Sustainability and innovation in 3D printing: Outlook and trends
Bibliographic record
Abstract
<abstract> <p>The convergence of additive manufacturing (AM), sustainability, and innovation holds significant importance within the framework of Industry 4.0. This article examines the environmentally friendly and sustainable aspects of AM, more commonly referred to as 3D printing, a cutting-edge technology. It describes the fundamentals of AM in addition to its diverse materials, processes, and applications. This paper demonstrates how several 3D printing techniques can revolutionize sustainable production by examining their environmental impacts. The properties, applications, and challenges of sustainable materials, such as biodegradable polymers and recyclable plastics, are thoroughly examined. Additionally, the research explores the implications of 3D printing in domains including renewable energy component fabrication, water and wastewater treatment, and environmental monitoring. In addition, potential pitfalls and challenges associated with sustainable 3D printing are examined, underscoring the criticality of continuous research and advancement in this domain. To effectively align sustainability goals with functional performance requirements, it is imperative to address complexities within fused deposition modeling (FDM) printing processes, including suboptimal bonding and uneven fiber distribution, which can compromise the structural integrity and durability of biodegradable materials. Ongoing research and innovation are essential to overcome these challenges and enhance the viability of biodegradable FDM 3D printing materials for broader applications.</p> </abstract>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".