i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

Elastomers play a crucial role in capturing tactile information for vision‐based tactile sensors (VBTSs), where they transduce contact stimuli into elastic deformation. Different sensor architectures demand distinct elastomer properties, such as optical transparency and mechanical hardness. Conventional forward design approaches, however, rely on iterative trial‐and‐error processes from material preparation to final performance, making them inefficient and difficult to scale. Here, we present i‐Tac, an inverse design pipeline for tailoring the optical and mechanical properties of elastomers used in VBTSs. Inspired by the composite structure of the human dermis, i‐Tac leverages multi‐material additive manufacturing with three distinct PolyJet 3D printing resins. A mixture design methodology is first employed to characterise printed elastomers, generating response surface models (ReSMs) that map material composition to functional properties. Based on user‐specified target requirements, a desirability function is then applied for multi‐objective optimisation, yielding an optimal operating window of compositions. This enables the fabrication of elastomers with desired properties in a single iteration through monolithic manufacturing. Experimental validation confirms the effectiveness of i‐Tac for elastomer customisation and demonstrates its potential for the complete fabrication of VBTSs with tailored performance.

Authors

Institutions

Publication Details

Journal
Advanced Intelligent Systems
Published
2026-04-24
DOI
https://doi.org/10.1002/aisy.202501200
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

Wen Fan, Dandan Zhang
Advanced Intelligent Systems
Advanced Sensor and Energy Harvesting Materials
article

i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

Wen Fan, Dandan Zhang
article en

Abstract

Elastomers play a crucial role in capturing tactile information for vision‐based tactile sensors (VBTSs), where they transduce contact stimuli into elastic deformation. Different sensor architectures demand distinct elastomer properties, such as optical transparency and mechanical hardness. Conventional forward design approaches, however, rely on iterative trial‐and‐error processes from material preparation to final performance, making them inefficient and difficult to scale. Here, we present i‐Tac, an inverse design pipeline for tailoring the optical and mechanical properties of elastomers used in VBTSs. Inspired by the composite structure of the human dermis, i‐Tac leverages multi‐material additive manufacturing with three distinct PolyJet 3D printing resins. A mixture design methodology is first employed to characterise printed elastomers, generating response surface models (ReSMs) that map material composition to functional properties. Based on user‐specified target requirements, a desirability function is then applied for multi‐objective optimisation, yielding an optimal operating window of compositions. This enables the fabrication of elastomers with desired properties in a single iteration through monolithic manufacturing. Experimental validation confirms the effectiveness of i‐Tac for elastomer customisation and demonstrates its potential for the complete fabrication of VBTSs with tailored performance.

Advanced Intelligent Systems
Imperial College London (GB)
University Postgraduate Programme
Openalex Percentile: Top 8%
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.