Optochemical Self-Organisation of Functional Microstructures
Bibliographic record
Abstract
Our group previously reported an optochemical organization route to 3-D optical and microstructural lattices that combines the spontaneity of self-organisation to the precision and directionality of lithography. This method exploits the inherent instability of a broad, uniform beam of white light propagating in a photopolymer and its consequent division into identical filaments of light. By imposing spatially controlled noise on the light beam, the self-organizing filaments can be coaxed into 2-D and 3-D lattices. Unlike any other known self-organised or lithographically constructed structure, these lattices comprise functional, multimode and multi-wavelength cylindrical waveguides. The objective of the work presented here is to apply multidirectional waveguide lattices (MWGLs) as wide-angled, light-capturing coatings that increase the intensity of light that is incident on optical devices including photovoltaic (PV) cells. Our approach is strongly motivated by the fact that even small increments of energy conversion efficiency (<1%) of PV modules are critical in the field. Furthermore, wide-angled, light-capture could eliminate (expensive) mechanised rotation of solar panels to track the Sun’s diurnal trajectory. We employ optochemical organization to prepare elastomer films comprising up to 5 intersecting arrays of waveguide lattices, which are oriented over a large range of angles with respect to the surface normal. When integrated into solar cell devices for example, the MWGLs could capture light seamlessly over a large range of angles and deliver intensity to the photovoltaic module and in this way, could increase conversion efficiencies.
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 | 0.000 | 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 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".