Predictive design of biomass-derived biochar electrodes through quantitative structure-performance relationships

Biochar from biomass residues has emerged as a sustainable alternative to conventional nanocarbon materials for electrochemical biosensors. Due to its low cost and adjustable physicochemical properties, significant progress has been made in developing biochar-based electrochemical sensors. However, the lack of a systematic mechanistic understanding of how interconnected biochar properties influence electrochemical performance limits rational electrode design. This study evaluates the correlation between physicochemical properties of different biomass feedstocks and their electrochemical performance, using quantitative structure-performance relationships to provide an in-depth mechanistic understanding. It was observed that electrochemical performance is governed by the collective interplay of multiple biochar physicochemical properties. With a reverse-engineering approach, it is demonstrated that biochars derived from Grass biomass feedstocks achieve superior electrochemical performance by balancing properties from moderate height particle irregularity (Ra = 0.79-3.31 nm), controlled microporosity (< 25.78%), sufficient hydrophilicity (low C/O < 4.19, moderate inorganic content 4.29-6.84%), and good carbon crystallinity (high sp² > 10.76% and low d₀₀₂ < 3.80 Å). This enables smooth-to-moderate interfacial electrode surface roughness for efficient electrode-electrolyte contact and rapid electron-transfer pathways. Therefore, this understanding shows that intentional feedstock selection based on grass classification can serve as a controllable strategy to engineer the electrode-electrolyte interface for advanced biosensing.