the removal of the most hazardous heavy metal

Overview

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Key numbers

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also exists in three thermodynamic stable forms Cr(0), Cr(III), logical activity of terrestrial and aquatic organisms. In plants,
increased exposure to arsenic.21 Peripheral neuropathy is the the presence of acid in the stomach. These stable oxidation
initial concentration of heavy metals signicantly inuences the linear, indicating favorable adsorption when n = 1, favorable
direct relation between the adsorbent capacity and initial sorption energy value is in the range of 8 to 16 kJ mol−1, it
AES). ICP-MS is 10–100 times superior to ICP-AES.43 The the removal of heavy metals due to their stable nature and high
also notable adsorbents for heavy metal ions.57 Employing tion, non-toxic nature, ease of synthesis, and high adsorption
carbonate nanocomposites (Cs/CaCO3) show signicant carbon-based materials as adsorbents.66 CNTs exhibit a stable
binding agents are used to modify their surface. These modi- the range of 13.3–15.1 mg g−1. The detection limit was found to
having a surface area of 9.1 m2 g−1 showed 92% and 91% emerging adsorbents for the removal of heavy metals.95
adsorb As ions including iron oxide nanoparticle-coated achieving an impressive 99% removal eﬃciency under the
Momčilović et al. used AC prepared from the cones of 99% removal eﬃciency at a concentration of 200 ppm.
ACNFs). These activated NFs exhibited an adsorption able removal eﬃciency of 97% at pH 2. The adsorption capacity
ions, achieving a 98.87% removal eﬃciency. The oxygenated of the –OH group, indicating that Cr(VI) binding primarily
enhance the adsorption eﬃciency. Carbon-based materials remove Cd(II) ions from water, achieving 72% maximum
models are shown in Table 2. revealed that the sawdust of Pinus sylvestris also has the capacity
Table 2 Comparison of diﬀerent carbon-based adsorbents for the removal of heavy metals
As(V) and As(III) Microwave assisted MWCNTs 6 92.0% and 91.0% removal Temkin, Dubinin-Radushkevich, Pseudo-rst order 82
ciency of 96% was observed. The adsorption process followed corncob (MCC) and Jatropha oil cake (JOC),105 bagasse y ash,106
capacity of orange waste was found to be 0.43 mmol g−1 at pH 6 the bound atoms (Na+ and Mg2+) are exchanged with the heavy
reduction in metal levels (97.4% for Pb, 79% for Cu and 73.28%
lead, exhibiting a maximum removal eﬃciency of 99.5%.116 process.138 In another study, Staphylococcus saprophyticus
Javanshir and colleagues synthesized iron nanoparticles of chromium(VI) ions, showing a removal eﬃciency of 99.75%
an arsenic removal eﬃciency of 93.8% with a maximum possesses enriched functional groups, which aid in the
globulus).126 Additionally, iron nanoparticles (BB-Fe NPs) eﬃciency reached 95.3%.143 Additionally, Bacillus subtilis coated
demonstrated the capacity for arsenic removal. Table 3 lists the of 84% and a high recovery percentage (76.4%), making it
Table 3 Comparison of diﬀerent agriculture waste-based adsorbents for the removal of heavy metals
Sugarcane bagasse 6.0 1.61 mg g−1 with 89.31% Freundlich isotherm Pseudo-second-order kinetic models 119
Maize cob 5 95% removal eﬃciency Freundlich model Lagergren rst-order kinetics 122
the mean free energy calculated from the D–R model vulgaris,164 etc. show promise as eﬀective sorbents for Hg(II)
(10.2 kJ mol−1) indicated that the adsorption occurred through ions. Table 4 provides a comparison of various microorganism-
Table 4 Comparison of diﬀerent microorganism-based adsorbents for heavy metals
enhances their surface properties.176 Thus, Neolaka et al. re- process, as supported by the mean free energy value of less than
showing more than 90% removal eﬃciency towards Cd(II) porous silica modied by iron-manganese binary oxide
ions.184 Another study showed that a silica gel material modied (FeMnOx/SBA-15) with 76.5% FeMnOx mass fraction,188 silica-
tive DH° values and negative DG° values show that the adsorp- ions. Table 5 summarizes the diﬀerent inorganic-based adsor-
Table 5 Comparison of various inorganic-based adsorbents for the removal of heavy metals
Cr(VI) Bentonite clay (BC) 3 95.74% 172
Bentonite clay@MnFe2O4 composite (BCMFC) 3 98.65% 172
Polyethylenimine-functionalized mesocellular silica foam 5 90% 184
As(III) and Mesoporous silica modied by iron-manganese binary oxide (FeMnOx/SBA-15) Below 9 90% of As 32.89 mg g−1 As(III) 188
As(V) with 76.5% FeMnOx mass fractions 35.71 mg g−1 As(V)
Red mud 7.25 for 96.52% for As(V) 173

Methods (brief)

reach the targeted functional groups. Alternatively, cryogels etry, atomic absorption spectrophotometry, and inductive
Fe2+, and Fe3+.50 Atomic absorption spectrophotometry requires Commercially available adsorbents predominantly consist of
the sample to be in atomic gas form and can determine carbon-based adsorbents such as graphene, carbon nanotubes,
inductively coupled plasma mass spectrometry (ICP-MS) and rolled-up graphene sheets. All these materials fall in the cate-
inductively coupled plasma atomic emission spectrometry (ICP- gory of nanomaterials and can be employed as adsorbents for
AES). ICP-MS is 10–100 times superior to ICP-AES.43 The the removal of heavy metals due to their stable nature and high
graphene oxide functionalized with alpha cyclodextrin and These types of adsorbents have the ability to remove organic
cyclodextrin-polycaprolactone/TiO2-NPs, chitosan/clay, and adsorbents, the regeneration of these adsorbents through
65 R. Sen Gupta, P. K. Samantaray and S. Bose, Going beyond cyclodextrin-polypyrrole nanocomposites, J. Mol. Liq.,

Implications

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Update history

The five most recent substantive edits to this page, classified major (evidence or structure moved), correction (a published value or statement was wrong and has been fixed), or minor (narrative rewritten without changing the underlying evidence). Each description is derived from what the edit did to this page; the linked commit is the authoritative record, routine regeneration passes are excluded, and the full version history lives in git. When DOI minting comes online (see schema docs), each entry below will also link to a version-pinned DataCite DOI.

Commit	Date	Change	Description
b01ec52c	2026-08-04	major	2 sections added
d49e450f	2026-08-03	major	5 sections added; narrative text revised