Evidence map›Paper›PMID 42513039›Full record

ArticleMicromachines2026

Time-Domain Simulation and Optimization of the Memory Window for HZO-Based FeFETs Using the NLS Model.

Shangda Han, Weifeng Lü, Yekun Liang, Tianyu Dai

Abstract read
In one paragraph

Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shangda HanSchool of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0009-0008-0306-7071
Weifeng LüSchool of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-4261-2377
Yekun LiangSchool of Electronic Information, Wuhan University, Wuhan 430072, China.ORCID 0009-0005-7282-3377
Tianyu DaiSchool of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0009-0009-4272-3390

Funding

Key State Physics and Chip Technologies, Institute of Semiconductors, Chinese Academy of Sciences SKSP202512
6 · The paper itself

Abstract

Hafnium-zirconium oxide (HZO)-based ferroelectric field-effect transistors (FeFETs) are expected to become core devices for new embedded memory and compute-in-memory systems. However, existing simulations rely on finite-element-based TCAD tools, which are computationally intensive and time-consuming, and they struggle to account for the dynamic flipping of ferroelectric domains. This paper utilizes a time-domain simulation framework based on the nucleation-limited switching (NLS) model coupled with the surface potential of a MOSFET, enabling a self-consistent solution for polarization and electrical characteristics; a Monte Carlo method is employed to simulate device variability, and Shmoo plots are used to identify optimal programming and erasure process windows; an integrated solution is proposed for 22 nm FDSOI devices, addressing geometric scaling, modification of the Landau-Khalatnikov (L-K) dynamic model for ultrathin ferroelectric layers, and suppression of short-channel effects. Model validation is limited to selected operating metrics, and predictive accuracy outside the calibrated cases requires additional independent datasets. This method enables end-to-end simulation of FeFETs, from material polarization and device electrical characteristics to performance optimization, thereby providing model-based analytical and design support for the development of advanced, ultra-low-power FeFETs.

Indexed as

ferroelectric transistorsfully depleted silicon-on-insulator (FDSOI)memory windowMonte Carlo simulationnucleation-limited switching (NLS)

Identifiers

PMID42513039
PMCPMC13413631

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.