradient of the system of interest. In this manuscript, we outline the theoretical foundations of a novel ML method which trains from a varying set of atomic positions and their energy gradients, called interpolating moving ridge regression (IMRR), and directly predicts the energy gradient of a new set of atomic positions. Several key theoretical findings are presented regarding the inputs used to train IMRR and the predicted energy gradient. A hyperparameter used to guide IMRR is rigorously examined as well. The method is then applied to three bimolecular reactions studied with AIMD, including HBr+ + CO2, H2S + CH, and C4H2 + CH, to demonstrate IMRR’s performance on different chemical systems of different sizes. This manuscript also compares the computational cost of the energy gradient calculation with IMRR vs. ab initio, and the results highlight IMRR as a viable option to greatly increase the efficiency of AIMD.

Automating the IRC Analysis within Eyringpy

To analyze the evolution of a chemical property along the reaction path, we have to extract all the necessary information from a set of electronic structure computations. However, this process is time-consuming and prone to human error. Here we introduce IRC-Analysis, a new extension in Eyringpy, to monitor the evolution of chemical properties along the intrinsic reaction coordinate, including complete reaction force analysis. IRC-Analysis collects the entire data set for each point on the reaction coordinate, eliminating human error in data capture and allowing the study of several chemical reactions in seconds, regardless of the complexity of the systems. Eyringpy has a simple input format, and no programming skills are required. A tracer has been included to visualize the evolution of a given chemical property along the reaction coordinate. Several properties can be analyzed at the same time. This version can analysis the evolution of bond distances and angles, Wiberg bond indices, natural charges, dipole moments, and orbital energies (and related properties).

Six Low-Lying Isomers of C11H8 Are Unidentified in the Laboratory - a Theoretical Study

The potential energy surface of C₁₁H₈ has been theoretically examined using density functional theory and coupled-cluster methods. The current investigation reveals that 2aH-cyclopenta[cd]indene (<b>2</b>), 7-ethynyl-1H-indene (<b>6</b>), 4-ethynyl-1H-indene (<b>7</b>), 6-ethynyl-1H-indene(<b>8</b>), 5-ethynyl-1H-indene (<b>9</b>), and 7bH-cyclopenta[cd]indene (<b>10</b>) remain elusive to date in the laboratory. The puckered low-lying isomer <b>2</b> lies at 11 kJ mol⁻¹ below the experimentally known molecule, cyclobuta[de]naphthalene (<b>3</b>), at the fc-CCSD(T)/cc-pVTZ//fc-CCSD(T)/cc-pVDZ level of theory. <b>2</b> lies at 35 kJ mol⁻¹ above the thermodynamically most stable and experimentally known isomer, 1H-cyclopenta[cd]indene (<b>1</b>), at the same level. It is identified that 1,2-H transfer from <b>1</b> yields 2H-cyclopenta[cd]indene (<b>14</b>) and subsequent 1,2-H shift from <b>14</b> yields <b>2</b>. Appropriate transition states have been identified and intrinsic reaction coordinate calculations have been done at the B3LYP/6-311+G(d,p) level of theory. Recently, 1-ethynyl-1H-indene (<b>11</b>) has been detected using synchrotron based vacuum ultraviolet ionization mass spectrometry. 2-ethynyl-1H-indene (<b>4</b>) and 3-ethynyl-1H-indene (<b>5</b>) have been synthetically characterized in the past. While the derivatives of 7bH-cyclopenta[cd]indene (<b>10</b>) have been isolated elsewhere, the<br>parent compound remains unidentified to date in the laboratory. Although C₁₁H₈ is a key elemental composition in reactive intermediates chemistry and most of its isomers are having a non-zero dipole moment, to the best of our knowledge, none of them have been characterized by rotational spectroscopy. Therefore, energetic and spectroscopic properties have been computed and the present investigation necessitates new synthetic studies on C₁₁H₈, in particular <b>2</b>, <b>6</b>-<b>10</b>, and also rotational spectroscopic studies on all low-lying isomers.

Six Low-Lying Isomers of C11H8 Are Unidentified in the Laboratory - a Theoretical Study

The potential energy surface of C₁₁H₈ has been theoretically examined using density functional theory and coupled-cluster methods. The current investigation reveals that 2aH-cyclopenta[cd]indene (<b>2</b>), 7-ethynyl-1H-indene (<b>6</b>), 4-ethynyl-1H-indene (<b>7</b>), 6-ethynyl-1H-indene(<b>8</b>), 5-ethynyl-1H-indene (<b>9</b>), and 7bH-cyclopenta[cd]indene (<b>10</b>) remain elusive to date in the laboratory. The puckered low-lying isomer <b>2</b> lies at 11 kJ mol⁻¹ below the experimentally known molecule, cyclobuta[de]naphthalene (<b>3</b>), at the fc-CCSD(T)/cc-pVTZ//fc-CCSD(T)/cc-pVDZ level of theory. <b>2</b> lies at 35 kJ mol⁻¹ above the thermodynamically most stable and experimentally known isomer, 1H-cyclopenta[cd]indene (<b>1</b>), at the same level. It is identified that 1,2-H transfer from <b>1</b> yields 2H-cyclopenta[cd]indene (<b>14</b>) and subsequent 1,2-H shift from <b>14</b> yields <b>2</b>. Appropriate transition states have been identified and intrinsic reaction coordinate calculations have been done at the B3LYP/6-311+G(d,p) level of theory. Recently, 1-ethynyl-1H-indene (<b>11</b>) has been detected using synchrotron based vacuum ultraviolet ionization mass spectrometry. 2-ethynyl-1H-indene (<b>4</b>) and 3-ethynyl-1H-indene (<b>5</b>) have been synthetically characterized in the past. While the derivatives of 7bH-cyclopenta[cd]indene (<b>10</b>) have been isolated elsewhere, the<br>parent compound remains unidentified to date in the laboratory. Although C₁₁H₈ is a key elemental composition in reactive intermediates chemistry and most of its isomers are having a non-zero dipole moment, to the best of our knowledge, none of them have been characterized by rotational spectroscopy. Therefore, energetic and spectroscopic properties have been computed and the present investigation necessitates new synthetic studies on C₁₁H₈, in particular <b>2</b>, <b>6</b>-<b>10</b>, and also rotational spectroscopic studies on all low-lying isomers.

Isomeric Forms of Biologically Active 2-Aminopyrimidinium Picrate Through Intrinsic Reaction Coordinate Analysis and Spectroscopic Measurements

In the present study, the isomeric forms of a biologically active 2-Aminopyrimidinium picrate cocrystal were investigated using spectroscopic investigation and Density functional theory (DFT) calculations. The vibrational assignments of IR and Raman peaks were predicted and the experimental IR and Raman spectra of the condensed phase of 2-Aminopyrimidinium picrate were compared with the simulated one. The intrinsic reaction coordinate (IRC) analysis was performed on all the possible reaction pathways to identify the isomeric forms of 2APP and transition state (TS) geometry. From the IRC analysis, a relatively stable form (named as isomer 2) has been identified in addition to the existing isomeric form (isomer 1) in the crystalline packing of 2APP. The presence of non-covalent interactions within the isomeric forms of 2APP was investigated with the help of quantum topological atoms in molecules (QTAIM) analysis. Reactivity descriptors and charge delocalization from lone pair to acceptor entities of both the isomers were predicted to validate the interactions present and to understand the charge distribution within the molecule.