An affordable platform for automated synthesis and electrochemical characterization
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
Electrochemical techniques are pivotal for material discovery and renewable energy; however, often the extensive chemical spaces to be explored require high-throughput experimentation (HTE) to ensure timely results, which are costly both for instrument and materials/consumables. While self-driving laboratories (SDL) promise efficient chemical exploration, most contemporary implementations demand significant time, economic investment, and expertise. This study introduces an open and cost-effective autonomous electrochemical setup, comprising a synthesis platform and a custom-designed potentiostat device. We present an SDL platform that offers rapid deployment and extensive control over electrochemical experiments compared to commercial alternatives. Using ChemOS 2.0 for orchestration, we showcase our setup's capabilities through a campaign in which different metal ions reacts with ligands to form coordination compounds., yielding a database of 400 electrochemical measurements. Committed to open science, we provide a potentiostat design, campaign software, and raw data, aiming to democratize customized components in SDLs and ensure transparent data sharing and reproducibility.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it