26 papers · ranked by Valyu relevance
Jaroslaw Krzywanski, Marcin Sosnowski, Karolina Grabowska, Anna Zylka + 3 more
'Anna Zylka' 'Lukasz Lasek' 'Agnieszka Kijo-Kleczkowska' 'Bongju Kim'] This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends…
Oliver Lee, Malte Gather, Eli Zysman-Colman
We describe a new tool for the efficient management of computational chemistry. Digichem is a program that automates and simplifies nearly the entire computational pipeline, including large-scale batch submission of calculations, analysis and results parsing, the generation of 3D density plots and 2D graphs of…
Miroslav Kratochvíl, Laurent Heirendt, St Elmo Wilken, Taneli Pusa + 9 more
Understanding metabolic interactions in cells is a crucial step to investigate disease mechanisms and to discover new therapeutics (; ; ). Constraint-Based Reconstruction and Analysis (COBRA) is a promising methodology for analyzing various metabolic processes at the organism- and community- levels (). The main idea…
Authors not listed
We present an open source collection of scripts and programs for the setup, management and evaluation of calculations with the Vienna ab-initio simulation package (VASP), called utils4VASP. It contains 20 independent Python scripts and Fortran programs, all with a unified and intuitive handling concept based on command…
Piotr Kica, Magdalena Otta, Krzysztof Czechowic, Karol Zając + 4 more
'P. Nowakowski' 'Andrew Narracott' 'Ian Halliday' 'M. Malawski'] Abstract—Digital twins are virtual representations of physical objects or systems used for the purpose of analysis, most often via computer simulations, in many engineering and scientific disciplines. Recently, this approach has been introduced to…
Andrew Stokely, Lane Votapka, Marcus Hock, Abigail Teitgen + 3 more
We present the Netsci program - an open-source scientific software package that leverages GPU acceleration and a k-nearest-neighbor algorithm in order to estimate the mutual information (MI) between data in a set. The GPU acceleration presented here, as an improvement upon existing estimators, enables calculation…
Timothy M. Weigand
Title: Summary The Porous Media Morphology and Topology Toolkit (PMMoTo) is a software tool designed to help researchers analyze and understand porous structures and how their features influence behavior at larger scales. A porous medium is any solid material that contains pores, for example, soil, membranes, skin, and…
Emil Karlsen, Marianne Gylseth, Christian Schulz, Eivind Almaas
Flux balance analysis (FBA) remains one of the most used methods for modeling the entirety of cellular metabolism, and a range of applications and extensions based on the FBA framework have been generated. Dynamic flux balance analysis (dFBA), the expansion of FBA into the time domain, still has issues regarding…
Authors not listed
The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
Yuji Nakatsukasa, Olivier Sète, Lloyd N. Trefethen
The AAA algorithm, introduced in 2018, computes best or near-best rational approximations to functions or data on subsets of the real line or the complex plane. It is much faster and more robust than previous algorithms for such problems and has been used in many applications since its appearance, including the…
Sven Köppel, Bernd Ulmann, Lars Heimann, Dirk Killat
Analog computers can be revived as a feasible technology platform for low precision, energy efficient and fast computing. We justify this statement by measuring the performance of a modern analog computer and comparing it with that of traditional digital processors. General statements are made about the solution of…
Samantha Durdy, Cameron J. Hargreaves, Mark Dennison, Benjamin Wagg + 5 more
The discovery of new materials often requires collaboration between experimental and computational chemists. Web based platforms allow more flexibility in this collaboration by giving access to computational tools without the need for access to computational researchers. We present Liverpool Materials Discovery Server…
Nathan R. Kern, Soohyung Park, Yiwei Cao, Wonpil Im
As high-performance computing provides the ability to generate and analyze ever larger simulation trajectories, the challenges in learning, applying, and sharing the best analytical practices become more salient. Extracting reproducible scientific insights from simulation requires a thorough understanding of many…
Alex N Popinga, Jack Forman, Dmitri Svetlov, Huy Vo + 1 more
