Starch-based hydrogels for heavy metal remediation: A critical review of progress, pitfalls, and rational design

Starch-based hydrogels are widely studied as biobased adsorbents for heavy metal removal, with reported Pb²⁺ and Cu²⁺ capacities ranging from 60 to over 850 mg g^-1. This broad performance spectrum, however, masks a persistent limitation: the origins of such variability remain poorly understood, and the field consequently relies upon empirical optimization. The present review attributes this methodological inertia to three interrelated bottlenecks. The first arises from the widespread omission of functional group density and crosslink density, which precludes quantitative structure-property relationships and renders comparative evaluation logically invalid. The second bottleneck concerns mechanistic assignments, which rest predominantly on single-technique inferences incapable of resolving the relative contributions of complexation, ion exchange, and electrostatic attraction. The third pertains to sustainability assessments, which rarely extend beyond starch renewability and thus neglect crosslinker toxicity and regeneration waste. A systematic analysis of the surveyed literature reveals that fewer than 10% of publications employ multi-technique validation, while over 70% fail to report functional group density. Collectively, these deficits define three knowledge gaps: the absence of quantitative predictive models, scarce validation in real wastewater, and insufficient integration of lifecycle metrics. In response, this work outlines a framework centered on standardized reporting of intensive properties, tiered mechanistic validation, and measurable lifecycle criteria as a foundation for the rigorous and transparent development of starch-based adsorbents.