Salvato in:
| Autori principali: | , , , , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2026
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2602.02957 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866914584105844736 |
|---|---|
| author | Liang, Yi Kim, Soohyeon Chiang, Tony Lenox, Megan K. Mercer, Ian Plombon, John J. Maria, Jon-Paul Ihlefeld, Jon F. Sun, Wenhao Lu, Wei Heron, John T. |
| author_facet | Liang, Yi Kim, Soohyeon Chiang, Tony Lenox, Megan K. Mercer, Ian Plombon, John J. Maria, Jon-Paul Ihlefeld, Jon F. Sun, Wenhao Lu, Wei Heron, John T. |
| contents | Real ferroelectric devices operate under mixed and distorted time-varying voltages, yet the standard nucleation-growth frameworks used to interpret ferroelectric switching - most notably the Kolmogorov-Avrami-Ishibashi (KAI) and nucleation-limited switching models (NLS) - are derived under the critically limiting assumption of a constant electric field. Thus, the prevailing interpretation of ferroelectric switching dynamics fails under real operating conditions. Here we introduce a compact dynamic-field-driven nucleation and growth (DFNG) model that enables quantitative fits to switching transients across multiple ferroelectric materials to extract time-varying domain wall velocity and growth dimensionality, even under arbitrary voltage waveform. This capability then motivates its use in device modeling under complex signals spanning disparate time and frequency scales. Coupling the compact model to application-related waveforms and circuit-level simulation platform facilitates a predictive materials-circuit co-design framework by linking nucleation and growth parameters to memory window, disturb error, speed, and energy dissipation for next-generation ferroelectric technologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_02957 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Ferroelectric dynamic-field-driven nucleation and growth model for predictive materials-to-circuit co-design Liang, Yi Kim, Soohyeon Chiang, Tony Lenox, Megan K. Mercer, Ian Plombon, John J. Maria, Jon-Paul Ihlefeld, Jon F. Sun, Wenhao Lu, Wei Heron, John T. Materials Science Real ferroelectric devices operate under mixed and distorted time-varying voltages, yet the standard nucleation-growth frameworks used to interpret ferroelectric switching - most notably the Kolmogorov-Avrami-Ishibashi (KAI) and nucleation-limited switching models (NLS) - are derived under the critically limiting assumption of a constant electric field. Thus, the prevailing interpretation of ferroelectric switching dynamics fails under real operating conditions. Here we introduce a compact dynamic-field-driven nucleation and growth (DFNG) model that enables quantitative fits to switching transients across multiple ferroelectric materials to extract time-varying domain wall velocity and growth dimensionality, even under arbitrary voltage waveform. This capability then motivates its use in device modeling under complex signals spanning disparate time and frequency scales. Coupling the compact model to application-related waveforms and circuit-level simulation platform facilitates a predictive materials-circuit co-design framework by linking nucleation and growth parameters to memory window, disturb error, speed, and energy dissipation for next-generation ferroelectric technologies. |
| title | Ferroelectric dynamic-field-driven nucleation and growth model for predictive materials-to-circuit co-design |
| topic | Materials Science |
| url | https://arxiv.org/abs/2602.02957 |