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<p>Nanomaterials improve biosensors primarily through engineered interfaces that govern target capture, signal transfer, and operational stability, rather than through material identity alone. Nanomaterial engineering is driving the evolution of bioanalytical sensing by enabling programmable surface chemistry, improved bioreceptor immobilization, and enhanced signal transduction across electrochemical, optical, and hybrid platforms. This review systematically maps carbon-based, inorganic/semiconductor, and bio-derived nanomaterial classes to their mechanistic roles in biosensor performance, emphasizing design criteria that govern sensitivity, selectivity, stability, and translation readiness. Carbon platforms (CNTs, graphene derivatives, carbon dots, and biomass-derived carbons) are analyzed through interfacial coupling, protective coatings, and amplification strategies, while inorganic and semiconductor architectures (noble metals, transition-metal oxides/chalcogenides, quantum dots, and nanowires) are evaluated via defect chemistry, morphology control, and hybrid charge-transfer pathways. Bio-derived soft materials (cellulose, lignin/hemicellulose composites, and electroconductive hydrogels) are discussed as scalable scaffolds that support capillarity-driven transport, antifouling behavior, and mechanically compliant sensing formats. Across these material families, performance improvements consistently arise from engineered interfaces that balance target capture with charge/energy transfer and matrix tolerance, rather than from material selection alone. We identify key translational barriers including batch-to-batch variability, limited primary-source traceability of reported metrics, and insufficient benchmarking in complex real samples, and outline an interface-centric roadmap prioritizing standardized reporting, stability validation, and manufacturable architectures aligned with sustainable synthesis routes.</p>

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Design rules of interface engineered nanomaterials for enhanced sensitivity stability and translational performance in bioanalytical biosensing

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月20日

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  • Kushagra Sharma,
  • Brijpal Bisen,
  • S. Reddy Veera Nagaveni

摘要

Nanomaterials improve biosensors primarily through engineered interfaces that govern target capture, signal transfer, and operational stability, rather than through material identity alone. Nanomaterial engineering is driving the evolution of bioanalytical sensing by enabling programmable surface chemistry, improved bioreceptor immobilization, and enhanced signal transduction across electrochemical, optical, and hybrid platforms. This review systematically maps carbon-based, inorganic/semiconductor, and bio-derived nanomaterial classes to their mechanistic roles in biosensor performance, emphasizing design criteria that govern sensitivity, selectivity, stability, and translation readiness. Carbon platforms (CNTs, graphene derivatives, carbon dots, and biomass-derived carbons) are analyzed through interfacial coupling, protective coatings, and amplification strategies, while inorganic and semiconductor architectures (noble metals, transition-metal oxides/chalcogenides, quantum dots, and nanowires) are evaluated via defect chemistry, morphology control, and hybrid charge-transfer pathways. Bio-derived soft materials (cellulose, lignin/hemicellulose composites, and electroconductive hydrogels) are discussed as scalable scaffolds that support capillarity-driven transport, antifouling behavior, and mechanically compliant sensing formats. Across these material families, performance improvements consistently arise from engineered interfaces that balance target capture with charge/energy transfer and matrix tolerance, rather than from material selection alone. We identify key translational barriers including batch-to-batch variability, limited primary-source traceability of reported metrics, and insufficient benchmarking in complex real samples, and outline an interface-centric roadmap prioritizing standardized reporting, stability validation, and manufacturable architectures aligned with sustainable synthesis routes.