ReviewPolymers2024
Advances in Additive Manufacturing of Polymer-Fused Deposition Modeling on Textiles: From 3D Printing to Innovative 4D Printing-A Review.
Review in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Article
- Smart Polymers and Adaptive Systems in Pilot Suit Engineering: Toward Autonomous, Responsive, and Wearable Flight Technologies.Nanomaterials (Basel, Switzerland) · 2025Review
- Strategic Framework for Additive Manufacturing with Smart Polymer Composites: A Pathway to Net-Zero Manufacturing.Polymers · 2025Article
- Reviewing Additive Manufacturing Techniques: Material Trends and Weight Optimization Possibilities Through Innovative Printing Patterns.Materials (Basel, Switzerland) · 2025Review
- Advancing Textile Waste Recycling: Challenges and Opportunities Across Polymer and Non-Polymer Fiber Types.Polymers · 2025Review
- Review
- Analyzing Sustainable 3D Printing Processes: Mechanical, Thermal, and Crystallographic Insights.Polymers · 2024Article
- Effective and new technologies in kidney tissue engineering.Frontiers in bioengineering and biotechnology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Technological advances and the development of new and advanced materials allow the transition from three-dimensional (3D) printing to the innovation of four-dimensional (4D) printing. 3D printing is the process of precisely creating objects with complex shapes by depositing superimposed layers of material. Current 3D printing technology allows two or more filaments of different polymeric materials to be placed, which, together with the development of intelligent materials that change shape over time or under the action of an external stimulus, allow us to innovate and move toward an emerging area of research, innovative 4D printing technology. 4D printing makes it possible to manufacture actuators and sensors for various technological applications. Its most significant development is currently in the manufacture of intelligent textiles. The potential of 4D printing lies in modular manufacturing, where fabric-printed material interaction enables the creation of bio-inspired and biomimetic devices. The central part of this review summarizes the effect of the primary external stimuli on 4D textile materials, followed by the leading applications. Shape memory polymers attract current and potential opportunities in the textile industry to develop smart clothing for protection against extreme environments, auxiliary prostheses, smart splints or orthoses to assist the muscles in their medical recovery, and comfort devices. In the future, intelligent textiles will perform much more demanding roles, thus envisioning the application fields of 4D printing in the next decade.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.