arXiv subjects

Nazmul Hasan

Publications and source records attributed to Nazmul Hasan.

13 recordsLinked to original sources

arXiv2026

Dirac Surface States and Nonlocal Quantum Tunneling in Topological Semiconductor Mo$_2$SeTe$_3$ for High-Performance Tunnel FETs

A first-principles and device-level study of the quasi-two-dimensional transition-metal chalcogenide Mo$_2$SeTe$_3$ is performed. The material is found to be a weak topological semiconductor with a finite bulk band gap and symmetry-protected Dirac surface states, indicating strong potential for next-generation low-power quantum electronic devices. An SOC-driven band inversion accompanied by an indirect semiconducting gap of approximately 0.75 eV is observed. Topological nontriviality is rigorously confirmed through Wannier charge-center evolution and $\mathbb{Z}_2$ invariant analysis, yielding weak topological indices of $(0;001)$, while iterative Green's-function surface-state calculations corroborate Dirac-cone conducting states traversing the bulk gap on symmetry-preserving surfaces. Mo$_2$SeTe$_3$ additionally exhibits exceptional dynamical and mechanical stability, pronounced optical anisotropy, high dielectric polarizability, broad infrared-to-visible optical absorption, a large static dielectric constant, and substantial birefringence, making it favorable for photonic and optoelectronic applications. Thermoelectric transport analyses further reveal enhanced carrier mobility and a competitive figure of merit under $n$-type doping near room temperature. A dual-source tunnel field-effect transistor (TFET) is implemented via TCAD simulations with nonlocal band-to-band tunneling, yielding subthreshold switching below the thermionic limit, a high ON/OFF current ratio, and enhanced tunneling efficiency driven by SOC-induced orbital hybridization and topologically enhanced interband coupling. The concurrent realization of nontrivial bulk-boundary correspondence, robust transport properties, and steep-slope switching characteristics establishes Mo$_2$SeTe$_3$ as a multifunctional quantum material platform for topological and next-generation energy-efficient nanoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2025

Strain-induced Moir\'e Reconstruction and Memorization in Two-Dimensional Materials without Twist

Two-dimensional (2D) materials with a twist between layers exhibit a moir\'e interference pattern with larger periodicity than any of the constituent layer unit cells. In these systems, a wealth of exotic phases appear that result from moir\'e-dependent many-body electron correlation effects or non-trivial band topology. One problem with using twist to generate moir\'e interference has been the difficulty in creating high-quality, uniform, and repeatable samples due to fabrication through mechanical stacking with viscoelastic stamps. Here we show, a new method to generate moir\'e interference through the controlled application of layer-by-layer strain (heterostrain) on non-twisted 2D materials, where moir\'e interference results from strain-induced lattice mismatch without twisting or stacking. Heterostrain generation is achieved by depositing stressed thin films onto 2D materials to apply large strains to the top layers while leaving layers further down less strained. We achieve deterministic control of moir\'e periodicity and symmetry in non-twisted 2D multilayers and bilayers, with 97% yield, through varying stressor film force (film thickness X film stress) and geometry. Moir\'e reconstruction effects are memorized after the removal of the stressor layers. Control over the strain degree-of-freedom opens the door to a completely unexplored set of unrealized tunable moir\'e geometric symmetries, which may now be achieved in a high-yield and user-skill independent process taking only hours. This technique solves a long-standing throughput bottleneck in new moir\'e quantum materials discovery and opens the door to industrially-compatible manufacturing for 2D moir\'e-based electronic or optical devices.

cond-mat.mtrl-sci↗

arXiv2025

Comprehensive numerical analysis of doping controlled efficiency in lead free Cs(SnGe)I3 perovskites solar cell

