Thermal-Based Droplet Composition Analysis: From Fundamentals to Applications

Abstract

Thermal processes in droplets, governed by thermophysical properties, evaporation dynamics, reaction energetics and internal flows, encode rich chemical and biological compositional information. This review provides a comprehensive overview of thermal-based droplet composition analysis, linking fundamental heat and mass transfer mechanisms to practical sensing methodologies and emerging applications. Key techniques are categorized based on the thermodynamic/thermophysical measurement parameters: enthalpy change (ΔH) via microcalorimetry and thermal shift assays; thermal conductivity (k) and specific heat capacity (cp) through active excitation; temperature fields using contact/non-contact thermometry; and evaporation-induced deposition patterns driven by capillary and Marangoni flows. These label-free approaches enable real-time quantification of analyte concentration, binding affinities, reaction kinetics and metabolic activity in droplets. Applications span nucleic acid/protein biomarker detection in blood, urine and saliva, as well as biochemical reaction monitoring in droplet microreactors. Recent machine learning (ML) integration has further boosted analytical performance, achieving high-accuracy component classification, concentration prediction and disease diagnosis from thermal fingerprints. Finally, we address current challenges and highlight future directions for intelligent, multimodal thermal sensing platforms toward point-of-care diagnostics, drug discovery and materials synthesis. By bridging fundamental thermal physics with practical label-free sensing, this review provides a timely and comprehensive resource for advancing point-of-care diagnostics, drug discovery, and materials synthesis.