Project description:The ab initio prediction of reaction rate constants for systems with hundreds of atoms with an accuracy that is comparable to experiment is a challenge for computational quantum chemistry. We present a divide-and-conquer strategy that departs from the potential energy surfaces obtained by standard density functional theory with inclusion of dispersion. The energies of the reactant and transition structures are refined by wavefunction-type calculations for the reaction site. Thermal effects and entropies are calculated from vibrational partition functions, and the anharmonic frequencies are calculated separately for each vibrational mode. This method is applied to a key reaction of an industrially relevant catalytic process, the methylation of small alkenes over zeolites. The calculated reaction rate constants (free energies), pre-exponential factors (entropies), and enthalpy barriers show that our computational strategy yields results that agree with experiment within chemical accuracy limits (less than one order of magnitude).
Project description:Pyrolysis is a promising technology for chemical recycling of waste plastics, since it enables the generation of high-value chemicals with low capital and operating cost. The calculation of thermodynamic equilibrium composition using the Gibbs free energy minimization approach can determine pyrolysis operating conditions that produce desired products. However, the availability of thermochemical data can limit the application of equilibrium calculations. While density functional theory (DFT) calculations have been commonly used to produce accurate thermochemical data (e.g., enthalpies of formation) of small molecules, the accuracy and computational cost of these calculations are both challenging to handle for large, flexible molecules, exhibiting multiple conformations at elevated (i.e., pyrolysis) temperatures. In this work, we develop a computational framework to calculate accurate, temperature-dependent thermochemistry of large and flexible molecules by combining force field based conformational search, DFT calculations, thermochemical corrections, and Boltzmann statistics. Our framework produces accurately calculated thermochemistry that is used to predict equilibrium thermal decomposition profiles of octadecane, a model compound of polyethylene. Our thermochemistry results are compared against literature data demonstrating a great agreement, and the predicted decomposition profiles rationalize a series of pyrolysis experimental observations. Our work systematically addresses entropic contributions of large molecules and suggests paths for accurate and yet computationally feasible calculations of Gibbs free energies. The first-principles-based thermodynamic equilibrium analysis proposed in this work can be a significant step toward predicting temperature-dependent product distributions from plastic pyrolysis and guide experimentation on chemical plastic recycling.
Project description:We present an on-the-fly ab initio semiclassical study of vibrational energy levels of glycine, calculated by Fourier transform of the wavepacket correlation function. It is based on a multiple coherent states approach integrated with monodromy matrix regularization for chaotic dynamics. All four lowest-energy glycine conformers are investigated by means of single-trajectory semiclassical spectra obtained upon classical evolution of on-the-fly trajectories with harmonic zero-point energy. For the most stable conformer I, direct dynamics trajectories are also run for each vibrational mode with energy equal to the first harmonic excitation. An analysis of trajectories evolved up to 50 000 atomic time units demonstrates that, in this time span, conformers II and III can be considered as isolated species, while conformers I and IV show a pretty facile interconversion. Therefore, previous perturbative studies based on the assumption of isolated conformers are often reliable but might be not completely appropriate in the case of conformer IV and conformer I for which interconversion occurs promptly.
Project description:Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations, and proton disorder. This is made possible by combining advanced free-energy methods and state-of-the-art machine-learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments and reliable estimates of the melting points of light and heavy water. We observe that nuclear-quantum effects contribute a crucial [Formula: see text] to the stability of ice Ih, making it more stable than ice Ic. Our computational approach is general and transferable, providing a comprehensive framework for quantitative predictions of ab initio thermodynamic properties using machine-learning potentials as an intermediate step.
Project description:The advent of machine learning potentials (MLPs) provides a unique opportunity to access simulation time scales and to directly compute physicochemical properties that are typically intractable using density functional theory (DFT). In this study, we use an active learning curriculum to train a generalizable MLP using the DeepMD-kit architecture. By using sufficiently long MLP-based molecular dynamics (MD) simulations, which provide DFT-level accuracy, we investigate the diffusion of key surface-bound adsorbates on a Ag(111) facet. Detailed analysis of the MLP/MD-calculated diffusivities sheds light on the potential shortcomings of using DFT-based nudged elastic band to estimate surface diffusion barriers. More generally, while this study is focused on a specific system, we anticipate that the underlying workflows and the resulting models can be extended to other adsorbates and other materials in the future.
