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Record W4408945356 · doi:10.1038/s41467-025-58379-0

Scaling-up molecular logic to meso-systems via self-assembly

2025· article· en· W4408945356 on OpenAlexfundno aff
Ze-Qing Chen, Brian Daly, Chaoyi Yao, Hannah S. N. Crory, Yikai Xu, Ziwei Ye, H. Q. Nimal Gunaratne, Ayumi Kimura, Seiichi Uchiyama, Steven E. J. Bell, Eric V. Anslyn, A. Prasanna de Silva

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldChemistry
TopicMolecular Sensors and Ion Detection
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilChina Scholarship CouncilQueen's UniversityQueen's University BelfastLeverhulme Trust
KeywordsComputationScalingLogic gateComputer scienceNanotechnologySet (abstract data type)Biological systemTheoretical computer scienceMaterials scienceAlgorithmMathematicsBiology

Abstract

fetched live from OpenAlex

Due to the small size and biocompatibility of molecules, molecular logic-based computation is a gateway to the informational basis of life processes. Logic-based computation operates widely with discrete molecules of up to nanometric sizes. The contribution of molecule-based bulk materials of milli/centimetric size to the field has begun in more recent years. However, artificial molecule-based meso-scale systems which intrinsically perform logic operations are very rare. Here, we show that self-assembled systems consisting of cyclophane octacarboxylates and a cationic surfactant can perform such functions, where a membrane itself behaves as a Reset-Set Flip-Flop which is integrated with 7 more logic elements. Now that molecular logic-based computation operates across a wide range of contiguous size-scales, the way opens for its general use in information processing aspects of biology and synthetic biology.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.771
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.288
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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