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Investigation of Melting Dynamics of Hafnium Clusters

Ng WC, Lim TL, Yoon TL

J Chem Inf Model, 2017 03 27;57(3):517-528.
PMID: 28178783 DOI: 10.1021/acs.jcim.6b00553

Melting dynamics of hafnium clusters are investigated using a novel approach based on the idea of the chemical similarity index. Ground state configurations of small hafnium clusters are first derived using Basin-Hopping and Genetic Algorithm in the parallel tempering mode, employing the COMB potential in the energy calculator. These assumed ground state structures are verified by using the Low Lying Structures (LLS) method. The melting process is carried out either by using the direct heating method or prolonged simulated annealing. The melting point is identified by a caloric curve. However, it is found that the global similarity index is much more superior in locating premelting and total melting points of hafnium clusters.
Epitaxial growth of graphene on 6H-silicon carbide substrate by simulated annealing method

Yoon TL, Lim TL, Min TK, Hung SH, Jakse N, Lai SK

J Chem Phys, 2013 Nov 28;139(20):204702.
PMID: 24289364 DOI: 10.1063/1.4832043

We grew graphene epitaxially on 6H-SiC(0001) substrate by the simulated annealing method. The mechanisms that govern the growth process were investigated by testing two empirical potentials, namely, the widely used Tersoff potential [J. Tersoff, Phys. Rev. B 39, 5566 (1989)] and its more refined version published years later by Erhart and Albe [Phys. Rev. B 71, 035211 (2005)]. Upon contrasting the results obtained by these two potentials, we found that the potential proposed by Erhart and Albe is generally more physical and realistic, since the annealing temperature at which the graphene structure just coming into view at approximately 1200 K is unambiguously predicted and close to the experimentally observed pit formation at 1298 K within which the graphene nucleates. We evaluated the reasonableness of our layers of graphene by calculating carbon-carbon (i) average bond-length, (ii) binding energy, and (iii) pair correlation function. Also, we compared with related experiments the various distance of separation parameters between the overlaid layers of graphene and substrate surface.
Effects of oxygen variation on the improved structural stability, electronic and optical properties of ZnTeO compounds

Chang YHR, Yoon TL, Lim TL, Koh PW, Goh ES

J Phys Condens Matter, 2020 Jan 27;32(22):225701.
PMID: 31986494 DOI: 10.1088/1361-648X/ab7032

Crystalline ZnTeO thin films are promising materials for next generation photovoltaics. However, their structural stability and optical nonlinearity potential in bulk form have not been reported. Here, structural, electronic and optical properties of ZnTeO composites have been thoroughly studied using genetic algorithm and density functional theory (DFT). Energetically, mechanically and dynamically stable O-rich phases, namely Zn2Te2O6 and ZnTeO4, were obtained. Ground-state properties such as lattice constants and simulated XRD were analyzed and compared to the experimental literature wherever possible. With a G 0 W 0 corrected band gap, these semiconducting phases display several desirable features, namely, Jahn-Teller distorted cations, hardness and shear anisotropy-induced optical nonlinearity that increase monotonically as O concentration elevates. Such trends appear to be consistent with that seen in the experimental study of ZnTeO thin film. It is observed that Zn-d, Te-p and O-p states have immense influence towards the electronic properties of these structures. Both phases exhibit steep elevation of absorption throughout the ultraviolet (UV) range, hitting peak value of ~5.0 × 105 cm-1. Of particular interest, the non-centrosymmetric ZnTeO4 has second harmonic generation coefficients (9.84 pm V-1 and 2.33 pm V-1 at static limit) greater than borates crystal and large birefringence that exceeds 0.08 in deep UV region, thus highlighting its potential pedigree as new optical materials in UV range.
A first-principles study of two-dimensional NbSe2H/g-ZnO van der Waals heterostructures as a water splitting photocatalyst

Yeoh KH, Chew KH, Yoon TL, Chang YHR, Ong DS

Phys Chem Chem Phys, 2021 Nov 03;23(42):24222-24232.
PMID: 34668497 DOI: 10.1039/d1cp03565g

Based on first-principles calculations, we propose a new two-dimensional (2D) van der Waals (vdW) heterostructure that can be used as a photocatalyst for water splitting. The heterostructure consists of vertically stacked 2D NbSe2H and graphene-like ZnO (g-ZnO). Depending on the stacking orders, we identified two configurations that have high binding energies with an energy band gap of >2.6 eV. These 2D systems form a type-II heterostructure which enables the separation of photoexcited electrons and holes. The presence of a strong electrostatic potential difference across the 2D NbSe2H and g-ZnO interface is expected to suppress the electron-hole recombination leading to an enhancement in the efficiency of the photocatalytic activity. Our study also shows that the 2D NbSe2H/g-ZnO vdW heterostructure has good thermodynamic properties for water splitting. Furthermore, the optical absorption of the 2D NbSe2H/g-ZnO vdW heterostructure extends into the visible light region. Our results suggest that the 2D NbSe2H/g-ZnO vdW heterostructure is a promising photocatalytic material for water splitting.
A novel machine learning scheme for classification of medicinal herbs based on 2D-FTIR fingerprints