One effective way to prevent toxicity and improve the stability of materials for photovoltaic applications is to exclude lead and organic molecules from perovskite materials. Specifically, the CsSn1-xGexI3 appears to be a promising contender; nonetheless, it requires optimization, particularly bandgap tuning by doping concentration modifications. In this study, density functional theory (DFT) was employed to comprehensively analyze the electronic properties of CsSn1-xGexI3 that influenced light-matter interactions tuning of the perovskite materials by varying composition in B site atoms. We use the solar cell capacitance (SCAPS-1D) simulator to compute device performance; however, it computes the absorption spectrum using a simplified mathematical function that approximates the actual spectrum. To achieve a quantum-mechanical level of accuracy DFT extracted parameters like absorption spectra and bandgap were fed into SCAPS-1D. We find that increasing the Ge concentration leads to a higher bandgap and improved absorption profile, thereby enhancing solar energy conversion efficiency. Thermal and field distribution analyses were also done for the optimized device through a finite-difference time-domain (FDTD) framework. By optimizing the absorber layer with a 75% Ge concentration, we achieve a remarkable PCE of 23.80%. Our findings guide future research in designing high-performance non-leaded halide PSCs, paving the way for low-cost, stable, and highly efficient solar cells through atomic doping-tuned perovskite absorber layers.

cond-mat.mtrl-sci↗

arXiv2024

Bi3+ Doped Nanocrystalline Ni-Co-Zn Spinel Ferrites: Tuning of Physical, Electrical, Dielectric and Magnetic Properties for Advanced Spintronics Applications

This study reports the synthesis and characterization of nanocrystalline Ni0.5Co0.2Zn0.3BixFe2-xO4 x varis by 0.0, 0.025, 0.050, 0.075, 0.100 ferrites synthesized via the sol-gel auto combustion method.The low coercivity values 23.68 to 87.71 Oe are observed,classifying the investigated materials as soft ferromagnetic.The increased magnetic anisotropy K through Bi3+ doping indicates tunable stability in magnetic orientations,making them suitable for multifunctional applications.

cond-mat.mtrl-sci↗

arXiv2024

Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data

Overheating anomaly detection is essential for the quality and reliability of parts produced by laser powder bed fusion (LPBF) additive manufacturing (AM). In this research, we focus on the detection of overheating anomalies using photodiode sensor data. Photodiode sensors can collect high-frequency data from the melt pool, reflecting the process dynamics and thermal history. Hence, the proposed method offers a machine learning (ML) framework to utilize photodiode sensor data for layer-wise detection of overheating anomalies. In doing so, three sets of features are extracted from the raw photodiode data: MSMM (mean, standard deviation, median, maximum), MSQ (mean, standard deviation, quartiles), and MSD (mean, standard deviation, deciles). These three datasets are used to train several ML classifiers. Cost-sensitive learning is used to handle the class imbalance between the "anomalous" layers (affected by overheating) and "nominal" layers in the benchmark dataset. To boost detection accuracy, our proposed ML framework involves utilizing the majority voting ensemble (MVE) approach. The proposed method is demonstrated using a case study including an open benchmark dataset of photodiode measurements from an LPBF specimen with deliberate overheating anomalies at some layers. The results from the case study demonstrate that the MSD features yield the best performance for all classifiers, and the MVE classifier (with a mean F1-score of 0.8654) surpasses the individual ML classifiers. Moreover, our machine learning methodology achieves superior results (9.66% improvement in mean F1-score) in detecting layer-wise overheating anomalies, surpassing the existing methods in the literature that use the same benchmark dataset.

cs.LG↗

arXiv2024

Ferromagnetic Semiconductors and Spintronic Devices

Ferromagnetic semiconductors play a crucial role in spintronic devices, enabling effective control of electron spin over charge. This study explores their unique properties, ongoing advancements in spin control, and potential integration into next-generation semiconductor technologies.

physics.app-ph↗

arXiv2023

Theoretical Study of the Structural, Electronic, Mechanical, and Optical of Transition Metal (Mn, Co, and Ni) Doped FrGeI3 Perovskites

