SinoGreenTech Academic Portal
KM
Verified CAS / Academic Author1 Decoded Studies

Prof. KONG Miao

SinoGreenTech Intelligence Archive (analysis based on Sci China Mater 2025, 68(12): 4307–4327)

Research Publications & English Decoded Briefs

Showing 1 publications
SCIENCE CHINA Materials2025DOI: 10.1007/s40843-025-3726-3

Advances in Olfactory Displays for Multisensory Immersion: Principles, Applications, and Future Directions

Olfactory displays remain the least commercialized modality in immersive virtual reality (VR) despite olfaction's disproportionate influence on emotion, memory consolidation, and hazard detection. This review classifies reported olfactory display mechanisms into airflow-based, atomization-based, and heating-based architectures, detailing their electrical characteristics, scent delivery latency, and residual odor management. Stationary, portable, and wearable form factors are systematically compared, with emphasis on structural configurations and operational constraints. Recent noninvasive electrical stimulation approaches for inducing olfactory percepts—including transethmoid olfactory bulb stimulation, subdural electrode activation of the olfactory tract, and direct orbitofrontal cortex stimulation—are examined alongside their clinical evidence base. The analysis identifies a persistent trade-off between scent switching speed and device miniaturization: airflow systems achieve rapid clearing but require bulky pumps and long transmission paths, while atomization and heating approaches reduce form factor at the cost of thermal management and nozzle clogging. Driven by flexible electronics, MEMS, and AI, the field is converging toward flexible, wearable, miniaturized, and intelligent olfactory displays. However, quantitative benchmarks for scent delivery latency, cross-contamination rates, and long-term reliability remain sparse, impeding standardization and commercial translation. This review consolidates the empirical foundation needed to prioritize engineering efforts and establish performance metrics for next-generation olfactory interfaces.