Yoon TL, Yeap ZQ, Tan CS, Chen Y, Chen J, Yam MF

Spectrochim Acta A Mol Biomol Spectrosc, 2022 Feb 05;266:120440.
PMID: 34627017 DOI: 10.1016/j.saa.2021.120440

A proof-of-concept medicinal herbs identification scheme using machine learning classifiers is proposed in the form of an automated computational package. The scheme makes use of two-dimensional correlation Fourier Transformed Infrared (FTIR) fingerprinting maps derived from the FTIR of raw herb spectra as digital input. The prototype package admits a collection of 11 machine learning classifiers to form a voting pool. A common set of oversampled dataset containing 5 different herbal classes is used to train the pool of classifiers on a one-verses-others manner. The collections of trained models, dubbed the voting classifiers, are deployed in a collective manner to cast their votes to support or against a given inference fingerprint whether it belongs to a particular class. By collecting the votes casted by all voting classifiers, a logically designed scoring system will select out the most probable guess of the identity of the inference fingerprint. The same scoring system is also capable of discriminating an inference fingerprint that does not belong to any of the classes the voting classifiers are trained for as the 'others' type. The proposed classification scheme is stress-tested to evaluate its performance and expected consistency. Our experimental runs show that, by and large, a satisfactory performance of the classification scheme of up to 90 % accuracy is achieved, providing a proof-of-concept viability that the proposed scheme is a feasible, practical, and convenient tool for herbal classification. The scheme is implemented in the form of a packaged Python code, dubbed the "Collective Voting" (CV) package, which is easily scalable, maintained and used in practice.
Thermoelectric and piezoelectric properties of the predicted AlxIn1-xN composites based on ab initio calculations

Chang YHR, Yoon TL, Lim TL, Tuh MH, Goh ES

Phys Chem Chem Phys, 2017 Sep 20;19(36):24613-24625.
PMID: 28856366 DOI: 10.1039/c7cp03749j

Theoretical investigations of the thermoelectric and piezoelectric characteristics in the AlxIn1-xN system have been carried out based on a first principles approach in combination with the semi-classical Boltzmann transport concept and density functional perturbation theory. Based on our previous work, herein, the study specimens Al5InN6, Al6In2N8, Al4In2N6, Al3In3N6, Al2In4N6, and AlIn7N8 have been predicted to be stable phases. These novel phases intrinsically exhibit moderate positive Seebeck curves (199.1-284.6 μV K-1) and a ZT close to unity that varies marginally over a broad temperature range of 200-800 K, demonstrating the sign of good bipolar effect tolerance. Addition of heftier elements, such as In, results in lower thermal conductivity, which in turn generates a high power factor (0.019-0.345 W m-1 K-2) in these alloys. While hole doping enhances the peak Seebeck coefficient of each phase, the electrical conductivity has been greatly compromised, resulting in a lower power factor. These composites also exhibit large piezoelectric constants, in which their respective largest piezoelectric tensor is several orders higher than that of quartz. The decomposition process shows that In and N are the main contributors of the internal piezoelectric term. Overall results indicate that AlxIn1-xN show bright prospects in thermoelectric and piezoelectric applications.
First-principles studies on the effects of halogen adsorption on monolayer antimony

Yeoh KH, Yoon TL, Ong DS, Lim TL, Zuntu Abdullahi Y

Phys Chem Chem Phys, 2017 Sep 27;19(37):25786-25795.
PMID: 28914944 DOI: 10.1039/c7cp03028b

Using first-principles calculations, we carry out systematic studies on the electronic, magnetic and structural properties of halogenated β-phase antimonene. We consider two different levels of halogen adatom coverage i.e. Θ = 1/8 and Θ = 1/18. It is found that F, Cl and Br adatoms act as acceptors whereas the I adatom acts as a donor. For a high coverage of Θ = 1/8, halogenated β-phase antimonene exhibits metallic characteristics. With a lower coverage of Θ = 1/18, through the adsorption of F, Cl and Br the semiconducting unstrained antimonene becomes metallic. In contrast, I-adsorbed antimonene remains semiconducting but exhibits magnetic behavior. We further investigate the effects of bi-axial strain on the halogenated β-phase antimonene. It is found that bi-axial strain can only induce ferromagnetism on the halogenated antimonene at Θ = 1/18. However, the ferromagnetism is suppressed when the applied strain is high. We uncover that the emergence of strain-dependent magnetism is attributed to the presence of localized states in the bandgap resulting from collective effects of bi-axial strain and the adsorption of halogen atoms.
The effect of vacancy defects on the electromechanical properties of monolayer NiTe2 from first principles calculations

