Force Training Neural Network Potential Energy Surface Models

Machine learned chemical potentials have shown great promise as alternatives to conventional computational chemistry methods to represent the potential energy of a given atomic or molecular system as a function of its geometry. However, such potentials are only as good as the data they are trained on, and building a comprehensive training set can be a costly process. Therefore, it is important to extract as much information from training data as possible without further increasing the computational cost. One way to accomplish this is by training on molecular forces in addition to energies. This allows for three additional labels per atom within the molecule. Here we develop a neural network potential energy surface for studying a hydrogen transfer reaction between two conformers of C5H5. We show that, for a much smaller training set, force training can greatly improve the accuracy of the model compared to only training to energies. We also demonstrate the importance of choosing the proper force to energy weight ratio for the loss function to minimize the model test error

Lokális és globális érzékenység-analízis új alkalmazásai a kémiai kinetikában = New applications of local and global sensitivity analysis in chemical kinetics

Az OTKA pályázat keretében végzett kutatások részletes reakciómechanizmusok vizsgálatával foglalkoztak. A kémiai rendszerek meglehetősen szerteágazóak voltak: hidrogén, szénmonoxid és metán égése; metán pirolízise; számos tüzelőanyag (H2, CO, CH4, C2H4, C3H6) oxigénnel alkotott elegyének gyulladása polikristályos platinafelületen; fotokémiai reakciók vizsgálata szmogkamrában és szennyezett szabad levegőben; CCl4 megsemmisítése plazmában reduktív és oxidatív körülmények között; egy biokémiai kinetikai rendszer, a sarjadzó élesztő sejtosztódásának vizsgálata. Minden esetben a vizsgált kémiai folyamatot részletes reakciómechanizmussal írtuk le, ennek alapján szimulációkat végeztünk, és a kapott eredményeket mérési adatokkal hasonlítottuk össze. A mérések vagy a jellemző alkalmazás körülményeinél elvégeztük a reakciórendszerek analízisét. Igénybe vettük a mások által, vagy éppen általunk korábban kifejlesztett módszereket is, de egy sor mechanizmusvizsgálati módszert e kutatások során fejlesztettünk ki és elsőként alkalmaztunk. Ilyen módszerek például a lokális érzékenységi vektorok korrelációjának vizsgálata, a lángsebesség-érzékenységek globális bizonytalanság-analízise, vagy a komponenstér dinamikus dimenziója változásának és az érzékenységi függvények globális hasonlóságának összehasonlítása. A kutatások következtében számos új kémiai ismerethez jutottunk a vizsgált rendszerekről, és új reakciómechanizmus-vizsgáló eszközöket vezettünk be. | All investigations in the project were related to the analysis of detailed reaction mechanisms. A wide variety of chemical systems were investigated, which included the combustion of hydrogen, wet CO and methane; pyrolysis and oxidative pyrolysis of methane; ignition of fuel-oxygen mixtures on polycrystalline platinum catalyst, where the fuels were H2, CO, CH4, C2H4, and C3H6; photochemical ozone formation in smog chambers and in ambient air; decomposition of carbon tetrachloride in RF thermal plasma reactor at neutral and oxidative conditions; molecular regulation network of the cell cycle of budding yeast. In all cases the system was described by a set of chemical reaction steps, simulations were carried out and the reaction mechanism was investigated at the experimental conditions or the conditions of typical applications. The analyses of mechanisms were carried out using tools that had been developed earlier, but also several new tools for mechanism analysis was developed during the project. These new tools include the analysis of the correlation of the local sensitivity vectors, global uncertainty analysis of local sensitivity coefficients, and contrasting the shape of the local sensitivity functions with the change of the dynamical dimension during the simulations. As a result of the project, new chemical knowledge was obtained about the systems investigated and several new methods were introduced for the analysis of complex reaction mechanisms

Time scale and dimension analysis of a budding yeast cell cycle model

BACKGROUND: The progress through the eukaryotic cell division cycle is driven by an underlying molecular regulatory network. Cell cycle progression can be considered as a series of irreversible transitions from one steady state to another in the correct order. Although this view has been put forward some time ago, it has not been quantitatively proven yet. Bifurcation analysis of a model for the budding yeast cell cycle has identified only two different steady states (one for G1 and one for mitosis) using cell mass as a bifurcation parameter. By analyzing the same model, using different methods of dynamical systems theory, we provide evidence for transitions among several different steady states during the budding yeast cell cycle. RESULTS: By calculating the eigenvalues of the Jacobian of kinetic differential equations we have determined the stability of the cell cycle trajectories of the Chen model. Based on the sign of the real part of the eigenvalues, the cell cycle can be divided into excitation and relaxation periods. During an excitation period, the cell cycle control system leaves a formerly stable steady state and, accordingly, excitation periods can be associated with irreversible cell cycle transitions like START, entry into mitosis and exit from mitosis. During relaxation periods, the control system asymptotically approaches the new steady state. We also show that the dynamical dimension of the Chen's model fluctuates by increasing during excitation periods followed by decrease during relaxation periods. In each relaxation period the dynamical dimension of the model drops to one, indicating a period where kinetic processes are in steady state and all concentration changes are driven by the increase of cytoplasmic growth. CONCLUSION: We apply two numerical methods, which have not been used to analyze biological control systems. These methods are more sensitive than the bifurcation analysis used before because they identify those transitions between steady states that are not controlled by a bifurcation parameter (e.g. cell mass). Therefore by applying these tools for a cell cycle control model, we provide a deeper understanding of the dynamical transitions in the underlying molecular network

