A functionally complete logic gate in a soft photoresponsive hydrogel
Bibliographic record
Abstract
Materials that compute-or process stimuli to generate a result output-are important in applications ranging from soft robotics to therapeutics. Here, we report a NAND gate based on the interactions of three self-trapped beams in a photoresponsive hydrogel. The beams self-trap by triggering localised contraction and corresponding refractive index changes (Δn) and communicate with each other through the interconnected hydrogel network. Light-induced Δn in one region suppresses contraction (and Δn) elsewhere. This inhibits self-trapping and reduces the power of the central beam-which competes with two equidistant neighbours-compared to either peripheral beam, which competes with just one neighbour. The NAND gate exploits this geometry-dependent inhibition: the central beam's peak power-the output-exceeds a threshold value unless both neighbours-inputs-are on, i.e., an output = 0 is retrieved only with input [1, 1]. We then demonstrate two and, separately, twelve sequentially chained NAND operations, and propose a route to multiple, simultaneously linked operations in a single, internally mediated step. Here, the output from one operation is spontaneously directed to subsequent operations. Our findings open pathways to soft materials with autonomous computational functionality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".