Dynamic Multiscale Modeling of Crystal Structures with Applications to Polymorphic and Ultra-high Temperature Ceramics
Bibliographic record
Abstract
Certain materials exhibit complex behavior explained by nanoscale kinetics of reconstructive polymorphic nature. The scales of such materials are inherently multiscale from atomistic to continuum domains. Concurrent multiscale approaches provide a feasible solution to the taxing power demand of conventional atomistic-based models. The recent work of the Bridging Cell Method (BCM) has shown great acumen in addressing current limitations that plague such classes of multiscale models. However, BCM relies on the Atomic-scale Finite Element (AFE) framework, which is a static-based formulation. Also, a lack of statistical thermodynamic consistency makes comparison to molecular dynamics (MD) results challenging. The BCM relies on temperature-based potential to enforce thermal effect in the simulation instead of thermostats. In parallel, atomic description of its embedded structure has always relied on simplified parameterization that cannot extract atomic features (e.g. dislocations, crack tips, crystal phases, etc.) for complex, non-monoatomic materials with varying space groups under the same crystal group. The objective of this work comes into two main folds: to develop of set of parameter capable of extracting atomic features of interest for complex crystalline systems and formulate a generalized dynamic model of the BCM for mechanical characterization of arbitrary atomic-continuum structures. To achieve those objectives, a set of parameters based on the Common Neighborhood Parameter (CNP) has been introduced with a focus to complex, non-monoatomic crystalline structures. Also, a dynamic formulation to the finite-element based BCM has been developed for those structures under a microcanonical ensemble consistency with a new set of representative elements, dubbed the Dynamic Atomic-scale Finite Element (DAFE) framework. Case studies are then presented first for the characterization parameters to show their efficiency for fine atomic feature extraction. Also, the new dynamic model is portrayed in simulations with a tensile and a fracture around a void. Next, the set of formulations is applied to phase transformation of Anatase to Rutile along the critical transformation planes to characterize the mechanics of transformation and mechanical property of the polymorphic ceramic. This has allowed an investigation of the temperature effect on Anatase’s stability from nanoscale while obtaining the product’s elastic modulus upon the plane of transformation.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".