Synergistic Distributed Thermal Regulation for On-CMOS High-Throughput Multimodal Amperometric DNA-Array Analysis
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
Accurate temperature regulation is critical for amperometric DNA analysis to achieve high fidelity, reliability, and throughput. In this work, a 9×6 cell array of mixed-signal CMOS distributed temperature regulators for on-CMOS multi-modal amperometric DNA analysis is presented. Three DNA analysis methods are supported, including constant potential amperometry (CPA), cyclic voltammetry (CV), and impedance spectroscopy (IS). In-cell heating and temperature sensing elements are implemented in standard CMOS technology without post-processing. Using proportional-integral-derivative (PID) control, the local temperature can be regulated to within ± 0.5∘C of any desired value between 20∘C and 90∘C. To allow the in-cell integration of independent PID control, a new mixed-signal design is proposed, where the two computationally intensive operations in the PID algorithm, multiplication, and subtraction, are performed by an in-cell dual-slope multiplying ADC, resulting in a small area and low power consumption. Over 95% of the circuit blocks are synergistically shared among the four operating modes, including CPA, CV, IS, and the proposed temperature regulation mode. A 3mm×3mm CMOS prototype fabricated in a 0.13μm CMOS technology has been fully experimentally characterized. The proposed distributed temperature regulation design and the mixed-signal PID implementation can be applied to a wide range of sensory and other applications.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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