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Sweat induced memristive behavior and its working mechanism for noninvasive diagnostics of chronic kidney and liver diseases

  • Jinlong He
  • , Bai Sun
  • , Songling Wang
  • , Qi Chen
  • , Zelin Cao
  • , Kaikai Gao
  • , Mengna Wang
  • , Teng Wu
  • , Longhui Fu
  • , Kun Wang
  • , Shuai Sun
  • , Xiaobin Ren
  • , Xianxia Yan
  • , Jinyou Shao
  • Frontier Institute of Science and Technology
  • Xi'an Jiaotong University
  • CAS - Fujian Institute of Research on the Structure of Matter
  • Xi'an Jiaotong University
  • The Second Affiliated Hospital of Xi'an Jiaotong University

Research output: Contribution to journalArticlepeer-review

Abstract

Chronic kidney disease (CKD) and chronic liver disease (CLD) have become the most prevalent types of diseases globally. However, early diagnosis and prevention are greatly restricted due to the invasive nature of traditional detection methods and limited access. Sweat, as a non-invasive and easily accessible biological specimen, often contains metabolites related to diseases, and holds great potential in health monitoring and disease diagnosis. In this work, we developed a memristive device with an Ag/Fe2O3/SiO2/FTO structure for noninvasive and highly sensitive detection of CKD and CLD through sweat analysis. The as-prepared memristor exhibits excellent resistive switching characteristics, self-rectifying behavior, and robust cycling stability. Specifically, when evaluated using sweat samples from healthy individuals, CKD patients, and CLD patients, the device manifested distinctive memristive signatures. These unique behaviors enable the precise classification of health status with minimal interference from fluctuations in sweat temperature or pH. Therefore, this work presents a novel, non-invasive, and portable method for disease diagnosis, specifically designed for real-time monitoring of chronic liver and kidney diseases, which demonstrates significant potential for health monitoring and early disease management.

Original languageEnglish
Article number103685
JournalMaterials Today Chemistry
Volume54
DOIs
StatePublished - Jun 2026

Keywords

  • Disease diagnosis
  • Health monitoring
  • Medical engineering
  • Memristor
  • Smart medicine

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