Проектирование расписания движения городского пассажирского транспорта на основе одноприборной задачи теории расписания

The branched C alcohol isopentanol (3-methylbutan-1-ol) has shown promise as a potential biofuel both because of new advanced biochemical routes for its production and because of its combustion characteristics, in particular as a fuel for homogeneous-charge compression ignition (HCCI) or related strategies. In the present work, the fundamental autoignition chemistry of isopentanol is investigated by using the technique of pulsed-photolytic Cl-initiated oxidation and by analyzing the reacting mixture by time-resolved tunable synchrotron photoionization mass spectrometry in low-pressure (8 Torr) experiments in the 550-750 K temperature range. The mass-spectrometric experiments reveal a rich chemistry for the initial steps of isopentanol oxidation and give new insight into the low-temperature oxidation mechanism of medium-chain alcohols. Formation of isopentanal (3-methylbutanal) and unsaturated alcohols (including enols) associated with HO production was observed. Cyclic ether channels are not observed, although such channels dominate OH formation in alkane oxidation. Rather, products are observed that correspond to formation of OH via β-C-C bond fission pathways of QOOH species derived from β- and γ-hydroxyisopentylperoxy (RO ) radicals. In these pathways, internal hydrogen abstraction in the RO QOOH isomerization reaction takes place from either the -OH group or the C-H bond in α-position to the -OH group. These pathways should be broadly characteristic for longer-chain alcohol oxidation. Isomer-resolved branching ratios are deduced, showing evolution of the main products from 550 to 750 K, which can be qualitatively explained by the dominance of RO chemistry at lower temperature and hydroxyisopentyl decomposition at higher temperature

Accelerated Saddle Point Refinement Through Full Exploitation of Partial Hessian Diagonalization

Identification and refinement of first order saddle point (FOSP) structures on the potential energy surface (PES) of chemical systems is a computational bottleneck in the characterization of reaction pathways. Leading FOSP refinement strategies require calculation of the full Hessian matrix, which is not feasible for larger systems such as those encountered in heterogeneous catalysis. For these systems, the standard approach to FOSP refinement involves iterative diagonalization of the Hessian, but this comes at the cost of longer refinement trajectories due to the lack of accurate curvature information. We present a method for incorporating information obtained by an iterative diagonalization algorithm into the construction of an approximate Hessian matrix that accelerates FOSP refinement. We measure the performance of our method with two established FOSP refinement benchmarks and find a 50% reduction on average in the number of gradient evaluations required to converge to a FOSP for one benchmark, and a 25% reduction on average for the second benchmark

Computational Chemistry of Cyclopentane Low Temperature Oxidation

Abstract Cycloalkanes are significant constituents of conventional fossil fuels, but little is known concerning their combustion chemistry and kinetics, particularly at low temperatures. This study investigates the pressure dependent kinetics of several reactions occurring during low-temperature cyclopentane combustion using theoretical chemical kinetics. The reaction pathways of the cyclopentyl + O 2 adduct is traced to alkylhydroperoxide, cyclic ether, β-scission and HO 2 elimination products. The calculations are carried out at the UCCSD(T)-F12b/cc-pVTZ-F12//M06-2X/6-311++G(d,p) level of theory. The barrierless entrance channel is treated using variable-reaction-coordinate transition state theory (VRC-TST) at the CASPT2(7e,6o) level of theory, including basis set, geometry relaxation and ZPE corrections. 1-D time-dependent multiwell master equation analysis is used to determine pressure-and temperature-dependent rate parameters of all investigated reactions. Tunneling corrections are included using Eckart barriers. Comparison with cyclohexane is used to elucidate the effect of ring size on the low temperature reactivity of naphthenes. The rate coefficients reported herein are suitable for use in cyclopentane and methylcyclopentane combustion models, even below ~900 K, where ignition is particularly sensitive to these pressure-dependent values

Geometry Optimization Speedup Through a Geodesic Approach to Internal Coordinates

We present a new geodesic-based method for geometry optimization in a basis of redundant internal coordinates. Our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate manifold, which dramatically reduces the number of steps required to converge to a minimum. Our method can be implemented in any existing optimization code, requiring only implementation of derivatives of the Wilson B-matrix and the ability to numerically solve an ordinary differential equation

Sella, an open-source automation-friendly molecular saddle point optimizer

We present a new algorithm for the optimization of molecular structures to saddle points on the potential energy surface using a redundant internal coordinate system. This algorithm automates the procedure of defining the internal coordinate system, including the handling of linear bending angles, e.g. through the addition of dummy atoms. Additionally, the algorithm supports constrained optimization using the null-space sequential quadratic programming formalism. Our algorithm determines the direction of the reaction coordinate through iterative diagonalization of the Hessian matrix, and does not require evaluation of the full Hessian matrix. Geometry optimization steps are chosen using the restricted step partitioned rational function optimization method, and displacements are realized using a high-performance geodesic stepping algorithm. This results in a robust and efficient optimization algorithm suitable for use in automated frameworks. We have implemented our algorithm in Sella, an open source software package designed to optimize atomic systems to saddle point structures. We also introduce a new benchmark test comprising 500 molecular structures that approximate saddle point geometries and show that our saddle point optimization algorithm outperforms the algorithms implemented in several leading electronic structure theory packages