Rapport final du projet européen ERA-NET CORNET DAF3D
Bibliographic record
Abstract
Water is vital for life and the essential key to important industrial processes. Due to the increasing consumption and contamination, the access, treatment and safety of water is becoming challenging and costly. Therefore, new technologies have to be developed to ensure sustainable protection and safe access to water for both human consumption and industrial use. The DAF3D project aims to develop an innovative and sustainable 3-D-printed filter based on antibacterial functionalised textiles for water disinfection. The expected application is centred on production and reusability of process water from diverse industrial sectors and grey water within households. For instance, in the chemical and food industries, water recycling is enforced and cost-saving but biological safety is a major concern. Thus, the 3-D-printed filter composed of antibacterial functionalised textiles is a promising solution for these issues and can be implemented in a wide diversity of applications, configurations and dimensions. The innovative filter for disinfection will be composed of a thermoplastic for 3-D-printing in combination with textile materials pre-impregnated with antibacterial agents, such as zinc oxide (ZnO) structures doped with Cu and/or Al. These new antibacterial textiles are capable of generating in situ highly reactive oxidizing species, which can degrade a wide range of organic substances, including microorganisms. It has been shown that ZnO can be used for water hygienisation due to its antimicrobial capacity. Species generated by ZnO break through the cell wall, causing irreversible damage and leading to the cell death. Additive manufacturing technologies or 3-D-printing technologies are able to print filter materials with precisely defined structures. The innovative principle behind this manufacturing process enables the development of efficient flow paths through the filter and the possible inclusion of additives for expanding functionality and reactivity. However, several aspects must be considered when applying such materials to water disinfection, as the risk of degradation and leaching would cause severe problems. Therefore, this project aims to develop innovative materials to be used for water hygienisation without causing contamination. A material with these properties is not yet available on the market. Therefore, antibacterial textile micropowders based on ZnO will be incorporated into the thermoplastic compound at different concentrations, using a plastic extruder. Subsequently, a filament for 3-D-printing will be produced for supporting further manufacturing of the filter for process water disinfection. The developed antibacterial filter will be tested for the degradation of microorganisms, such as E. coli and others pathogens individually and/or in combination, in a variety of domestic and industrial process waters. Pre-treatments will be applied before the filter, depending on the process water to be treated. The tests will be performed in a bench scale demonstrator. The treated water will be accessed accordingly to evaluate disinfection efficiency and the reusability in the targeted industrial sector. In summary, the ultimate aim of the DAF3D project is to develop and validate a disinfection filter for reuse of process water. This is achieved by combining functionalised textiles impregnated with antimicrobial agents and a safe thermoplastic for 3-D-printed filters. The versatility of 3-D-printed antimicrobial filter will support SMEs on market creation. Moreover, the filter is a promising and competitive technology for replacing less-efficient and sustainable existing technology. Moreover, the flexibility will enable and/or increase the application of water recycling and reuse in industrial and private applications. The DAF3D project can have a significant impact on enabling sustainable treatment and safe access to water, which is a well-known resource but susceptible to contamination and source of critical health and environmental problems.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".