A 312pJ°C<sup>2</sup> Ultra-Low-Power Direct-ADC Multi-Range Temperature Sensor for IoT Nodes
Bibliographic record
Abstract
An ADC-direct energy-efficient temperature sensor with a novel multi-range BJT-based transducer design is presented. Thanks to the novel transducer design, the proposed NPN-based sensor does not require any analog-domain pre-ADC signal conditioning. Through bias current control, the sensing range can be adjusted for different applications. Our simulation results show a 2.67 × improvement in ADC dynamic range utilization for the military (-55° C to 125° C) and 3.8 × improvement for the medical (0°C to 100° C) temperature ranges, respectively. An Incremental ΔΣ-based readout circuitry for the proposed sensor has also been implemented and the circuit- and system-level simulation results are presented. The entire design draws 2.6μA from a 1.2V supply voltage to yield a resolution of 0.01° for a conversion time of 100ms, achieving a resolution FoM of 3.12pJ°C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .
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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".