High‐Precision In‐Sensor Computing Reaching Up to 10 Bits

The growing demand for data-centric and intelligent applications calls for seamless integration of sensing, memory, and computation within a single device to improve efficiency, reduce energy consumption, and enable real-time processing. However, the adoption of such in-sensor computing is hindered by limited reconfigurability, which constrains its use in complex tasks beyond basic image processing. Here, we identify cascaded switching driven by interactions among differently polarized domains as a fundamental barrier to achieving high reconfiguration precision. To overcome this, we introduce a polarization energy focusing strategy, enabled by a tailored compositional distribution of ferroelectric and semiconductor materials. This approach yields the first in-sensor computing device with reconfigurable precision reaching 10 bits. Its capability in both conventional image processing and advanced reconstructed optics is demonstrated, highlighting its potential as a high-linearity, high-precision platform for next-generation intelligent systems.

Authors

Institutions

Publication Details

Journal
Advanced Materials
Published
2026-02-22
DOI
https://doi.org/10.1002/adma.202519096
Citations
1
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High‐Precision In‐Sensor Computing Reaching Up to 10 Bits

Linqi Guo, Siping Yang, Liangliang Min, Lei Li et al.
1 citations
Advanced Materials
Ferroelectric and Negative Capacitance Devices
article

High‐Precision In‐Sensor Computing Reaching Up to 10 Bits

Linqi Guo, Siping Yang, Liangliang Min, Lei Li, Chi Zhang, Han Sun, Abd. Rashid bin Mohd Yusoff
article en
1 citations

Abstract

The growing demand for data-centric and intelligent applications calls for seamless integration of sensing, memory, and computation within a single device to improve efficiency, reduce energy consumption, and enable real-time processing. However, the adoption of such in-sensor computing is hindered by limited reconfigurability, which constrains its use in complex tasks beyond basic image processing. Here, we identify cascaded switching driven by interactions among differently polarized domains as a fundamental barrier to achieving high reconfiguration precision. To overcome this, we introduce a polarization energy focusing strategy, enabled by a tailored compositional distribution of ferroelectric and semiconductor materials. This approach yields the first in-sensor computing device with reconfigurable precision reaching 10 bits. Its capability in both conventional image processing and advanced reconstructed optics is demonstrated, highlighting its potential as a high-linearity, high-precision platform for next-generation intelligent systems.

Advanced MaterialsVol. 38(17)
Soochow University (CN), University of Technology Malaysia (MY), Yangzhou University (CN)
Affordable and clean energy
Openalex Percentile: Top 48%
Ferroelectric and Negative Capacitance Devices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

High‐Precision In‐Sensor Computing Reaching Up to 10 Bits — Linqi Guo, Siping Yang, et al. · Advanced Materials (2026) | TGRS Research Map | TGRS