Biological data is prone to both intrinsic and extrinsic noise and variability between experimental replicas. That same stochasticity and heterogeneity can carry information about underlying biochemical mechanisms but, if not incorporated in modeling and probabilistic inference, can also bias parameter estimates and…
Alexander J. Bryer, Juan R. Perilla
Dimensionality reduction via coarse grain modeling has positioned itself as an indispensable tool for decades, particularly for biomolecular simulations where atomic systems encompass hundreds of millions of atoms. While distinct flavors of coarse grain modeling exist, those occupying the coarse end of the spectrum are…
Rachel Mester, Alfonso Landeros, Chris Rackauckas, Kenneth Lange + 1 more
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to…
Nafiul Nipu, Carla Floricel, Negar Naghashzadeh, Roberto Paoli + 1 more
Contrails are condensation trails generated from emitted particles by aircraft engines, which perturb Earth’s radiation budget. Simulation modeling is used to interpret the formation and development of contrails. These simulations are computationally intensive and rely on high-performance computing solutions, and the…
Authors not listed
Traditional and non-classical machine learning models for solid-state structure prediction have predominantly relied on compositional features (derived from properties of constituent elements) to predict the existence of structure and its properties. However, the lack of structural information can be a source of…
Kazuki Maeda, Thiago Teixeira, Jonathan M. Wang, Jeffrery Hokanson + 5 more
'Caetano Melone' 'Mario Di Renzo' 'Steven J.M. Jones' 'Javier Urzay' 'Gianluca Iaccarino'] An integrated computational framework is introduced to study complex engineering systems through physicsbased ensemble simulations on heterogeneous supercomputers. The framework is primarily designed for the quantitative…
Cefe López
Artificial intelligence is gaining strength and materials science can both contribute to and profit from it. In a simultaneous progress race, new materials, systems and processes can be devised and optimized thanks to machine learning techniques and such progress can be turned into innovative computing platforms.…
Jens Hansen, Abhinav R. Jain, Philip Nenov, Peter N. Robinson + 1 more
'Ravi Iyengar'] Cell level functions underlie tissue and organ physiology. Gene expression patterns offer extensive views of the pathways and processes within and between cells. Single cell transcriptomics provides detailed information on gene expression within cells, cell types, subtypes and their relative proportions…
Andrew McCluskey, Miguel Rivera, Antonia Mey
The role of computing in the chemical sciences is changing. Previously the domain of the theoretical or computational chemist, advanced digital skills, including data analysis and simulation, are becoming extremely relevant to all. Here, we discuss the importance of integrating computing and digital skills into an…
Cedric P. van den Berg, Nicholas D. Condon, Cara Conradsen, Thomas E. White + 1 more
Animal and plant colouration presents a striking dimension of phenotypic variation, the study of which has driven general advances in ecology, evolution, and animal behaviour. Quantitative Colour Pattern Analysis (QCPA) is a dynamic framework for analysing colour patterns through the eyes of non-human observers.…
Nang Xuan Ho, Tien-Thinh Le, The-Hung Dinh, Van-Hai Nguyen
This article deals with prediction of buckling damage of steel equal angle structural members using a surrogate model combining machine learning and metaheuristic optimization technique. In particular, a hybrid Artificial Intelligence (AI)-based model involving Artificial Neural Network (ANN) and Particle Swarm…
Georges Czaplicki, Serge Mazeres
Model validation depends on the agreement between the predicted and experimental data. However, finding solutions to problems, described by equations with many parameters, for which virtually nothing is known, is a difficult task. For example, the extraction of kinetic parameters from complex schemes representing the…
Rostyslav Hnatyshyn, J. L. Zhao, Danny Pérez, James Ahrens + 1 more
In this section, we discuss several works that directly inspired views in MolSieve. Tominski et al. developed a multi-attribute temporal view for a spatial trajectory by stacking horizon charts representing each attribute. This stacked trajectory chart is then rendered on top of 3D map data to facilitate a…