Detecting and Directing Single Molecule Binding Events on H-Si(100) with Application to Ultradense Data Storage
Bibliographic record
Abstract
Abstract Many diverse material systems are being explored to enable smaller, more capable and energy efficient devices. These bottom up approaches for atomic and molecular electronics, quantum computation, and data storage all rely on a well-developed understanding of materials at the atomic scale. Here, we report a versatile scanning tunneling microscope (STM) charge characterization technique, which reduces the influence of the typically perturbative STM tip field, to develop this understanding even further. Using this technique, we can now observe single molecule binding events to atomically defined reactive sites (fabricated on a hydrogen-terminated silicon surface) through electronic detection. We then developed a simplified error correction tool for automated hydrogen lithography, quickly directing molecular hydrogen binding events using these sites to precisely repassivate surface dangling bonds (without the use of a scanned probe). We additionally incorporated this molecular repassivation technique as the primary rewriting mechanism in ultradense atomic data storage designs (0.88 petabits per in2).
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".