Materials Research Bulletin, Journal Year: 2023, Volume and Issue: 166, P. 112368 - 112368
Published: May 27, 2023
Language: Английский
Materials Research Bulletin, Journal Year: 2023, Volume and Issue: 166, P. 112368 - 112368
Published: May 27, 2023
Language: Английский
International Journal of Mechanical Sciences, Journal Year: 2023, Volume and Issue: 252, P. 108378 - 108378
Published: April 11, 2023
Language: Английский
Citations
39Composites Science and Technology, Journal Year: 2022, Volume and Issue: 227, P. 109594 - 109594
Published: June 16, 2022
Language: Английский
Citations
38Computer Methods in Applied Mechanics and Engineering, Journal Year: 2023, Volume and Issue: 410, P. 116032 - 116032
Published: April 6, 2023
Language: Английский
Citations
32Construction and Building Materials, Journal Year: 2024, Volume and Issue: 438, P. 137191 - 137191
Published: July 4, 2024
Language: Английский
Citations
14Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)
Published: Aug. 27, 2024
The fracture behaviour of artificial metamaterials often leads to catastrophic failures with limited resistance crack propagation. In contrast, natural materials such as bones and ceramics possess microstructures that give rise spatially controllable path toughened material advances. This study presents an approach is inspired by nature's strengthening mechanisms develop a systematic design method enabling damage-programmable engineerable microfibers in the cells can program micro-scale behaviour. Machine learning applied provide effective engine accelerate generation offer advanced toughening functionality bowing, deflection, shielding seen materials; are optimised for given programming path. paper shows features effectively enable crack-resisting on basis tip interactions, shielding, bridging synergistic combinations these mechanisms, increasing up 1,235% absorbed energy comparison conventional metamaterials. proposed have broad implications damage-tolerant materials, lightweight engineering systems where significant resistances or highly programmable damages high performances sought after.
Language: Английский
Citations
13Materials & Design, Journal Year: 2024, Volume and Issue: unknown, P. 113305 - 113305
Published: Sept. 1, 2024
Language: Английский
Citations
10Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: June 14, 2024
Abstract Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice with tailored or optimal mechanical properties remains a significant challenge. With each added variable, the space quickly becomes intractable. To address this challenge, research efforts have sought combine computational approaches machine learning (ML)-based reduce cost process and accelerate design. While these made substantial progress, challenges in (1) building interpreting ML-based surrogate models (2) iteratively efficiently curating training datasets for optimization tasks. Here, we first challenge by combining modeling Shapley additive explanation (SHAP) analysis interpret impact variable. We find that our achieve excellent prediction capabilities ( R 2 > 0.95) SHAP values aid uncovering variables influencing performance. second utilizing active learning-based methods, such as Bayesian optimization, explore report 5 × reduction simulations relative grid-based search. Collectively, results underscore value intelligent systems leverage methods key accelerating
Language: Английский
Citations
9Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 20, 2025
Abstract Diatoms have been described as “nanometer‐born lithographers” because of their ability to create sophisticated 3D amorphous silica exoskeletons. The hierarchical architecture these structures provides diatoms with mechanical protection and the filter, float, manipulate light. Therefore, they emerge an extraordinary model multifunctional materials from which draw inspiration. In this paper, numerical simulations, analytical models, experimental tests are used unveil structural fluid dynamic efficiency Coscinodiscus species diatom. Then a novel printable biomimetic material is proposed for applications such porous filters, heat exchangers, drug delivery systems, lightweight structures, robotics. results demonstrate Nature's role designer efficient tunable systems highlight potential engineering innovation. Additionally, paper lays foundation extend structure‐property characterization diatoms.
Language: Английский
Citations
1Thin-Walled Structures, Journal Year: 2021, Volume and Issue: 169, P. 108319 - 108319
Published: Sept. 11, 2021
Language: Английский
Citations
54Composites Science and Technology, Journal Year: 2021, Volume and Issue: 216, P. 109064 - 109064
Published: Sept. 22, 2021
Language: Английский
Citations
44