# CAREER: Towards Interactive Sensor-Driven Tools for Exploring, Replicating, and Sharing Material Recipes

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · University of Texas at Arlington (TX) · $549,205

## Abstract

Many everyday materials change their behavior as they are mixed, prepared, or processed. These include materials such as inks, gels, pastes, slurries, emulsions, and suspensions, which appear in activities ranging from crafting and food preparation to advanced manufacturing. Small differences in preparation can determine whether a material spreads smoothly, holds its shape, or fails during use. People who work with these materials often rely on trial and error to adjust mixtures, timing, and preparation steps. Important practical knowledge about these processes is rarely documented, which makes it difficult for others to reproduce successful results or learn from failed attempts. This project develops tools that help people observe, measure, and share how these materials behave during preparation and use. By making these processes easier to study and communicate, the project supports learning, experimentation, and collaboration in hands on making. The work expands opportunities for students, educators, and community makers to engage with science and engineering through practical experimentation with materials, strengthening training in advanced manufacturing, creative technologies, and material development.

This project develops a sensing and data platform for studying viscous materials used in fabrication and experimental making practices. The platform centers on a low-cost rheometer that measures the resistance of materials as a small sample is drawn into and expelled from a tube while a pressure sensor records the resulting signals. These measurements provide information about how a material resists flow. Computational analysis of these signals allows materials to be compared, grouped, and tracked as they change during preparation processes such as mixing, setting, or curing. The project will develop tools that organize these measurements into interactive maps of material behavior. A browser extension will connect these measurements to existing online recipe r

## Key facts

- **NSF award ID:** 2543683
- **Awardee organization:** University of Texas at Arlington (TX)
- **SAM.gov UEI:** LMLUKUPJJ9N3
- **PI:** Cesar A Torres
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CAREER-Faculty Erly Career Dev, Cyber-Human Systems, Advanced Manufacturing, GRADUATE INVOLVEMENT
- **Estimated total:** $549,205
- **Funds obligated:** $321,890
- **Transaction type:** Continuing Grant
- **Period:** 06/01/2026 → 05/31/2031

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2543683

## Citation

> US National Science Foundation, Award 2543683, CAREER: Towards Interactive Sensor-Driven Tools for Exploring, Replicating, and Sharing Material Recipes. Retrieved via AI Analytics 2026-06-26 from https://api.ai-analytics.org/grant/nsf/2543683. Licensed CC0.

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