Yeoh KH, Chew KH, Chang YHR, Yoon TL, Ong DS

Phys Chem Chem Phys, 2022 Dec 05.
PMID: 36468660 DOI: 10.1039/d2cp05102h

The electromechanical properties of monolayer 1-T NiTe2 under charge actuation were investigated using first-principles density functional theory (DFT) calculations. Monolayer 1-T NiTe2 in its pristine form has a work area density per cycle of up to 5.38 MJ m-3 nm upon charge injection and it can generate a strain and a stress of 1.51% and 0.96 N m-1, respectively. We found that defects in the form of vacancies can be exploited to modulate the electromechanical properties of this material. The presence of Ni-vacancies can further enhance the generated stress by 22.5%. On the other hand, with Te-vacancies, it is possible to improve the work area density per cycle by at least 145% and also to enhance the induced strain from 1.51% to 2.92%. The effect of charge polarity on the contraction and expansion of monolayer 1T-NiTe2 was investigated. Due to its excellent environmental stability and good electromechanical properties, monolayer NiTe2 is considered to be a promising electrode material for electroactive polymer (EAP) based actuators.
Computational Screening of a Single-Atom Catalyst Supported by Monolayer Nb2S2C for Oxygen Reduction Reaction

Yeoh KH, Chang YHR, Chew KH, Jiang J, Yoon TL, Ong DS, et al.

Langmuir, 2024 Feb 08.
PMID: 38329924 DOI: 10.1021/acs.langmuir.3c03188

The search for high-performance catalysts to improve the catalytic activity for an oxygen reduction reaction (ORR) is crucial for developing a proton exchange membrane fuel cell. Using the first-principles method, we have performed computational screening on a series of transition metal (TM) atoms embedded in monolayer Nb2S2C to enhance the ORR activity. Through the scaling relationship and volcano plot, our results reveal that the introduction of a single Ni or Rh atom through substitutional doping into monolayer Nb2S2C yields promising ORR catalysts with low overpotentials of 0.52 and 0.42 V, respectively. These doped atoms remain intact on the monolayer Nb2S2C even at elevated temperatures. Importantly, the catalytic activity of the Nb2S2C doped with a TM atom can be effectively correlated with an intrinsic descriptor, which can be computed based on the number of d orbital electrons and the electronegativity of TM and O atoms.
Utilizing 3D Slicer to incorporate tomographic images into GATE Monte Carlo simulation for personalized dosimetry in yttrium-90 radioembolization

Abdul Hadi MFR, Abdullah AN, Hashikin NAA, Ying CK, Yeong CH, Yoon TL, et al.

Med Phys, 2022 Dec;49(12):7742-7753.
PMID: 36098271 DOI: 10.1002/mp.15980

PURPOSE: Monte Carlo (MC) simulation is an important technique that can help design advanced and challenging experimental setups. GATE (Geant4 application for tomographic emission) is a useful simulation toolkit for applications in nuclear medicine. Transarterial radioembolization is a treatment for liver cancer, where microspheres embedded with yttrium-90 (90 Y) are administered intra-arterially to the tumor. Personalized dosimetry for this treatment may provide higher dosimetry accuracy compared to the conventional partition model (PM) calculation. However, incorporation of three-dimensional tomographic input data into MC simulation is an intricate process. In this article, 3D Slicer, free and open-source software, was utilized for the incorporation of patient tomographic images into GATE to demonstrate the feasibility of personalized dosimetry in hepatic radioembolization with 90 Y.
METHODS: In this article, the steps involved in importing, segmenting, and registering tomographic images using 3D Slicer were thoroughly described, before importing them into GATE for MC simulation. The absorbed doses estimated using GATE were then compared with that of PM. SlicerRT, a 3D Slicer extension, was then used to visualize the isodose from the MC simulation.
RESULTS: A workflow diagram consisting of all the steps taken in the utilization of 3D Slicer for personalized dosimetry in 90 Y radioembolization has been presented in this article. In comparison to the MC simulation, the absorbed doses to the tumor and normal liver were overestimated by PM by 105.55% and 20.23%, respectively, whereas for lungs, the absorbed dose estimated by PM was underestimated by 25.32%. These values were supported by the isodose distribution obtained via SlicerRT, suggesting the presence of beta particles outside the volumes of interest. These findings demonstrate the importance of personalized dosimetry for a more accurate absorbed dose estimation compared to PM.
CONCLUSION: The methodology provided in this study can assist users (especially students or researchers who are new to MC simulation) in navigating intricate steps required in the importation of tomographic data for MC simulation. These steps can also be utilized for other radiation therapy related applications, not necessarily limited to internal dosimetry.