Emergence of inorganic metal halide perovskites as multifunctional optoelectronic materials are due to their exceptional tunability in optoelectronic properties. This study sought to enhance the physical and mechanical properties of lead-free FrGeI3 perovskites by introducing transition metal dopants (Mn, Co, and Ni). First-principle calculations based density functional theory (DFT) have been utilized to illustrate the impact of transition-metal doping on the structural, electronic, and light-matter interaction properties of FrGeI3. The study found that transition metal doping in FrGeI3 perovskites leads to an increase in the electronic bandgap leading to semiconducting behavior after phase stability confirmation. Enhanced optical and mechanical properties suggest wide industrial applications in optoelectronics to biomedical area. This study provides a sound understanding of the underlying mechanisms of transition metal doping in Fr-contained halide perovskites, which could pave the way to the headway of new optoelectronic and biomedical devices based on these materials.

cond-mat.mtrl-sci↗

arXiv2023

First-principles Studies on Structural, Electronic, Optical and Mechanical Properties of Inorganic CS2NaTlX6 (X = F, Cl, Br) Double Halide Perovskites

The structural, electrical, optical, and mechanical characteristics of the lead-free halide double perovskites Cs2NaTlX6 X = F, Cl, Br are calculated by utilizing PBE functional within generalized gradient approximation GGA under the context of density functional theory DFT.The structural properties such as lattice parameter, cell volume, total energy, bulk modulus, pressure derivative, and tolerance factor are computed at equilibrium.The electronic density of states reveals the semiconducting nature of the compound and the band structure exhibits the nature of the band gap to be direct.HSE06 functional is introduced to correct the underestimated band gap as obtained in the GGA-PBE functional.The real and imaginary components of the dielectric function, absorption coefficient, energy loss function, reflectivity, refractive index, and extinction coefficient are analyzed and explained by electronic structures.

cond-mat.mtrl-sci↗

arXiv2023

Multi-objective Optimization: A Case Study

The aim of this literature is to illustrate the application of multi-objective optimization routines through a case study of face milling operation. For this purpose, the face milling operation is designed as a multi-objective optimization problem and then solved to obtain optimum values for the machining parameters - cutting speed (Vc), feed rate (fz) and depth of cut (t) using the optimization routines. The formulated problem of face milling operation includes two conflicting objectives - to maximize Material Removal Rate (MRR) and to minimize surface roughness (Ra). Among various multi-objective optimization routines, five of them namely Global Criterion Method, Lexicographic Method, Weighted Sum Method, Epsilon Constraint Method and Genetic Algorithm are used in this literature. The outcomes of these multi-objective optimization routines are then compared to reflect their relative attractiveness.

math.OC↗

arXiv2022

Investigation of Minerals Using Hyperspectral Satellite Imagery in Bangladesh

Mineral identification using remote sensing technologies is becoming more dominant in this field since it saves time by demonstrating a more effective way for land resources survey. In such remote sensing technologies, hyperspectral remote sensing (HSRS) technology has increased gradually for its efficient manner. This technology is usually used from an airborne platform, i.e., satellite. Hence, satellite imagery remote sensing technology is now more capable of providing accuracy in mineral identification, and mapping. Hyperspectral satellite imagery can identify minerals more accurately compared to traditional technologies in remote sensing by constructing a complete reflectance of the spectrum from each pixel with its advanced imaging sensor. Bangladesh is a developing country with an area of 1,50,000 square kilometers located in Southeast Asia. Though it is a small country, it is enriched with several mineral resources through rivers, forests, hills, and the Bay of Bengal. In this study, hyperspectral imaging technology is employed on some major identical areas (Maheshkhali, Netrokona, Panchagarh, and Patuakhali) of Bangladesh to identify minerals there. As there are no studies done in Bangladesh using hyperspectral imaging yet, it is a good opportunity to explore the potentiality of HS imagery in this field. In this study, the FLAASH (Fast Line-of-sight Atmospheric Analysis) module with necessary parameter settings is used to filter the data, and finally, mineral identification is done by the spectral matched filtering method. Our investigation resulted in finding some potential minerals in those areas including Stariolite, Diasphore, Zircon, Alunite, Quartz, and so on. This indicates that there still is enormous potential for further exploration of minerals in Bangladesh by Hyperspectral Satellite Imagery.

