Microscale 3D‐Printed Digital Strain Switches for Embedded Mechanical Computation

ABSTRACT Conventional strain sensors output continuous analog signals requiring amplification, filtering, and digital conversion, adding hardware that increases size, weight, and power (SWaP), complicating low‐SWaP applications. Here, we introduce microscale digital strain switches that open and close at a designed strain threshold, delivering a native digital output without additional signal conditioning. Devices are directly printed on flexible films via two‐photon polymerization followed by metallization and laser ablation for trace isolation. A closed‐form kinematic model maps chevron geometry to threshold strain, prescribing threshold targets between and microstrain (). Digital image correlation (DIC) shows results across 110 devices agree with model predictions within 5% after an empirical correction factor is added to compensate for polymer shrinkage and film stress. Electrical characterization of devices yielded , and no switch bouncing was observed across 50 closure events. Sensors operate reliably through the maximum cycles tested. Series and parallel wiring of strain switches demonstrates strain‐activated AND, OR, and XOR logic with zero standby power at the device level. Together, the printed sensors and geometry‐to‐threshold framework enable distributed, ultra‐low‐power event detection in compliant systems and suggest a pathway to embedded mechanical computation.

Authors

Institutions

Publication Details

Journal
Advanced Materials Technologies
Published
2026-09-28
DOI
https://doi.org/10.1002/admt.71359
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Microscale 3D‐Printed Digital Strain Switches for Embedded Mechanical Computation

Regan Kubicek, Sarah Bergbreiter, Gabriel Smith, Daniel Quinn
Advanced Materials Technologies
Advanced Sensor and Energy Harvesting Materials
article

Microscale 3D‐Printed Digital Strain Switches for Embedded Mechanical Computation

Regan Kubicek, Sarah Bergbreiter, Gabriel Smith, Daniel Quinn
article en

Abstract

ABSTRACT Conventional strain sensors output continuous analog signals requiring amplification, filtering, and digital conversion, adding hardware that increases size, weight, and power (SWaP), complicating low‐SWaP applications. Here, we introduce microscale digital strain switches that open and close at a designed strain threshold, delivering a native digital output without additional signal conditioning. Devices are directly printed on flexible films via two‐photon polymerization followed by metallization and laser ablation for trace isolation. A closed‐form kinematic model maps chevron geometry to threshold strain, prescribing threshold targets between and microstrain (). Digital image correlation (DIC) shows results across 110 devices agree with model predictions within 5% after an empirical correction factor is added to compensate for polymer shrinkage and film stress. Electrical characterization of devices yielded , and no switch bouncing was observed across 50 closure events. Sensors operate reliably through the maximum cycles tested. Series and parallel wiring of strain switches demonstrates strain‐activated AND, OR, and XOR logic with zero standby power at the device level. Together, the printed sensors and geometry‐to‐threshold framework enable distributed, ultra‐low‐power event detection in compliant systems and suggest a pathway to embedded mechanical computation.

Advanced Materials Technologies
DEVCOM Army Research Laboratory (US), Carnegie Mellon University (US)
Affordable and clean energy
Openalex Percentile: Top 21%
Advanced Sensor and Energy Harvesting Materials
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.

Microscale 3D‐Printed Digital Strain Switches for Embedded Mechanical Computation — Regan Kubicek, Sarah Bergbreiter, et al. · Advanced Materials Technologies (2026) | TGRS Research Map | TGRS