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Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor
Published on: February 16, 2018
Biochar-based biosensors: from sustainable carbon materials to next-generation sensing platforms
Sacheen Kumar1, Shubhankar Anand1, Veepin Kumar2
1Department of Biotechnology and Bioengineering, School of Biosciences and Technology, Galgotias University, Greater Noida, Uttar Pradesh, India-203201. sacheen3@gmail.com.
Abstract:
Growing demand for rapid, sensitive, and affordable analytical tools in healthcare, environmental monitoring, and food safety is driving interest in sustainable carbon nanomaterials for biosensors. Biochar, derived from biomass via pyrolysis or hydrothermal carbonization, has emerged as a promising candidate due to its tunable porosity, high surface area, rich surface functionalities, and low cost from waste feedstocks. This review highlights biochar as a sustainable biosensing component, beginning with an overview of modern biosensor technologies and carbonaceous nanomaterials' role in enhancing transduction efficiency, sensitivity, and selectivity. This review examines how thermochemical conversion routes, process parameters (temperature, heating rate, and residence time), and feedstock characteristics govern key biochar properties-pore structure, graphitization, surface functional groups, and heteroatom content-which determine electrochemical behavior and bioreceptor immobilization capacity. Special attention is given to engineered and nano-scaled biochars, where activation, heteroatom doping, and composite formation with metals, metal oxides, and carbon allotropes address limitations including moderate surface area, structural heterogeneity, and limited electroactive sites. Applications of biochar-based electrochemical and optical biosensors for detecting small molecules, heavy metals, pollutants, and clinical biomarkers are consolidated, emphasizing limits of detection, sensitivity, linear range, response time, and stability. Sustainability and techno-economic aspects-feedstock availability, energy requirements, co-product valorization, life-cycle impacts, and cost competitiveness-are examined. Persistent challenges including batch-to-batch variability, lack of standardization, scalable functionalization difficulties, and environmental fate uncertainties are analyzed. Finally, emerging opportunities at the interface of biochar science, artificial intelligence, and advanced manufacturing are outlined, defining priorities for translating laboratory progress into reliable real-world diagnostic platforms.
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