Computational framework demonstrates quantitative translation of literary clothing descriptors into breathable fabric parameters, indicating a novel design route for functional textiles.
Bridging cultural semantics and engineering-oriented textile design remains a significant challenge in the development of intelligent functional materials. This study proposes a three-level mapping framework that quantitatively translates clothing descriptions in Ming and Qing novels into textile engineering parameters through semantic deconstruction, perceptual evaluation, and material characterization. Historical semantic clusters associated with lightweight, ventilation, and moisture management are extracted and linked to user perception and fabric properties using Word2Vec, Delphi analysis, partial least squares regression, and structural equation modeling. The resulting model achieves a prediction coefficient (R2) of 0.81 for air permeability and establishes a quantitative interface between literary semantics and engineering indicators. Guided by the semantic concept of Summer Plain Yarn, a regenerated cellulose fabric reaches an air permeability of 215 mm/s, while a multifunctional single-layer fabric inspired by the concept of lightweight comfort achieves 192 mm/s together with a UPF above 50 and an antibacterial rate exceeding 98%. Beyond providing a culturally informed strategy for breathable textile development, the proposed semantic-to-parameter mapping framework offers a novel methodology for the design of functional materials in wearable electronic and electromagnetic textile systems, where optimized transport characteristics and human-centered performance are critical.
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J. Z. Han (2026) studied this question.
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