Machine learning enabled 3D printing parameter settings for desired mechanical properties DOI Creative Commons
Linlin Wang, Jingchao Jiang, Yuan Dong

и другие.

Virtual and Physical Prototyping, Год журнала: 2024, Номер 19(1)

Опубликована: Ноя. 14, 2024

Additive manufacturing facilitates the production of parts with tailored mechanical properties, yet achieving specific stress–strain responses remains a significant challenge due to intricate relationship between printing parameters and material behaviour. This study introduces novel approach utilising long short-term memory (LSTM) models predict parameter configurations for extrusion additive (MEX) parts, aiming meet requirements. The proposed framework transforms raw tensile test data LSTM compatibility, yielding coefficient determination 0.8648 mean square error 0.1348 in inverse prediction tasks. Additionally, validation new resulted an percentage below 2%. Our enables efficient design customised accurate reducing need extensive experimentation allowing adaptation various processes.

Язык: Английский

Temperature-responsive 4D printing with shape memory polymers: Advancing simulation with a viscoelastic constitutive model DOI
Jiarui Wang, Tong Mu,

Yuliang Xia

и другие.

Applied Materials Today, Год журнала: 2025, Номер 42, С. 102604 - 102604

Опубликована: Янв. 20, 2025

Язык: Английский

Процитировано

1

Nonlinear free vibration of sandwich beam with data-driven inverse-designed auxetic core based on deep learning DOI
Xi Fang, Hui‐Shen Shen, Hai Wang

и другие.

European Journal of Mechanics - A/Solids, Год журнала: 2025, Номер unknown, С. 105626 - 105626

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

Neuro-Symbolic Artificial Intelligence in Accelerated Design for 4D Printing: Status, Challenges, and Perspectives DOI Creative Commons

Oualid Bougzime,

Christophe Cruz,

Jean–Claude André

и другие.

Materials & Design, Год журнала: 2025, Номер unknown, С. 113737 - 113737

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Role of artificial intelligence in data-centric additive manufacturing processes for biomedical applications DOI

Saman Mohammadnabi,

Nima Moslemy,

Hadi Taghvaei

и другие.

Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials, Год журнала: 2025, Номер 166, С. 106949 - 106949

Опубликована: Фев. 25, 2025

Язык: Английский

Процитировано

0

Revolutionizing the Future of Smart Materials: A Review of 4D Printing, Design, Optimization, and Machine Learning Integration DOI Open Access
Kashif Azher, Aamer Nazir,

Muhammad Umar Farooq

и другие.

Advanced Materials Technologies, Год журнала: 2025, Номер unknown

Опубликована: Фев. 25, 2025

Abstract With technological advancement and development, there is a tremendous increase in demand for different smart materials because of their stimulation from external sources. Moreover, the time‐dependent response provides insight into fabrication these using 4D printing (4DP) techniques. Hence, this study presents comprehensive review 4DP materials. The covers aspects material, design optimization to printing. Herein, have been discussed detail based on physical, biological, chemical stimuli‐responsive subtype's behavior. For designing materials, usage tools such as new software, finite element analysis, machine learning are also discussed. challenging responsive natures complexity mechanisms. detailed present 3D techniques, use 4DP, how future applications can be incorporated with material presented. help learning, directions fabricating 4DP. challenges utilization comprehensively covered.

Язык: Английский

Процитировано

0

Stimulus-responsive gradient hydrogel micro-actuators fabricated by two-photon polymerization-based 4D printing DOI Creative Commons

Tongqing Li,

Gary Chi-Pong Tsui,

Chi Ho Wong

и другие.

Nanotechnology Reviews, Год журнала: 2025, Номер 14(1)

Опубликована: Янв. 1, 2025

Abstract The growing field of 4D printing has spurred extensive exploration into applications stimulus-responsive materials, such as hydrogels for micro-actuators. However, the hydrogel-based micro-actuators fabricated by one-step, single-material are typically bilayer, and their actuation capabilities limited. This study proposes a novel gradient strategy via two-photon polymerization (2PP) based to enhance performance hydrogel feasibility this approach was demonstrated investigating shrinkage rates elastic moduli poly( N -isopropylacrylamide) (PNIPAm) micro-cuboids printed at different laser doses using confocal scanning microscope atomic force microscopy nano-indentation respectively. 2PP-based used fabricate bilayer trilayer PNIPAm micro-actuators, with dose programmed modulate crosslinking degree each layer. These were actuated near-infrared (NIR) light in gold nanorods (AuNRs) solutions. effects NIR powers, micro-actuator sizes, layer thicknesses on behaviors systematically investigated. Compared 12-µm-thickness micro-actuation, introduction transitional one significantly enhanced amplitude speed (the bending angle curvature increased about 150 70%, respectively, cycle time recovery shortened 35%). advancements have significant implications microscale materials enhancing applications.

Язык: Английский

Процитировано

0

Machine learning powered inverse design for strain fields of hierarchical architectures DOI Creative Commons
Liuchao Jin,

Shouyi Yu,

Jianxiang Cheng

и другие.

Composites Part B Engineering, Год журнала: 2025, Номер unknown, С. 112372 - 112372

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

A novel controlled high-dynamic braking effect-driven droplet transition in GMAW DOI
Jun‐Jun Xiao, You Wan, Shujun Chen

и другие.

Journal of Manufacturing Processes, Год журнала: 2025, Номер 142, С. 71 - 83

Опубликована: Март 30, 2025

Язык: Английский

Процитировано

0

Optimizing multi-physics variables in wire arc additive manufacturing for weld bead aspect ratio: a machine learning approach DOI
P. van ’t Veer, Deepak Mudakavi,

Somashekara M Adinarayanappa

и другие.

Progress in Additive Manufacturing, Год журнала: 2025, Номер unknown

Опубликована: Апрель 19, 2025

Язык: Английский

Процитировано

0

Physically Constrained 3D Diffusion for Inverse Design of Fiber-reinforced Polymer Composite Materials DOI Creative Commons
Pei Xu, Yunpeng Wu, Alireza Zarei

и другие.

Composites Part B Engineering, Год журнала: 2025, Номер unknown, С. 112515 - 112515

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0