Project description:Double-transition-metal MXenes (D-MXenes) have been widely pursued in the advancement of the renewable energy storage technology in recent years. In this work, the hydrogen evolution reaction (HER) catalytic mechanism of several oxygen-terminated D-MXenes with the chemical formula of M'2M″C2O2 (M' = Mo, Cr; M″ = Ti, V, Nb, Ta) is theoretically studied. For comparison, the corresponding monometallic MXenes (M-MXenes, M'3C2O2) are fairly compared by means of the density functional theory calculations. Based on our theoretical results, the HER performance of M-MXenes can be improved by constructing a "sandwich-like" ordered D-MXene configuration. Moreover, the HER performance of Mo-based D-MXenes (Mo2M″C2O2) is superior to that of Cr-based D-MXenes (Cr2M″C2O2), which highlights that the HER activity of Mo2VC2O2 and Mo2NbC2O2 is better than that of Pt(111). This work not only unravels the HER mechanism of D-MXenes (M'2M″C2O2) but also paves the way in designing emergent MXene-based HER electrocatalysts with high efficiency.
Project description:We applied relativistic multiconfigurational all-electron ab initio calculations including the spin-orbit interaction to calculate the 3d4f resonant inelastic X-ray scattering (RIXS) map (3d3/2 → 5f5/2 U M4 absorption edge and 4f5/2 → 3d3/2 U Mβ emission) of uranyl (UO22+). The calculated data are in excellent agreement with experimental results and allow a detailed understanding of the observed features and an unambiguous assignment of all involved intermediate and final states. The energies corresponding to the maxima of the resonant emission and the non-resonant (normal) emission were determined with high accuracy, and the corresponding X-ray absorption near edge structure spectra extracted at these two positions were simulated and agree well with the measured data. With the high quality of our theoretical data, we show that the cause of the splitting of the three main peaks in emission is due to the fine structure splitting of the 4f orbitals induced through the trans di-oxo bonds in uranyl and that we are able to obtain direct information about the energy differences between the 5f and 4f orbitals: Δ5f δ/ϕ - 4f δ/ϕ, Δ5f π* - 4f π, and Δ5f σ* - 4f σ from the 3d4f RIXS map. RIXS maps contain a wealth of information, and ab initio calculations facilitate an understanding of their complex structure in a clear and transparent way. With these calculations, we show that the multiconfigurational protocol, which is nowadays applied as a standard tool to study the X-ray spectra of transition metal complexes, can be extended to the calculation of RIXS maps of systems containing actinides.
Project description:High-pressure polymorphism and phase transitions have wide ranging consequences on the basic properties of ammonium nitrate. However, the phase diagram of ammonium nitrate at high pressure and high temperature is still under debate. This study systematically investigates the phase transitions and structural properties of ammonium nitrate at a pressure range of 5-60 GPa and temperature range of 250-400 K by ab initio molecular dynamics simulations. Two new phases are identified: one corresponds to the experimentally observed phase IV' and the other is named AN-X. Simultaneously, the lattice strains play a significant role in the formation and stabilization of phase IV', providing a reasonable explanation for experimental observation of phase IV-IV' transition which only appears under nonhydrostatic pressure. In addition, 12 O atoms neighboring the NH (N atom in ammonium cation) atom are selected as reference system to clearly display the tanglesome rotation of ammonium cation.
Project description:Macroscopic pKa values were calculated for all compounds in the SAMPL6 blind prediction challenge, based on quantum chemical calculations with a continuum solvation model and a linear correction derived from a small training set. Microscopic pKa values were derived from the gas-phase free energy difference between protonated and deprotonated forms together with the Conductor-like Polarizable Continuum Solvation Model and the experimental solvation free energy of the proton. pH-dependent microstate free energies were obtained from the microscopic pKas with a maximum likelihood estimator and appropriately summed to yield macroscopic pKa values or microstate populations as function of pH. We assessed the accuracy of three approaches to calculate the microscopic pKas: direct use of the quantum mechanical free energy differences and correction of the direct values for short-comings in the QM solvation model with two different linear models that we independently derived from a small training set of 38 compounds with known pKa. The predictions that were corrected with the linear models had much better accuracy [root-mean-square error (RMSE) 2.04 and 1.95 pKa units] than the direct calculation (RMSE 3.74). Statistical measures indicate that some systematic errors remain, likely due to differences in the SAMPL6 data set and the small training set with respect to their interactions with water. Overall, the current approach provides a viable physics-based route to estimate macroscopic pKa values for novel compounds with reasonable accuracy.
Project description:First-principles crystal structure prediction (CSP) is the most powerful approach for materials discovery, enabling the prediction and evaluation of properties of new solid phases based only on a diagram of their underlying components. Here, we present the first CSP-based discovery of metal-organic frameworks (MOFs), offering a broader alternative to conventional techniques, which rely on geometry, intuition, and experimental screening. Phase landscapes were calculated for three systems involving flexible Cu(II) nodes, which could adopt a potentially limitless number of network topologies and are not amenable to conventional MOF design. The CSP procedure was validated experimentally through the synthesis of materials whose structures perfectly matched those found among the lowest-energy calculated structures and whose relevant properties, such as combustion energies, could immediately be evaluated from CSP-derived structures.