Application of phase change materials in 4D printing: A review

Mehta, Parth Dinesh; Sahlot, Pankaj

doi:10.1016/j.matpr.2021.05.664

Cited by 10 publications

(4 citation statements)

References 28 publications

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“…Smart materials are designed to respond to external stimuli such as mechanical stress, temperature, light, electric, and magnetic fields, pressure, chemical compounds, and moisture ( Figure a). 4D printable smart materials include liquid crystal elastomers, [ 230 ] shape memory polymers, [ 231 ] phase‐change materials, [ 232 ] polymeric hydrogels, [ 233 ] pH‐sensitive polymers, [ 234 ] temperature‐responsive polymers, [ 235 ] self‐healing materials, [ 236 ] thermoelectric materials, [ 237 ] dielectric elastomers, [ 238 ] piezoelectric composites. [ 239 ] By harnessing these smart materials, mechanical metamaterials have been developed that demonstrate static non‐reciprocity, [ 221 ] thermally programmable mechanical response, [ 68 ] spatially illumination‐controlled mechanical behavior, [ 222 ] electrochemically reconfigurable architecture, [ 223 ] magnetomechanical behavior responsive to magnetic fields, [ 224 ] negative‐pressure buckling‐induced actuation, [ 225 ] and liquid‐induced topological transformations [ 226 ] (Figures 18b–h).…”

Section: Discussionmentioning

confidence: 99%

Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design

et al. 2023

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Mechanical metamaterials are meticulously designed structures with exceptional mechanical properties determined by their microstructures and constituent materials. Tailoring their material and geometric distribution unlocks the potential to achieve unprecedented bulk properties and functions. However, current mechanical metamaterial design considerably relies on experienced designers' inspiration through trial and error, while investigating their mechanical properties and responses entails time‐consuming mechanical testing or computationally expensive simulations. Nevertheless, recent advancements in deep learning have revolutionized the design process of mechanical metamaterials, enabling property prediction and geometry generation without prior knowledge. Furthermore, deep generative models can transform conventional forward design into inverse design. Many recent studies on the implementation of deep learning in mechanical metamaterials are highly specialized, and their pros and cons may not be immediately evident. This critical review provides a comprehensive overview of the capabilities of deep learning in property prediction, geometry generation, and inverse design of mechanical metamaterials. Additionally, this review highlights the potential of leveraging deep learning to create universally applicable datasets, intelligently designed metamaterials, and material intelligence. This article is expected to be valuable not only to researchers working on mechanical metamaterials but also those in the field of materials informatics.This article is protected by copyright. All rights reserved

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Section: Discussionmentioning

confidence: 99%

Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design

et al. 2023

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“…Nevertheless, through using more advanced methods of 4DP with heterogeneous principles, the understanding of multi-material and multi-voxel systems through one or more 3D printers becomes feasible, and in the future, it will lead to high performance in industrial applications. As opposed to the use of SMMs to change the shapes of 3D-printed parts, 4DP has also been employed for fabricating multi-materials with different swelling or deformation properties [35,37]. Unfortunately, the need for specific 3D printers limits the use of 4DP [38].…”

Section: Advantages and Challengesmentioning

confidence: 99%

New Trends in 4D Printing: A Critical Review

et al. 2023

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In a variety of industries, Additive Manufacturing has revolutionized the whole design–fabrication cycle. Traditional 3D printing is typically employed to produce static components, which are not able to fulfill dynamic structural requirements and are inappropriate for applications such as soft grippers, self-assembly systems, and smart actuators. To address this limitation, an innovative technology has emerged, known as “4D printing”. It processes smart materials by using 3D printing for fabricating smart structures that can be reconfigured by applying different inputs, such as heat, humidity, magnetism, electricity, light, etc. At present, 4D printing is still a growing technology, and it presents numerous challenges regarding materials, design, simulation, fabrication processes, applied strategies, and reversibility. In this work a critical review of 4D printing technologies, materials, and applications is provided.

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“…Professor Skylar Tibbits demonstrated how alterations occur in a stationary object produced by 3D printing throughout time during the TED talk, "The emergence of 4D printing", at MIT in 2013 [26]. It has been shown that a simple 3D object or part can be converted into a more complicated form over time.…”

Section: D Printingmentioning

confidence: 99%

A REVIEW ON 4D ADDITIVE MANUFACTURING - THE APPLICATIONS, SMART MATERIALS & EFFECT OF VARIOUS STIMULI ON 4D PRINTED OBJECTS

Maidin,

Jin Wee,

Sharum

et al. 2023

Jurnal Teknologi

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Additive Manufacturing, often known as 3D printing, is a process that uses a variety of materials to manufacture highly accurate items layer by layer. However, this technology has its limitations. One such limitation is the inability to print components larger than the printer's size due to the limited size of the build chamber. 4D additive manufacturing or 4D printing is an innovative development based on 3D printing that allows objects to be reshaped after printing, using stimuli-responsive materials that require external stimuli. This article present a review on 4D printing. Four databases, Google Scholar, ScienceDirect, IEEE Xplore, and Scopus database, were systematically searched for relevant review articles to identify and classify research studies. Specific keywords (4D printing, additive manufacturing, smart materials, stimuli, and application) were identified and used to guide the discovery of relevant studies. A total of 28 full articles were reviewed to study the applications of 4D printing, smart materials for 4D printing, as well as the effect of various stimuli on 4D printed objects. In conclusion, this review gives a summary of 4D printing and highlights its potential for revolutionizing manufacturing and further research is required to solve the limitations posed by this technology.

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Application of phase change materials in 4D printing: A review

Cited by 10 publications

References 28 publications

Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design

Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design

New Trends in 4D Printing: A Critical Review

A REVIEW ON 4D ADDITIVE MANUFACTURING - THE APPLICATIONS, SMART MATERIALS & EFFECT OF VARIOUS STIMULI ON 4D PRINTED OBJECTS

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