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Zhang, Zheng

Publications and source records attributed to Zhang, Zheng.

Structural and physical properties of two distinct 2D lead halides with intercalated Cu( II )

Transition metal cation intercalation between the layers of two-dimensional (2D) metal halides is an underexplored research area. In this work we focus on the synthesis and physical property characterizations of two layered hybrid lead halides: a new compound [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 and the previously reported [Cu(O 2 C–(CH 2 ) 3 –NH 3 ) 2 ]PbBr 4 . These compounds exhibit 2D layered crystal structures with incorporated Cu 2+ between the metal halide layers, which is achieved by combining Cu(II) and lead bromide with suitable amino acid precursors. The resultant [Cu(O 2 C–(CH 2 ) 3 –NH 3 ) 2 ]PbBr 4 adopts a 2D layered perovskite structure, whereas the new compound [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 crystallizes with a new structure type based on edge-sharing dodecahedral PbBr5O3 building blocks. [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 is a semiconductor with a bandgap of 3.25 eV. It shows anisotropic charge transport properties with a semiconductor resistivity of 1.44 × 10 10 Ω cm (measured along the a-axis) and 2.17 × 10 10 Ω cm (along the bc-plane), respectively. The fabricated prototype detector based on this material showed response to soft low-energy X-rays at 8 keV with a detector sensitivity of 1462.7 μCGy –1 cm –2 , indicating its potential application for ionizing radiation detection. Finally, these encouraging results are discussed together with the results from density functional theory calculations, optical, magnetic, and thermal property characterization experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Distributionally Robust Variational Quantum Algorithms With Shifted Noise

Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is the high sensitivity of quantum noise to environmental changes, and its propensity to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step towards improving the reliability of VQAs influenced by real-time noise.

97 MATHEMATICS AND COMPUTING