Fungal melanin-based electrospun membranes for heavy metal detoxification of water
Source abstract
Abstract
Abstract In recent years, heavy metal pollution in water resources has become a severe environmental and public health problem worldwide. Thereby, enhanced treatments are urgently needed with respect to eco-friendliness, filtration efficiencies and low operational costs. This study demonstrates how fungal melanin extracted from Armillaria cepistipes (Empa 655) can be applied as a promising biosorbent for removal of toxic heavy metals from water. For this aim, an electrospinning technique was developed to incorporate fungal melanin particles, a novel source of adsorptive species, into polymeric nanofibrous membranes to obtain stable and highly porous filtration systems. Starting spinning dispersions were investigated with respect to their rheological behaviour and electrical conductivity and related to morphological and surface properties of the resulting composite fibres and membranes. Metal adsorption assays were then performed on both raw melanin and melanised membranes. At the physiotoxic concentrations of Pb2+, Cd2+, Ni2+ and Cr3+, fungal melanin was able to remove >90% of heavy metals in single-component solutions. In multi-component solutions incorporating Ca2+ and Zn2+, fungal melanin showed a different affinity to different metals in the following order: Pb2+ > Cr3+ > Ni2+ > Cd2+ > Zn2+ > Ca2+ with an extreme preference for Pb2+ (80% removal) over the essential metals (0% and 12% removal for Ca2+ and Zn2+, respectively). The metal adsorption profiles also showed that melanised membranes were able to maintain the adsorption capacity of the raw melanin. Thus, these novel membranes can be efficiently used as filtration membranes for removal of heavy metals from water.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Plant and Biological Electrophysiology Studies · Microplastics and Plastic Pollution · Slime Mold and Myxomycetes Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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