DFT FUKUI DESCRIPTOR-BASED PREDICTION OF ARSENIC ADSORPTION ON GRAPHENE

Arsenic contamination in water remains a significant environmental and public health challenge, necessitating efficient removal strategies. This study employs advanced quantum mechanical calculations to quantitatively evaluate arsenic’s interactions with graphene and water under vacuum and aqueous conditions. Key molecular descriptors, including electron affinity (EA) and global electrophilicity index (GEI), reveal that water (EA = -1.85 eV, GEI = 0.94 eV) and graphene (EA = 1.34 eV, GEI = 2.81 eV) exhibit a higher electron-donating capacity, while arsenic demonstrates strong electron-accepting (EA = 4.87 eV) and electrophilic behavior (GEI = 39.19 eV). These findings suggest that arsenic, being highly electrophilic, preferentially adsorbs onto electron-rich materials like graphene, which has significantly lower GEI and EA values. Additionally, interaction energy gap calculations indicate that arsenic interacts more strongly with graphene (IEGAE = 0.61 eV) than with water (IEGAE = 3.05 eV), reinforcing graphene’s superior adsorption efficiency. A similar trend is observed in the aqueous environment, with a slight reduction in interaction strength due to increased water molecule presence. Molecular orbital analyses, including electrostatic potential mapping and interaction energy band gaps, further confirm graphene’s superior affinity for arsenic removal. These insights highlight graphene’s potential as an advanced adsorbent, offering a sustainable solution for arsenic mitigation in water treatment applications.

Authors

Publication Details

Journal
European Journal of Materials Science and Engineering
Published
2025-09-20
DOI
https://doi.org/10.36868/ejmse.2025.10.03.181
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
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article

DFT FUKUI DESCRIPTOR-BASED PREDICTION OF ARSENIC ADSORPTION ON GRAPHENE

Toyese Oyegoke, AYENI Olusola Ibraheem
European Journal of Materials Science and Engineering
Advanced biosensing and bioanalysis techniques
article

DFT FUKUI DESCRIPTOR-BASED PREDICTION OF ARSENIC ADSORPTION ON GRAPHENE

Toyese Oyegoke, AYENI Olusola Ibraheem
article en

Abstract

Arsenic contamination in water remains a significant environmental and public health challenge, necessitating efficient removal strategies. This study employs advanced quantum mechanical calculations to quantitatively evaluate arsenic’s interactions with graphene and water under vacuum and aqueous conditions. Key molecular descriptors, including electron affinity (EA) and global electrophilicity index (GEI), reveal that water (EA = -1.85 eV, GEI = 0.94 eV) and graphene (EA = 1.34 eV, GEI = 2.81 eV) exhibit a higher electron-donating capacity, while arsenic demonstrates strong electron-accepting (EA = 4.87 eV) and electrophilic behavior (GEI = 39.19 eV). These findings suggest that arsenic, being highly electrophilic, preferentially adsorbs onto electron-rich materials like graphene, which has significantly lower GEI and EA values. Additionally, interaction energy gap calculations indicate that arsenic interacts more strongly with graphene (IEGAE = 0.61 eV) than with water (IEGAE = 3.05 eV), reinforcing graphene’s superior adsorption efficiency. A similar trend is observed in the aqueous environment, with a slight reduction in interaction strength due to increased water molecule presence. Molecular orbital analyses, including electrostatic potential mapping and interaction energy band gaps, further confirm graphene’s superior affinity for arsenic removal. These insights highlight graphene’s potential as an advanced adsorbent, offering a sustainable solution for arsenic mitigation in water treatment applications.

European Journal of Materials Science and EngineeringVol. 10(3)
Openalex Percentile: Top 76%
Advanced biosensing and bioanalysis techniques
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