Modeling and design of architected structures and metamaterials assisted with artificial intelligence DOI Creative Commons
Angel Mora,

Gustavo Herrera-Ramos,

Diana L. Ramírez-Gutiérrez

et al.

Materials Research Express, Journal Year: 2024, Volume and Issue: 11(12), P. 122002 - 122002

Published: Dec. 1, 2024

Abstract Architected structures and metamaterials have attracted the attention of scientists engineers due to contrast in behavior compared base material they are made from. This interest within scientific engineering community has lead use computational tools accelerate design, optimization, discovery architected metamaterials. A tool that gained popularity recent years is artificial intelligence (AI). There several AI algorithms as many been used field for different objectives with degrees success. Then, this review we identify study metamaterials, purpose using AI, discuss their advantages disadvantages. Additionally, trends usage particular identified. Finally, perspectives regarding new directions areas opportunity presented.

Language: Английский

On-demand prediction of low-frequency average sound absorption coefficient of underwater coating using machine learning DOI Creative Commons
Nansha Gao, Mou Wang, Xiao Liang

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104163 - 104163

Published: Jan. 1, 2025

Language: Английский

Citations

1

Applied Artificial Intelligence in Materials Science and Material Design DOI Creative Commons
Emigdio Chávez‐Ángel, Martin Eriksen, Alejandro Castro‐Álvarez

et al.

Advanced Intelligent Systems, Journal Year: 2025, Volume and Issue: unknown

Published: March 2, 2025

Materials science has traditionally relied on a combination of experimental techniques and theoretical modeling to discover develop new materials with desired properties. However, these processes can be time‐consuming, resource‐intensive, often limited by the complexity material systems. The advent artificial intelligence (AI), particularly machine learning, revolutionized offering powerful tools accelerate discovery, design, characterization novel materials. AI not only enhances predictive properties but also streamlines data analysis in like X‐Ray diffraction, Raman spectroscopy, scanning probe microscopy, electron microscopy. By leveraging large datasets, algorithms identify patterns, reduce noise, predict behavior unprecedented accuracy. In this review, recent advancements applications across various domains science, including synchrotron studies, microscopies, metamaterials, atomistic modeling, molecular drug are highlighted. It is discussed how AI‐driven methods reshaping field, making discovery more efficient, paving way for breakthroughs design real‐time analysis.

Language: Английский

Citations

0

Architected acoustic metamaterials: An integrated design perspective DOI
Gianni Comandini, Morvan Ouisse, Valeska P. Ting

et al.

Applied Physics Reviews, Journal Year: 2025, Volume and Issue: 12(1)

Published: March 1, 2025

The review focuses on architected acoustic metamaterials to manipulate airborne sound waves, with only limited discussions elastic related solid media. We the design of and physical mechanisms underpinning their performance manufacturing methodologies, while also examining potential issues challenges affecting use in acoustics. complexities several metamaterial architectures are discussed. A new classification system is proposed distinguish configurations based typology channels inside meta-atom. Several types architectures, such as perforated micro-perforated panels, foams, resonators, various geometrical paths, piezoelectric patches, fundamental these classes identified commented on. paper describes main measurement techniques used for quantities evaluated, providing a guide characterize assess performance. current designs discussed, focus complex synergy between architectural patterns thickness. clarify distinction metamaterials, emphasizing applications materials that waves fluid offers further comments about need practical tools allow real-world applications.

Language: Английский

Citations

0

AInsectID Version 1.1: An Insect Species Identification Software Based on the Transfer Learning of Deep Convolutional Neural Networks DOI Creative Commons
Haleema Sadia, Parvez Alam

Published: March 25, 2025

AInsectID Version 1.1 is a Graphical User Interface (GUI)‐operable open‐source insect species identification, color processing, and image analysis software. The software has current database of 150 insects integrates artificial intelligence approaches to streamline the process with focus on addressing prediction challenges posed by mimics. This paper presents methods algorithmic development, coupled rigorous machine training used enable high levels validation accuracy. Our work transfer learning prominent convolutional neural network (CNN) architectures, including VGG16, GoogLeNet, InceptionV3, MobileNetV2, ResNet50, ResNet101. Here, we employ both fine tuning hyperparameter optimization improve performance. After extensive computational experimentation, ResNet101 evidenced as being most effective CNN model, achieving accuracy 99.65%. dataset utilized for sourced from National Museum Scotland, Natural History London, open source datasets Zenodo (CERN's Data Center), ensuring diverse comprehensive collection species.

