Work

Temporally resolved concentration profiling via computationally limited, distributed sensor nodes

Year: 2024

Type: article

Abstract: Accurate mapping of chemical concentrations in reactor networks remains an obstacle to establish complete systems‐level insight and control. This issue extends beyond traditional reactor design to biological and other inaccessible systems of interest. Recent developments in novel materials with non‐volatile memory allow autonomous sensor nodes to record information with minimal external supervision. Integrating these materials in solution suspended particles demonstrates the unique potential for diffuse measurements of chemical data at the microscale. In this study, we establish a generalized workflow for the simulated deployment of time aware particle sensors (TAPS) in ideal reactor systems to measure analyte profiles, using Gillespie kinetic Monte Carlo algorithms (KMC). Our results show that computationally‐limited, chemically sensitive tracer particles capable of timestamping an analyte detection event can provide accurate analyte profiles throughout multistage reactors in an ensemble fashion.

Source: AIChE Journal

DOI: 10.1002/aic.18691

Authors: Matthew Lee Manion, Joshua Doctor, Albert Tianxiang Liu

Institution: University of Michigan

Language: English

Topic: Fault Detection and Control Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,940

Funders: National Science Foundation, American Chemical Society Petroleum Research Fund