arXiv subjects

Anas Abutaha

Publications and source records attributed to Anas Abutaha.

4 recordsLinked to original sources

arXiv2026

Pressure-Tuned Competing Electronic States in Layered Tellurides

Layered transition-metal dichalcogenides (TMDs) host competing electronic states that can be tuned by external perturbations, providing a platform to explore the interplay between disorder, electronic structure, and quantum transport. Here we investigate magnetotransport in bulk semiconducting 2H-MoTe2 under hydrostatic pressure. At ambient pressure, transport evolves from high-temperature metallic behavior into activated conduction and ultimately a strongly localized variable-range hopping regime, accompanied by a pronounced magnetotransport anomaly near 45 K and large, nonsaturating magnetoresistance extending up to an unprecedented field of 60 T in semiconducting 2H-MoTe2. Under compression to 15.6 GPa, the insulating state is rapidly suppressed and a low-resistivity regime emerges in which quantum interference dominates, exhibiting a crossover from weak antilocalization (WAL) to weak localization (WL) at low temperatures. A physically motivated phenomenological description captures the magnetoresistance across these regimes and yields a characteristic electronic length scale that remains comparable across the localized and quantum-interference regimes. First-principles calculations reveal a continuous pressure-driven collapse of the bandgap into a semimetallic electronic structure. These results establish a unified picture of pressure-tuned transport spanning hopping and quantum-coherent regimes.

cond-mat.str-el↗

arXiv2025

Pressure-Tuned Magnetism and Bandgap Modulation in Layered Fe-Doped CrCl3

We explore the structural, magnetic, vibrational and optical band gap properties under varying pressures. By integrating first-principles calculations with experimental techniques, including Raman spectroscopy, photoluminescence (PL), uniaxial pressure studies (thermal expansion), and magnetization measurements, we unveil the intricate pressure-induced transformations in Fe-doped CrCl3, shedding light on its structural, electronic, and magnetic evolution. At ambient pressure, Raman spectra confirm all expected Raman-active modes, which exhibit blue shifts with increasing pressure. The PL measurements demonstrate an optical bandgap of 1.48 eV at ~0.6 GPa, with a progressive increase in the bandgap under pressure, transitioning slower above 6 GPa due to an isostructural phase transition. Magnetization results under pressure shows two competing magnetic components (FM and AFM) at ambient conditions, where at the lowest temperature and applied field, the FM component dominates. The presence of competing FM and AFM energy scales is confirmed by Grueneisen analysis of the thermal expansion and their uniaxial pressure dependence is determined. The experimental findings agree with theoretical results based on Density functional theory (DFT). In the experiments, we observe a pressure-enhanced ferromagnetic interlayer coupling that is followed by the stabilization of antiferromagnetic ordering, due to weakened direct interlayer interactions. Above 1.2 GPa the FM component of the magnetism is gone in the experimental observations, which is also in good agreement with DFT based theory. The findings reported here underscore the potential of CrCl3 for use in pressure-tunable magnetic and optoelectronic applications, where, e.g., the delicate balance between FM and AFM configurations could have potential for sensor applications.

cond-mat.mtrl-sci↗

arXiv2021

Electronic transport descriptors for the rapid screening of thermoelectric materials

The discovery of novel materials for thermoelectric energy conversion has potential to be accelerated by data-driven screening combined with high-throughput calculations. One way to increase the efficacy of successfully choosing a candidate material is through its evaluation using transport descriptors. Using a data-driven screening, we selected 12 potential candidates in the trigonal ABX2 family, followed by charge transport property simulations from first principles. The results suggest that carrier scattering processes in these materials are dominated by ionised impurities and polar optical phonons, contrary to the oft-assumed acoustic-phonon-dominated scattering. Combined with calculations of thermal conductivity based on three-phonon scattering, we predict p-type AgBiS2 and TlBiTe2 as potential high-performance thermoelectrics in the intermediate temperature range for low grade waste heat harvesting, with a predicted zT above 1 at 500 K. Using these data, we further derive ground-state transport descriptors for the carrier mobility and the thermoelectric power factor. In addition to low carrier mass, high dielectric constant was found to be an important factor towards high carrier mobility. A quadratic correlation between dielectric constant and transport performance was established and further validated with literature. Looking ahead, dielectric constant can potentially be exploited as an independent tuning knob for improving the thermoelectric performance.

cond-mat.mtrl-sci↗

arXiv2020

Machine learning and high-throughput robust design of P3HT-CNT composite thin films for high electrical conductivity

Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that machine learning, combined with multi-labeled datasets, can additionally be used for scientific understanding and hypothesis testing. We introduce an automated flow system with high-throughput drop-casting for thin film preparation, followed by fast characterization of optical and electrical properties, with the capability to complete one cycle of learning of fully labeled ~160 samples in a single day. We combine regio-regular poly-3-hexylthiophene with various carbon nanotubes to achieve electrical conductivities as high as 1200 S/cm. Interestingly, a non-intuitive local optimum emerges when 10% of double-walled carbon nanotubes are added with long single wall carbon nanotubes, where the conductivity is seen to be as high as 700 S/cm, which we subsequently explain with high fidelity optical characterization. Employing dataset resampling strategies and graph-based regressions allows us to account for experimental cost and uncertainty estimation of correlated multi-outputs, and supports the proving of the hypothesis linking charge delocalization to electrical conductivity. We therefore present a robust machine-learning driven high-throughput experimental scheme that can be applied to optimize and understand properties of composites, or hybrid organic-inorganic materials.

physics.app-ph↗