Molecular dynamics simulations of nanoindentation – the importance of force field choice on the predicted elastic modulus of FCC aluminum
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
Molecular Dynamics (MD) was used to determine the accuracy of different force fields on predicting the elastic modulus of single crystal aluminum through nanoindentation tests. In this work, nanoindentation was performed using three different types of force fields (EAM, MEAM and ReaxFF) and the resulting elastic modulus was compared to the value obtained using elastic constants from standard small strain tensile simulations. When the predicted modulus of each force field was compared to the modulus via elastic constants, the ReaxFF resultant moduli were similar to that of nanoindentation, but for EAM and MEAM the two methods produced significantly different values. Therefore, even if a force field is parameterised for elastic modulus, it does not guarantee the force field will accurately predict the modulus from other procedures. As well, two different methods for calculating modulus from indentation curves were compared: The Hertz approximation and the Oliver and Pharr (O&P) method. For EAM and MEAM force fields, the Hertz method significantly under predicted modulus while the O&P method was in better agreement with the experimental modulus.
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 | 0.000 |
| 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 it