Adnan Ali Khan

Mr. Adnan Ali Khan

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 April 2021 in Chemistry of Materials
Verified
Journal Article
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IMImran Muhammad
Imran Muhammad
UYUmer Younis
Umer Younis
HXHuanhuan Xie
Huanhuan Xie
AKAdnan Ali Khan
Adnan Ali Khan
AKAbdul Khaliq
Abdul Khaliq
QSQiang Sun
Qiang Sun

6 January 2023 in Nanomaterials
Verified
Journal Article
Open access
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Yasair S. S. Al-FaiyzYasair S. S. Al-Faiyz
Yasair S. S. Al-Faiyz
SSSehrish Sarfaraz
Sehrish Sarfaraz
MYMuhammad Yar
Muhammad Yar
SMSajida Munsif
Sajida Munsif
AKAdnan Ali Khan
Adnan Ali Khan
KAKhurshid Ayub
Khurshid Ayub
V-series nerve agents are very lethal to health and cause the inactivation of acetylcholinesterase which leads to neuromuscular paralysis and, finally, death. Therefore, rapid detection and elimination of V-series nerve agents are very important. Herein, we have carried out a theoretical investigation of carbon nitride quantum dots (C2N) as an electrochemical sensor for the detection of V-series nerve agents, including VX, VS, VE, VG, and VM. Adsorption of V-series nerve agents on C2N quantum dots is explored at M05-2X/6-31++G(d,p) level of theory. The level of theory chosen is quite adequate in systems describing non-bonding interactions. The adsorption behavior of nerve agents is characterized by interaction energy, non-covalent interaction (NCI), Bader’s quantum theory of atoms in molecules (QTAIM), frontier molecular orbital (FMO), electron density difference (EDD), and charge transfer analysis. The computed adsorption energies of the studied complexes are in the range of −12.93 to −17.81 kcal/mol, which indicates the nerve agents are physiosorbed onto C2N surface through non-covalent interactions. The non-covalent interactions between V-series and C2N are confirmed through NCI and QTAIM analysis. EDD analysis is carried out to understand electron density shifting, which is further validated by natural bond orbital (NBO) analysis. FMO analysis is used to estimate the changes in energy gap of C2N on complexation through HOMO-LUMO energies. These findings suggest that C2N surface is highly selective toward VX, and it might be a promising candidate for the detection of V-series nerve agents.

1 March 2022 in Journal of Molecular Graphics and Modelling
Verified
Journal Article
Closed access
MAMisbah Asif
Misbah Asif
HSHasnain Sajid
Hasnain Sajid
KAKhurshid Ayub
Khurshid Ayub
AKAdnan Ali Khan
Adnan Ali Khan
RARashid Ahmad
Rashid Ahmad
TMTariq Mahmood
Tariq Mahmood

28 January 2022 in RSC Advances
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Journal Article
Open access
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MEMehdi Esrafili
Mehdi Esrafili
AKAdnan Ali Khan
Adnan Ali Khan
The development of effective drug delivery vehicles is essential for the targeted administration and/or controlled release of drugs. Using first-principles calculations, the potential of alkali metal (AM = Li, Na, and K) decorated C60 fullerenes for delivery of 5-fluorouracil (5FU) is explored. The adsorption energies of the 5FU on a single AM atom decorated C60 are −19.33, −16.58, and −14.07 kcal mol−1 for AM = Li, Na, and K, respectively. The results, on the other hand, show that up to 12 Li and 6 Na or K atoms can be anchored on the exterior surface of the C60 fullerene simultaneously, each of which can interact with a 5FU molecule. Because of the moderate adsorption energies and charge-transfer values, the 5FU can be simply separated from the fullerene at ambient temperature. Furthermore, the results show that the 5FU may be easily protonated in the target cancerous tissues, which facilitates the release of the drug from the fullerene. The inclusion of solvent effects tends to decrease the 5FU adsorption energies in all 5FU-fullerene complexes. This is the first report on the high capability of AM decorated fullerenes for delivery of multiple 5FU molecules utilizing a C60 host molecule.

10 November 2022 in ACS Omega
Verified
Journal Article
Open access
HUHabib Ullah
Habib Ullah
RARashid Ahmad
Rashid Ahmad
AKAdnan Ali Khan
Adnan Ali Khan
NLNa Eun Lee
Na Eun Lee
JLJaewoo Lee
Jaewoo Lee
S. O. ChoS. O. Cho
S. O. Cho
Advanced anodic SnO2 nanoporous structures decorated with Cu2O nanoparticles (NPs) were employed for creatinine detection. Anodization of electropolished Sn sheets in 0.3 M aqueous oxalic acid electrolyte under continuous stirring produced complete open top, crack-free, and smooth SnO2 nanoporous structures. Structural analyses confirm the high purity of rutile SnO2 with successful functionalization of Cu2O NPs. Morphological studies revealed the formation of self-organized and highly-ordered SnO2 nanopores, homogeneously decorated with Cu2O NPs. The average diameter of nanopores is ∼35 nm, while the average Cu2O particle size is ∼23 nm. Density functional theory results showed that SnO2@Cu2O hybrid nanostructures are energetically favorable for creatinine detection. The hybrid nanostructure electrode exhibited an ultra-high sensitivity of around 24343 μA mM-1 cm-2 with an extremely lower detection limit of ∼0.0023 μM, a fast response time (less than 2 s), and wide linear detection ranges of 2.5-45 μM and 100 μM to 15 mM toward creatinine. This is ascribed to the creation of highly active surface sites as a result of Cu2O NP functionalization, SnO2 band gap diminution, and the formation of heterojunction and Cu(1)/Cu(ll)-creatinine complexes through secondary amines which occur in the creatinine structure. The real-time analysis of creatinine in blood serum by the fabricated electrode evinces the practicability and accuracy of the biosensor with reference to the commercially existing creatinine sensor. The proposed biosensor demonstrated excellent stability, reproducibility, and selectivity, which reflects that the SnO2@Cu2O nanostructure is a promising candidate for the non-enzymatic detection of creatinine.

14 July 2022 in ACS Applied Nano Materials
Verified
Journal Article
Closed access
HUHabib Ullah
Habib Ullah
FUFahad Usman
Fahad Usman
MRMuhammad Asim Rasheed
Muhammad Asim Rasheed
AKAdnan Ali Khan
Adnan Ali Khan
RARashid Ahmad
Rashid Ahmad
S. O. ChoS. O. Cho
S. O. Cho