Leveraging 3D printing to enhance mass spectrometry: A review
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
The use of 3D printing in the chemical and analytical sciences has gained a lot of momentum in recent years. Some of the earliest publications detailed 3D-printed interfaces for mass spectrometry, which is an evolving family of powerful detection techniques. Since then, the application of 3D printing for enhancing mass spectrometry has significantly diversified, with important reasons for its application including flexible integration of different parts or devices, fast customization of setups, additional functionality, portability, cost-effectiveness, and user-friendliness. Moreover, computer-aided design (CAD) and 3D printing enables the rapid and wide distribution of scientific and engineering knowledge. 3D printers allow fast prototyping with constantly increasing resolution in a broad range of materials using different fabrication principles. Moreover, 3D printing has proven its value in the development of novel technologies for multiple analytical applications such as online and offline sample preparation, ionization, ion transport, and developing interfaces for the mass spectrometer. Additionally, 3D-printed devices are often used for the protection of more fragile elements of a sample preparation system in a customized fashion, and allow the embedding of external components into an integrated system for mass spectrometric analysis. This review comprehensively addresses these developments, since their introduction in 2013. Moreover, the challenges and choices with respect to the selection of the most appropriate printing process in combination with an appropriate material for a mass spectrometric application are addressed; special attention is paid to chemical compatibility, ease of production, and cost. In this review, we critically discuss these developments and assess their impact on mass spectrometry.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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