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The design of intelligent materials often draws parallels with the complex adaptive behaviors of biological organisms, where robust functionality stems from sophisticated hierarchical organization and emergent long-distance coordination…

Soft Condensed Matter · Physics 2025-11-13 Vladimir A. Baulin , Rudolf M. Füchslin , Achille Giacometti , Helmut Hauser , Marco Werner

Materials informatics offers a promising pathway towards rational materials design, replacing the current trial-and-error approach and accelerating the development of new functional materials. Through the use of sophisticated data analysis…

Materials Science · Physics 2018-05-17 Cormac Toher , Corey Oses , Stefano Curtarolo

Materials informatics, data-enabled investigation, is a "fourth paradigm" in materials science research after the conventional empirical approach, theoretical science, and computational research. Materials informatics has two essential…

Materials Science · Physics 2023-05-09 Bhupesh Bishnoi

Molecular optimization is a key challenge in drug discovery and material science domain, involving the design of molecules with desired properties. Existing methods focus predominantly on single-property optimization, necessitating…

Machine Learning · Computer Science 2024-09-13 Aye Phyu Phyu Aung , Jay Chaudhary , Ji Wei Yoon , Senthilnath Jayavelu

To provide a foundation for conceptual modeling, ontologies have been introduced to specify the entities, the existences of which are acknowledged in the model. Ontologies are essential components as mechanisms to model a portion of reality…

Artificial Intelligence · Computer Science 2020-07-21 Sabah Al-Fedaghi

This paper presents an ontology of portions of matter with practical implications across scientific and industrial domains. The ontology is developed under the Unified Foundational Ontology (UFO), which uses the concept of quantity to…

Artificial Intelligence · Computer Science 2024-06-04 Lucas Valadares Vieira , Mara Abel , Fabricio Henrique Rodrigues , Tiago Prince Sales , Claudenir M. Fonseca

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution,…

Materials Science · Physics 2023-09-27 Sue Sin Chong , Yi Sheng Ng , Hui-Qiong Wang , Jin-Cheng Zheng

With recent advances in structural biology, including experimental techniques and deep learning-enabled high-precision structure predictions, molecular dynamics methods that scale up to large biomolecular systems are required. Current…

Biological Physics · Physics 2022-06-24 Tim Hempel , Simon Olsson , Frank Noé

Metal-organic frameworks (MOFs) are a class of crystalline materials with promising applications in many areas such as carbon capture and drug delivery. In this work, we introduce MOFFlow, the first deep generative model tailored for MOF…

Biomolecules · Quantitative Biology 2025-03-20 Nayoung Kim , Seongsu Kim , Minsu Kim , Jinkyoo Park , Sungsoo Ahn

Researchers across nearly every discipline seek to leverage ontologies for knowledge discovery and computational tasks; yet, the number of machine readable materials science ontologies is limited. The work presented in this paper explores…

Digital Libraries · Computer Science 2022-11-21 Jane Greenberg , Scott McClellan , Xintong Zhao , Elijah J Kellner , David Venator , Haoran Zhao , Jiacheng Shen , Xiaohua Hu , Yuan An

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired…

Metal-organic frameworks (MOFs) are a highly tunable class of crystalline materials where metal atoms or clusters are connected by organic linkers. They offer a versatile platform for exploring quantum phenomena such as entangled magnetism,…

Strongly Correlated Electrons · Physics 2025-12-25 Natalia Drichko , V. Sara Thoi , N. Peter Armitage

State space models (SSMs) with selection mechanisms and hardware-aware architectures, namely Mamba, have recently demonstrated significant promise in long-sequence modeling. Since the self-attention mechanism in transformers has quadratic…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Hanwei Zhang , Ying Zhu , Dan Wang , Lijun Zhang , Tianxiang Chen , Zi Ye

Materials informatics is increasingly used to support modelling, analysis and design across the length scales of materials science, from atomistic simulations to microstructural characterisation and continuum descriptions. Despite rapid…

The Metadata Object Description Schema (MODS) was developed to describe bibliographic concepts and metadata and is maintained by the Library of Congress. Its authoritative version is given as an XML schema based on an XML mindset which…

Computation and Language · Computer Science 2023-08-02 Rushrukh Rayan , Cogan Shimizu , Heidi Sieverding , Pascal Hitzler

Simulations with high accuracy are an essential part of scientific research to accelerate the innovation process. They are especially useful for finding novel approaches or optimizing existing methods. Today, powerful software tools are…

Medical Physics · Physics 2022-08-31 Patrick Vogel , Martin A. Rückert , Thomas Kampf , Volker C. Behr

Biochars have been attracting renewed attention as economical and environmentally friendly carbon sequestration materials with a diverse range of applications. However, experimental developments may be limited by the lack of molecular-level…

Materials Science · Physics 2024-06-11 Rosie Wood , Ondrej Masek , Valentina Erastova

Modern optical systems are subject to very restrictive performance, size and cost requirements. Especially in portable systems size often is the most important factor, which necessitates elaborate designs to achieve the desired…

Successful materials innovations can transform society. However, materials research often involves long timelines and low success probabilities, dissuading investors who have expectations of shorter times from bench to business. A…

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