Language: Английский

Citations

0

Hierarchical Design of Mechanical Metamaterials: an Application on Pentamode-like Structures DOI Creative Commons
S. Gómez, Emilio P. Calius, Akbar Afaghi Khatibi

et al.

International Journal of Mechanical Sciences, Journal Year: 2025, Volume and Issue: unknown, P. 110232 - 110232

Published: April 1, 2025

Language: Английский

Citations

0

Inverse design of non-parametric acoustic metamaterials via transfer-learned dual variational autoencoder with latent space-based data augmentation DOI

Keon Ko,

Min Woo Cho,

Kyungjun Song

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 151, P. 110735 - 110735

Published: April 8, 2025

Language: Английский

Citations

0

Quantum metamaterials: Applications in quantum information science DOI Creative Commons
Solomon Akpore Uriri, Yaseera Ismail, Mhlambululi Mafu

et al.

Deleted Journal, Journal Year: 2025, Volume and Issue: 2(2)

Published: April 9, 2025

Metamaterials are a class of artificially engineered materials with periodic structures possessing exceptional properties not found in conventional materials. This definition can be extended when we introduce degree freedom by adding quantum elements such as dots, cold atoms, Josephson junctions, and molecules, making metamaterials highly valuable for various applications. have been used to achieve invisibility cloaking, super-resolution, energy harvesting, sensing, among other Most these applications performed the classical regime. gradually made their way into regime since advent computing sensing imaging. Quantum relatively new technology, use information processing has proliferated. We restrict this study state manipulation control, entanglement, single photon generation, switching, engineering, key distribution, algorithms, orbital angular momentum, Considering developments, examine theory, fabrication, contributing how contribute field. find that ability harness unique drive is great importance, they potential unlock possibilities revolutionizing processing, bringing world closer practical technologies unprecedented capabilities. conclude suggesting possible future research directions.

Language: Английский

Citations

0

Recent Innovations in EMI Shielding Materials for Stealth Technology DOI

Lalitha Durairaj,

M. Murugesan

Synthetic Metals, Journal Year: 2025, Volume and Issue: unknown, P. 117874 - 117874

Published: April 1, 2025

Language: Английский

Citations

0

An automated design framework for composite mechanical metamaterials and its application to 2D pentamode materials DOI Creative Commons
S. Gómez, Emilio P. Calius, Akbar Afaghi Khatibi

et al.

International Journal of Mechanical Sciences, Journal Year: 2024, Volume and Issue: 276, P. 109393 - 109393

Published: May 16, 2024

Until relatively recently most mechanical metamaterial classes being studied have been composed of a single solid constituent phase and design has focused almost exclusively on structural geometry. Additional dimensions can be introduced by accepting heterogeneity varying materiality, i.e., allowing properties to vary across the metamaterial's unit cells or even from cell in domain, creating composite metamaterials. This higher dimensionality significantly expands effective property envelope, but additional complexity also presents significant hurdle. To overcome challenge, an automated framework is proposed that leverages modern evolutionary computation techniques, combined with finite element analysis for fitness evaluation, discretized voxelated domain. However, this approach introduces stochastic statistical aspects process, which requires processing successfully extract useful solutions. A case study presented used generate 2D structures exhibit pentamode-like behavior. Pentamode metamaterials, are best known extreme bulk-to-shear modulus ratios (B/G), offer unique control over elastic make particularly interesting test case. The objective was defined as maximizing B/G square It found process converges solution rapidly, generally less hundred generations. ratio values 10,000 more were obtained, largely exceeding those commonly literature experimental pentamode These generated designs feature reduced stress concentrations due elimination point-like connections between lattice struts, addresses key practical limitation diamond pentamodes. observed whatever initial variety moduli voxels evolution progressed collapsed much smaller number, often binary very stiff limited number softer at locations acted hinges.

Language: Английский

Citations

4

Recent Innovations in Microstrip Patch Antennas: Biomedical Uses and Wireless Integration DOI

K. Aafizaa,

K. Uma Haimavathi,

S. Saravanan

et al.

Deleted Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 21, 2025

Language: Английский

Citations

0