Abstract
ABSTRACT
Solar interfacial evaporation (SIE) offers a low‐energy route for desalination and water purification, but high‐performance evaporator design still relies heavily on experience. Here, we report Photothermal‐Seek, a literature‐grounded and evidence‐anchored knowledge framework that connects synthesis, structure, and performance information in SIE materials. Built from 2771 publications, Photothermal‐Seek integrates large language model (LLM)‐assisted extraction, graph‐based reasoning, and full‐text retrieval of source evidence, generating a knowledge base with 57 707 nodes, 126 649 relationships, and 1535 curated material nodes. Repeated object‐level audits showed that most sampled extracted objects were supported by source evidence, while benchmark evaluation demonstrated improved domain‐specific reasoning relative to general‐purpose language models. Literature‐scale semantic analysis shows that conjugated materials had the largest representation in the corpus‐defined upper evaporation‐rate tertile, while multicomponent systems near the conjugated–carbonaceous/fibrous semantic boundary emerged as candidates for further investigation. Guided by this rule, we built and tested a polypyrrole‐coated delignified wood evaporator with a cellulose nanofiber/poly(vinyl alcohol) capillary‐regulation layer (PPy@DW/CP), which achieved 2.275 kg·m
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. A held‐out Dyson sphere‐like evaporator (DSE‐V) case further supports performance estimation for unseen evaporator designs. These results show that literature‐grounded knowledge graphs can connect reported SIE knowledge with real material design and support the early assessment of new evaporator systems.