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Abstract The tuning of the Fermi level in tin telluride, a topological crystalline insulator, is essential for accessing its unique surface states and optimizing its electronic properties for applications such as spintronics and quantum computing. In this study, we demonstrate that the Fermi level in tin telluride can be effectively modulated by controlling the tin concentration during chemical vapor deposition synthesis. By introducing tin-rich conditions, we observed a blue shift in the x-ray photoelectron spectroscopy core-level peaks of both tin and tellurium, indicating an upward shift in the Fermi level. This shift is corroborated by a decrease in work function values measured via ultraviolet photoelectron spectroscopy, confirming the suppression of Sn vacancies. Our findings provide a low-cost, scalable method to achieve tunable Fermi levels in tin telluride, offering a significant advancement in the development of materials with tailored electronic properties for next-generation technological applications. 

Abstract Ensemble density functional theory (EDFT) is a generalization of ground-state DFT, which is based on an exact formal theory of finite collections of a system’s ground and excited states. EDFT in various forms has been shown to improve the accuracy of calculated energy level differences in isolated model systems, atoms, and molecules, but it is not yet clear how EDFT could be used to calculate band gaps for periodic systems. We extend the application of EDFT toward periodic systems by estimating the thermodynamic limit with increasingly large finite one-dimensional ‘particle in a box’ systems, which approach the uniform electron gas (UEG). Using ensemble-generalized Hartree and local spin density approximation exchange-correlation functionals, we find that corrections go to zero in the infinite limit, as expected for a metallic system. However, there is a correction to the effective mass, with results comparable to other calculations on 1D, 2D, and 3D UEGs, which indicates promise for non-trivial results from EDFT on periodic systems. 

Water quality monitoring is essential for identifying risks to environmental and human health. Nitrate monitoring is of particular importance, as its anthropogenic point and nonpoint sources are common globally and have deleterious effects on water quality and usability as well as aquatic ecosystem health. Standard methods for assessing nitrate concentrations in water generally involve laboratory techniques, as methods available for field testing face significant tradeoffs between cost, precision, and portability. Given its relatively ubiquitous nature and the widespread regulation of nitrate pollution, it is a prime target for sensor development. The growing field of nanomaterials (e.g., nanoparticles, nanotubes, and 2-dimensional materials) offers the potential to eliminate these tradeoffs through a new generation of field-ready nitrate sensors. However, transitioning nano-sensors from the lab to the field remains challenging. In this perspective we examine the challenges of lab-to-field transition of nano-sensors for nitrate, highlighting the importance of a user-centered design approach under the framework of FOCUS (form factor, operational robustness, cost, user interface, and sensitivity). 

A system of tunnel-coupled quantum dots is considered in the presence of an applied electric field. Given the measurements of differences between ground state and excited state energy levels as the electric field is varied, we seek to recover the quantum Hamiltonians that describe this system. We formulate this as a parameterized inverse eigenvalue problem and develop algebraic and computational methods for solving for parameters to represent these Hamiltonians. The results demonstrate that this approach is highly precise even when there is error present within the measurements. This theory could aid in the design of high resolution tunable quantum sensors.