eess.IV↗

arXiv2022

Incorporating Multi-Agent Systems Technology in Power and Energy Systems of Bangladesh: A Feasibility Study

The power sector of Bangladesh is presently experiencing essential changes as demand for power services is increasing with rising population and economic development. With a gradual shift from a rigidly centralized structure to a more decentralized and fluid setup, fundamentally because of the enormous advancement of distributed renewable energy sources, the future power system of the nation requires new control strategies to work efficiently and sustainably in the face of evolving conditions and constraints. Multi-Agent Systems (MAS) technology has attributes that meet these prerequisites of modern power systems and has been shown to be effective in dealing with its distributed and complex nature. This is a literature-based feasibility study to explore whether MAS technology is suited to be applied in the context of Bangladesh. For this preliminary paper, we look at the topic from a holistic perspective and conduct a meta-review to curate common applications of Multi-Agent System-based concepts, tools and algorithms on the power and energy sector. We also identify the top challenges of this domain in Bangladesh and connect the potential MAS-based solutions to address each challenge. Our qualitative assessment is motivated to provide a starting point for local researchers eager to experiment with MAS technology for application in Bangladesh.

eess.SY↗

arXiv2022

Structural, elastic and optoelectronic properties of inorganic cubic FrBX3 (B = Ge, Sn; X = Cl, Br, I) perovskite: the density functional theory approach

Inorganic metal-halide cubic perovskite semiconductors have become more popular in industrial applications of photovoltaic and optoelectronic devices. Among various perovskites, lead-free materials are currently most explored due to their non-toxic effect on the environment. In this study, the structural, electronic, optical, and mechanical properties of lead-free cubic perovskite materials FrBX3 (B = Ge, Sn; X = Cl, Br, I) are investigated through first-principles density-functional theory (DFT) calculations. These materials are found to exhibit semiconducting behavior with direct bandgap energy and mechanical phase stability. The observed variation in the bandgap is explained based on the substitutions of cations and anions sitting over B and X-sites of the FrBX3 compounds. The high absorption coefficient, low reflectivity, and high optical conductivity make these materials suitable for photovoltaic and other optoelectronic device applications. It is observed that the material containing Ge (germanium) in the B-site has higher optical absorption and conductivity than Sn containing materials. A systematic analysis of the electronic, optical, and mechanical properties suggests that among all the perovskite materials, FrGeI3 would be a potential candidate for optoelectronic applications. The radioactive element Fr-containing perovskite FrGeI3 may have applications in nuclear medicine and diagnosis such as X-ray imaging technology.

cond-mat.mtrl-sci↗

arXiv2021

Correcting Presbyopia with Autofocusing Liquid-Lens Eyeglasses

Presbyopia, an age-related ocular disorder, is characterized by the loss in the accommodative abilities of the human ocular system and afflicts more than 1.8 billion people world-wide. Conventional methods of correcting presbyopia fragment the field of vision, inherently resulting in significant vision impairment. We demonstrate the development, assembly and evaluation of autofocusing eyeglasses for restoration of accommodation without vision field loss. The adaptive optics eyeglasses consist of two variable-focus piezoelectric liquid lenses, a time-of-flight range sensor and low-power, dual microprocessor control electronics housed within an ergonomic frame. Patient-specific accommodation deficiency models were utilized to demonstrate a high-fidelity accommodative correction. Each accommodation correction calculation was performed in ~67 ms requiring 4.86 mJ of energy. The optical resolution of the system was 10.5 cycles/degree, featuring a restorative accommodative range of 4.3 D. This system can run for up to 19 hours between charge cycles and weighs ~132 g, allowing comfortable restoration of accommodative function

physics.med-ph↗