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Traditional Genetic Algorithms (GAs) mating schemes select individuals for crossover independently of their genotypic or phenotypic similarities. In Nature, this behaviour is known as random mating. However, non-random schemes - in which…

Neural and Evolutionary Computing · Computer Science 2009-09-30 C. M. Fernandes , J. J. Merelo , A. C. Rosa

We propose a genetic algorithm (GA) based method for modifying n-best lists produced by a machine translation (MT) system. Our method offers an innovative approach to improving MT quality and identifying weaknesses in evaluation metrics.…

Computation and Language · Computer Science 2023-06-01 Josef Jon , Ondřej Bojar

The underlying structural order that transcends the liquid, glass and crystalline states is identified using an efficient genetic algorithm (GA). GA identifies the most common energetically favorable packing motif in crystalline structures…

In genome-wide association studies (GWASs), there is an increasing need for detecting the associations between a genetic variant and multiple traits. In studies of complex diseases, it is common to measure several potentially correlated…

Methodology · Statistics 2021-02-04 Qiaolan Deng , Chi Song

The Gauge-Including Projector Augmented Wave (GIPAW) method, within the Density Functional Theory (DFT) Generalized Gradient Approximation (GGA) framework, is applied to compute solid state NMR parameters for $^{27}Al$ in the $\alpha$,…

Materials Science · Physics 2015-05-30 Ary R. Ferreira , Emine Küçükbenli , Alexandre A. Leitão , Stefano de Gironcoli

We developed new modified embedded-atom method (MEAM) interatomic potentials for the Mg-Al alloy system using a first-principles method based on density functional theory (DFT). The materials parameters, such as the cohesive energy,…

Materials Science · Physics 2013-05-29 B. Jelinek , J. Houze , Sungho Kim , M. F. Horstemeyer , M. I. Baskes , Seong-Gon Kim

Crystal structure prediction (CSP), which aims to predict the three-dimensional atomic arrangement of a crystal from its composition, is central to materials discovery and mechanistic understanding. However, given the composition in a unit…

Materials Science · Physics 2026-03-10 Shi Yin , Jinming Mu , Xudong Zhu , Linxin He

Nigam et al. reported a genetic algorithm (GA) utilizing the SELFIES representation and also propose an adaptive, neural network-based penalty that is supposed to improve the diversity of the generated molecules. The main claims of the…

Machine Learning · Computer Science 2021-02-11 Kevin Maik Jablonka , Fergus Mcilwaine , Susana Garcia , Berend Smit , Brian Yoo

Genetic algorithms are a class of heuristic search techniques that apply basic evolutionary operators in a computational setting. We have designed a fully parallel and distributed hardware/software implementation of the generalized…

Astrophysics · Physics 2009-11-07 T. S. Metcalfe , P. Charbonneau

Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. Nevertheless, ML-accelerated discovery both inherits the…

Materials Science · Physics 2022-05-09 Chenru Duan , Fang Liu , Aditya Nandy , Heather J. Kulik

Approximate density functional theory (DFT) has become indispensable owing to its cost-accuracy trade-off in comparison to more computationally demanding but accurate correlated wavefunction theory. To date, however, no single density…

Chemical Physics · Physics 2022-07-25 Chenru Duan , Aditya Nandy , Ralf Meyer , Naveen Arunachalam , Heather J. Kulik

A genetic algorithm (GA) is a search-based optimization technique based on the principles of Genetics and Natural Selection. We present an algorithm which enhances the classical GA with input from quantum annealers. As in a classical GA,…

Quantum Physics · Physics 2022-09-16 Steven Abel , Luca A. Nutricati , Michael Spannowsky

The paper describes an extension of the Liga algorithm for structure solution from atomic pair distribution function (PDF), to handle periodic crystal structures with multiple elements in the unit cell. The procedure is performed in 2…

Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of Group IV, III-V, and II-VI zinc blende (ZB) semiconductors, powered by crystal Graph-based Neural Networks…

Crystal structure prediction has traditionally relied on prototype-based seeding, approaches that often bias sampling toward known low-energy basins and overlook metastable polymorphs with unconventional symmetries. Here, we introduce…

Materials Science · Physics 2026-04-24 Jiexi Song , Diwei Shi , Aixian She , Chongde Cao , Fengyuan Xuan

The structural, dynamical, and thermodynamical properties of diamond, graphite and layered derivatives (graphene, rhombohedral graphite) are computed using a combination of density-functional theory (DFT) total-energy calculations and…

Materials Science · Physics 2009-11-10 Nicolas Mounet , Nicola Marzari

Discovering materials with new structural chemistry is key to achieving transformative functionality. Generative artificial intelligence offers a scalable route to propose candidate crystal structures. We introduce a reliable low-cost proxy…

Genetic algorithm (GA) belongs to a class of nature-inspired evolutionary algorithms that leverage concepts from natural selection to perform optimization tasks. In cosmology, the standard method for estimating parameters is the Markov…

Cosmology and Nongalactic Astrophysics · Physics 2025-12-15 Reginald Christian Bernardo , Yun Chen

We discuss the efficacy of evolutionary method for the purpose of structural analysis of amorphous solids. At present ab initio molecular dynamics (MD) based melt-quench technique is used and this deterministic approach has proven to be…

Materials Science · Physics 2016-08-03 Suhas Nahas , Anshu Gaur , Somnath Bhowmick

Drug target binding affinity (DTA) is a key criterion for drug screening. Existing experimental methods are time-consuming and rely on limited structural and domain information. While learning-based methods can model sequence and structural…

Machine Learning · Computer Science 2024-06-26 Xi Xiao , Wentao Wang , Jiacheng Xie , Lijing Zhu , Gaofei Chen , Zhengji Li , Tianyang Wang , Min Xu
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