ALTRUISM: A Higher Calling

Field-Theodore, Terri E.; Taylor, Peter R.

doi:10.1021/acs.jctc.0c00388

“…We note that the TRIM scheme is readily generalized to searches for higher-order transition states, as shown in recent work by Field-Theodore and Taylor. 52 In the present context, the last element of eq 43 corresponding to the chemical potential would have its sign reversed and the corresponding eigenvalue of the Hessian in eq 44 would also have its sign reversed. While not all functions have a corresponding image, 53 in second-order optimization schemes we only require that the second-order Taylor expansion around a given reference point has an image function.…”

Section: ■ Optimization Methods In Of-dftmentioning

confidence: 82%

“…Extensions to determine higher-order saddle points in the context of geometry optimization have been reported recently. 52…”

Section: ■ Molecular Systemsmentioning

confidence: 99%

Robust All-Electron Optimization in Orbital-Free Density-Functional Theory Using the Trust-Region Image Method

Ryley

¹

,

Withnall

²

,

Irons

³

et al. 2020

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We present a Gaussian-basis implementation of orbital-free density-functional theory (OF-DFT) in which the trust-region image method (TRIM) is used for optimization. This second-order optimization scheme has been constructed to provide benchmark all-electron results with very tight convergence of the particle-number constraint, associated chemical potential, and electron density. It is demonstrated that, by preserving the saddle-point nature of the optimization and simultaneously optimizing the density and chemical potential, an order of magnitude reduction in the number of iterations required for convergence is obtained. The approach is compared and contrasted with a new implementation of the nested optimization scheme put forward by Chan, Cohen, and Handy. Our implementation allows for semilocal kinetic-energy (and exchange−correlation) functionals to be handled self-consistently in all-electron calculations. The all-electron Gaussian-basis setting for these calculations will enable direct comparison with a wide range of standard high-accuracy quantum-chemical methods as well as with Kohn−Sham density-functional theory. We expect that the present implementation will provide a useful tool for analyzing the performance of approximate kinetic-energy functionals in finite systems.

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“…We note that the TRIM scheme is readily generalized to searches for higher-order transition states, as shown in recent work by Field-Theodore and Taylor. 52 In the present context, the last element of Eq. ( 43) corresponding to the chemical potential would have its sign reversed and the corresponding eigenvalue of the Hessian in Eq.…”

Section: The Cohen-chan-handy (Cch) Methodsmentioning

confidence: 96%

“…Extensions to determine higher-order saddle points in the the context of geometry optimization have been reported recently. 52…”

Section: Molecular Binding and Size-consistencymentioning

confidence: 99%

Robust All-Electron Optimization in Orbital-Free Density Functional Theory Using the Trust Region Image Method

Ryley,

Withnall,

Irons

et al. 2020

Preprint

0

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We present a Gaussian-basis implementation of orbital-free density-functional theory (OF-DFT) in which the trust-region image method (TRIM) is used for optimization. This second-order optimization scheme has been constructed to provide benchmark all-electron results with very tight convergence of the particle-number constraint, associated chemical potential and electron density. It is demonstrated that, by preserving the saddle-point nature of the optimization and simultaneously optimizing the density and chemical potential, an order of magnitude reduction in the number of iterations required for convergence is obtained. The approach is compared and contrasted with a new implementation of the nested optimization scheme put forward by

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“…26 If the barrier to products is a mountain range, the transition state is the highest point on the most accessible pass through this range. 27 Transition states are not readily found without a suitable initial geometry. The high dimensionality of the coordinate space of even moderately sized molecules precludes any brute force search, 28 and characterizing transition states requires costly second-derivative calculations.…”

mentioning

confidence: 99%

Automatic discovery of chemical reactions using imposed activation

Lavigne

¹

,

Gomes²,

Pollice³

et al. 2020

Preprint

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Computational power and quantum chemical methods have improved immensely since computers were first applied to the study of reactivity, but the de novo prediction of chemical reactions has remained challenging. We show that complex reactions can be efficiently and autonomously predicted using chemical activation imposed by simple geometrical constraints. Our approach is demonstrated on realistic and challenging chemistry, such as a triple cyclization cascade involved in the total synthesis of a natural product and several oxidative addition reactions of complex drug-like molecules. Notably and in contrast with traditional hand-guided computational chemistry calculations, our method requires minimal human involvement and no prior knowledge of products or mechanisms. Imposed activation can be a transformational tool to screen for chemical reactivity and mechanisms as well as to study byproduct formation and decomposition.<br>

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ALTRUISM: A Higher Calling

Cited by 9 publications

References 44 publications

Robust All-Electron Optimization in Orbital-Free Density-Functional Theory Using the Trust-Region Image Method

Robust All-Electron Optimization in Orbital-Free Density-Functional Theory Using the Trust-Region Image Method

Robust All-Electron Optimization in Orbital-Free Density Functional Theory Using the Trust Region Image Method

Automatic discovery of chemical reactions using imposed activation

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