Top-bending deformation in silver nanowires: Insights from molecular dynamics and autonomous basin climbing simulations
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
Atomistic insight into nanowire deformation under mechanical loading is necessary to bridge the gap between theoretical modeling and real-world nanoscale applications. In this study, we investigate the bending-induced plasticity of single-crystalline silver nanowires using molecular dynamics (MD) and autonomous basin climbing (ABC) simulations. Top-bending tests were performed along both [111] and [001] crystallographic orientations to explore the role of applied force, boundary conditions, and timescale sensitivity on defect formation. At low applied forces, MD simulations predicted purely elastic behavior, while ABC revealed early plastic activity, including the nucleation of stacking faults near the fixed end and the formation of twin boundaries. These plastic events emerged well below the MD yield threshold, enabled by ABC’s ability to access long-timescale, diffusion-mediated mechanisms such as surface atom rearrangement and barrier-lowering via atomic shuffling. Under elevated forces, both MD and ABC captured the formation of stable five-fold twin structures, though only ABC simulations revealed their nucleation sequence and internal development in detail. These findings underscore ABC’s essential role in resolving thermally activated deformation pathways that are inaccessible to conventional MD. By bridging the timescale gap, ABC provides critical insight into early-stage plasticity and defect evolution in nanoscale metals, offering a more comprehensive understanding of deformation under bending.
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 | 0.000 | 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 | 0.001 |
| 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 it