Multifunctional inks in aerosol jet printing: performance, challenges, and applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article comprehensively analyses AJP technology, with a greater focus on the areas that received scant attention in the previously published literature. Whereas various reviews so far discussed the basic principles of AJP and its comparison with other printing techniques, the present article goes further to discuss different types of functional inks being utilized in AJP, including conductive, dielectric, semiconducting, and biological inks. The minimum resolutions of micropatterns achieved with these inks are then reviewed, together with the specific printing recipes enabling their use, to give an overview of the performances of different materials within the AJP process. Furthermore, the article classifies the dimensionality of AJP-printed patterns into 2D-planar, 2D-nonplanar, and 3D parts, underlining the capability of the technology for the fabrication of both planar and non-planar geometries. This makes AJP a tool of major relevance in the newly emerging fields of electronics, sensors, and biotechnology, which strongly demand precise micro-patterning and substrate adaptability. The review, therefore, explains how AJP is bound to change manufacturing processes by exploring its new applications in those sectors. The article also covers the current limitations of AJP, including how to optimize printing processes and generalize them into more industrial uses. Synthesizing state-of-the-art research, this review not only describes the main achievements of AJP technology but also points out likely future tendencies and even disruptions that may occur within this field. This review aims to be an extensive source of information for both researchers and industry representatives interested in finding opportunities for further applications of AJP in various areas.
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.
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 | 0.000 |
| 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 it