11 papers · ranked by Valyu relevance
Wataru Takahara, Ryuto Baba, Yosuke Harashima, Tomoaki Takayama + 4 more
In the field of data-driven material development, bias in a dataset often causes difficulties in building a regression model when machine learning methods are applied. One of inorganic functional materials facing such a difficulty is photocatalysts. In this study, we propose a two-stage machine learning model to…
Tobias Seidel, Lena-Marie Ränger, Thomas Grützner, Michael Bortz
In this work we present a new approach that we use to simulate and optimize multiple dividing wall columns at the same time. Instead of considering all model equations as constraints and all process variables as optimization variables in a large and highly nonlinear optimization problem we only incorporate a subset of…
Fuzhan Rahmanian, Robert M. Lee, Dominik Linzner, Kathrin Michel + 4 more
Predicting and monitoring battery life early and across chemistries is a significant challenge due to the plethora of degradation paths, form factors, and electrochemical testing protocols. Existing models typically translate poorly across different electrode, electrolyte, and additive materials, mostly require a fixed…
Xinyi Zhang, William Arnold, Natasha Wright, Paige Novak + 1 more
This study aims to support the prioritization of research and development (R&D) pathways of hydrogel-encapsulated anaerobic technology to treat high-strength organic industrial wastewaters, enabling decentralized energy recovery and treatment to reduce organic loading on centralized treatment facilities. To…
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We present an algorithm for finding chemical reaction pathways using a Monte-Carlo transition state search (MCTSS) scheme. Our strategy is a bidirectional two-state approach that simultaneously drives two Monte-Carlo trajectories from reactants to products and vice versa, until the trajectories meet. The trajectories…
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Identifying synthesis routes from knowledge graphs poses challenges beyond retrosynthesis, including path–finding artifacts and data issues. We introduce “SynGPS”, a novel algorithm that overcomes these limitations by identifying viable routes even with common artifacts. SynGPS can resolve nonsensical cycles…
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Efficient and reliable identification of transition states (TS) is critical for reaction modelling. Among the approaches available, the combination of double-ended TS search with eigenvector-following, referred to as “hierarchical TS search”, is an effective tool to locate TSs starting from reactant and product…
Eric Hermes, Khachik Sargsyan, Habib Najm, Judit Zádor
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…
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Two kinetic schemes of the general modifier mechanism have been analysed in a quasi-steady state approximation, assuming that the reaction product concentration is negligible (a natural assumption for the initial rate method) and without additional simplifying assumptions. The characteristic equations have been…
Oskar Weser, Ali Alavi, Giovanni Li Manni
In this paper we propose an improved excitation generation algorithm for the full configuration interaction quantum monte carlo (FCIQMC) method, which is particularly effective in systems described by localized orbitals. The method is an extension of the precomputed heat-bath (PCHB) strategy of Holmes et al., with more…
Yann Garniron, Thomas Applencourt, Kevin Gasperich, Anouar Benali + 15 more
Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multi-reference second-order perturbation theory (PT2). The determinant-driven…