相关论文: ChemKED: a human- and machine-readable data standa…
The ignition delay of a fuel/air mixture is an important quantity in designing combustion devices, and these data are also used to validate chemical kinetic models for combustion. One of the typical experimental devices used to measure the…
Efficient chemical kinetic model inference and application in combustion are challenging due to large ODE systems and widely separated time scales. Machine learning techniques have been proposed to streamline these models, though strong…
Side-by-side comparison of detailed kinetic models using a new tool to aid recognition of species structures reveals significant discrepancies in the published rates of many reactions and thermochemistry of many species. We present a first…
We develop a Python-based open-source package to analyze the results stemming from ab initio molecular-dynamics simulations of fluids. The package is best suited for applications on natural systems, like silicate and oxide melts,…
Recent advancements in language models have started a new era of superior information retrieval and content generation, with embedding models playing an important role in optimizing data representation efficiency and performance. While…
In the present work we compare reliability of several most widely used reduced detailed chemical kinetic schemes for hydrogen-air and hydrogen-oxygen combustible mixtures. The validation of the schemes includes detailed analysis of 0D and…
Foundation models have shown remarkable success across scientific domains, yet their impact in chemistry remains limited due to the absence of diverse, large-scale, high-quality datasets that reflect the field's multifaceted nature. We…
Astrochemical modeling is needed for understanding the formation and evolution of interstellar molecules, and for extracting physical information from spectroscopic observations of interstellar clouds. The modeling usually involves handling…
Chemical modelling serves two purposes in dynamical models: accounting for the effect of microphysics on the dynamics and providing observable signatures. Ideally, the former must be done as part of the hydrodynamic simulation but this…
Coarse-grained modeling in molecular simulations serves not only to extend accessible time and length scales beyond atomistic limits, but also to reduce high-dimensional chemical data to low-dimensional representations that expose the…
This paper introduces ChemGen, a software package that uses code generation to integrate multispecies thermodynamics and chemical kinetics into C+-based computational physics codes. ChemGen aims to make chemical kinetics more accessible in…
A novel extension of a rapid compression machine (RCM), namely a Rapid Compression Expansion Machine (RCEM), is described and its use for studying chemical kinetics is demonstrated. Like conventional RCMs, the RCEM quickly compresses a…
Early-stage fire scenes (0-15 minutes after ignition) represent a crucial temporal window for emergency interventions. During this stage, the smoke produced by combustion significantly reduces the visibility of surveillance systems,…
Accurate simulations of combustion phenomena require the use of detailed chemical kinetics in order to capture limit phenomena such as ignition and extinction as well as predict pollutant formation. However, the chemical kinetic models for…
NOMAD CAMELS (short: CAMELS) is a configurable, open-source measurement software that records fully self-describing experimental data. It has its origins in the field of experimental physics where a wide variety of measurement instruments…
The development of chemical engineering technology is a multi-stage process that encompasses laboratory research, scaling up, and industrial deployment. This process demands interdisciplinary col laboration and typically incurs significant…
There is currently a lot of activity in R\&D for future collider experiments. Multiple detector prototypes are being tested, each one with slightly different requirements regarding the format of the data to be analysed. This has generated a…
In many scientific fields, there is an interest in understanding the way in which complex chemical networks evolve. The chemical networks which researchers focus upon, have become increasingly complex and this has motivated the development…
The dynamic mode decomposition (DMD) is a simple and powerful data-driven modeling technique that is capable of revealing coherent spatiotemporal patterns from data. The method's linear algebra-based formulation additionally allows for a…
AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem. 2018, 39, 1922-1930). This release features a number of new capabilities: rare-event molecular dynamics…