25 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…
Jing Li, Leyi Wei, Henry H Y Tong, Quan Zou
In early drug discovery, virtual screening based on deep learning, virtual screening based on molecular docking, and molecular dynamics are three widely used computational strategies, but they always face a trade-off between throughput, search stability, and physical fidelity. This article discusses how quantum…
Shuhei Kudo, Yusaku Yamamoto, Takeo Hoshi
We present a new computation method for simulating reflection high-energy electron diffraction and the total-reflection high-energy positron diffraction experiments. The two experiments are used commonly for the structural analysis of material surface. The present paper improves the conventional numerical method, the…
Rohan Chandraghatgi, Hai-Feng Ji, Gail L. Rosen, Bahrad A. Sokhansanj
Recent advances in computational methods provide the promise of dramatically accelerating drug discovery. While math-ematical modeling and machine learning have become vital in predicting drug-target interactions and properties, there is untapped potential in computational drug discovery due to the vast and complex…
Ragnar Bjornsson
We introduce ASH, a multi-scale, multi-theory modeling program for quantum mechanics (QM), molecular mechanics (MM), and hybrid calculations, written in the Python programming language. ASH is written in response to the increasingly diverse computational chemistry software landscape that features more QM and MM…
Hongyan Zhang, Yu Zhou, Yutao Li, Fu-Yun Li + 1 more
The problem-project-oriented STEM education plays a significant role in training students' ability of innovation. Although the conceive-design-implement-operate (CDIO) approach and the computational thinking (CT) are hot topics in recent decade, there are still two deficiencies: the CDIO approach and CT are discussed…
Jean-Louis Palgen, Angélique Perrillat-Mercerot, Nicoletta Ceres, Emmanuel Peyronnet + 6 more
Mechanistic models are built using knowledge as the primary information source, with well-established biological and physical laws determining the causal relationships within the model. Once the causal structure of the model is determined, parameters must be defined in order to accurately reproduce relevant data.…
Weitang Li, Zhi Yin, Xiaoran Li, Dongqiang Ma + 8 more
Quantum computing, with its superior computational capabilities compared to classical approaches, holds the potential to revolutionize numerous scientific domains, including pharmaceuticals. However, the application of quantum computing for drug discovery has primarily been limited to proof-of-concept studies, which…
Andrea Serani, Thomas P. Scholcz, Valentina Vanzi
This scoping review assesses the current use of simulation-based design optimization (SBDO) in marine engineering, focusing on identifying research trends, methodologies, and application areas. Analyzing 277 studies from Scopus and Web of Science, the review finds that SBDO is predominantly applied to optimizing marine…
Milena Rmus, Ti-Fen Pan, Liyu Xia, Anne G. E. Collins
Computational cognitive models have been used extensively to formalize cognitive processes. Model parameters offer a simple way to quantify individual differences in how humans process information. Similarly, model comparison allows researchers to identify which theories, embedded in different models, provide the best…
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…
Robert I. McLachlan
is the most common and is often all that is needed. It is variously called the leapfrog, St¨ormer–Verlet, or Strang splitting method. (Here Xi is the Hamiltonian vector field associated with Hamiltonian Hi , ehX is the time-h flow of the vector field X, and h is the time step.) For example, it is the basic building…
Zihao Li, Siguang An, Guoping Zou, Jianqiang Han + 1 more
In sensor design, electromagnetic field numerical simulation techniques are widely used to investigate the working principles of sensors. These analyses help designers understand how sensors detect and respond to external signals during operation. One popular method for electromagnetic field computation is the meshless…
Shiqiang Zhu, Ting Yu, Tao Xu, Hongyang Chen + 17 more
'Sylvain Gigan' 'Denız Gündüz' 'Ekram Hossain' 'Yaochu Jin' 'Feng‐Huei Lin' 'Бо Лю' 'Zhiguo Wan' 'Ji Zhang' 'Zhifeng Zhao' 'Wentao Zhu' 'Zuoning Chen' 'T.S. Durrani' 'Huaimin Wang' 'Jiangxing Wu' 'Tong‐Yi Zhang' 'Yunhe Pan'] Computing is a critical driving force in the development of human civilization. In recent…
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…
Andrew Simmonett, Bernard Brooks, Thomas Darden
Evaluation of noncovalent electrostatic interactions is the dominant bottleneck in classical molecular dynamics simulations, and evaluation of Coulombic matrix elements similarly limits quantum mechanical self consistent field calculations. These difficulties are a result of the Coulomb operator’s slow decay, which…
Gustavo Deco, Yonatan Sanz Perl, Jakub Vohryzek, Andrea Luppi + 1 more
The perhaps most important unsolved problem in neuroscience is how the brain survives in a complex world by performing a rich repertoire of computation on a minimal energy budget. The brain is much better at adapting to the multiplicity of stimuli and outcomes than current generations of computers, artificial neural…
Maja Rudolph, Stefan Kurz, Barbara Rakitsch
Design patterns provide a systematic way to convey solutions to recurring modeling challenges. This paper introduces design patterns for hybrid modeling, an approach that combines modeling based on first principles with data-driven modeling techniques. While both approaches have complementary advantages there are often…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Simone Severini
This piece plays with the idea of the Computocene: an era defined not merely by the ubiquity of computers, but by their deepening role in how we observe, interpret, and make sense of the world. Rather than emphasizing automation, speed, scale, or intelligence, computation is reframed as a mode of attention—filtering…
Authors not listed
Hybrid machine-learning/molecular-mechanics (ML/MM) methods extend the classical QM/MM paradigm by replacing the quantum desription with neural network interatomic potentials trained to reproduce accurately quantum-mechanical (QM) results. By describing only the chemically active region with ML and the surrounding…
Boon Xian Chai, Boris Eisenbart, Mostafa Nikzad, Bronwyn Fox + 12 more
'Yuqi Wang' 'Kyaw Hlaing Bwar' 'Kaiyu Zhang' 'Marcin Sosnowski' 'Jaroslaw Krzywanski' 'Karolina Grabowska' 'Dorian Skrobek' 'Ghulam Moeen Uddin' 'Yunfei Gao' 'Anna Zylka' 'Anna Kulakowska' 'Bachil El Fil'] The utilisation of numerical process simulation has greatly facilitated the challenging task of liquid composite…
Beatrix C. Hiesmayr, Marc‐Thorsten Hütt
A recent trend in mathematical modeling is to publish the computer code together with the research findings. Here we explore the formal question, whether and in which sense a computer implementation is distinct from the mathematical model. We argue that, despite the convenience of implemented models, a set of implicit…
Rosen Ting-Ying Yu, Cyril Picard, Faez Ahmed
Bayesian Optimization (BO) is a foundational strategy in engineering design optimization for efficiently handling black-box functions with many constraints and expensive evaluations. This paper introduces a novel constraint-handling framework for Bayesian Optimization (BO) using Prior-data Fitted Networks (PFNs), a…