Temporal response is an important factor limiting the performance of two-dimensional (2D) material photodetectors. The deep trap states caused by intrinsic defects are the main factor to prolong the response time. In this work, it is demonstrated that the trap states in 2D molybdenum disulfide (MoS) can be efficiently modulated by defect engineering through mild oxygen plasma treatment. The response time of the few-layer MoS photodetector is accelerated by 2-3 orders of magnitude, which is mainly attributed to the deep trap states that can be easily filled when O or oxygen ions are chemically bonded with MoS at sulfur vacancies (SV) sites. We characterized the defect engineering of plasma-exposed MoS by Raman, PL and electric properties. Under the optimal processing conditions of 30 W, 50 Pa and 30 s, we found 30-fold enhancements in photoluminescence (PL) intensity and a nearly 2-fold enhancement in carrier field-effect mobility, while the rise and fall response times reached 110 ms and 55 ms, respectively, at the illumination wavelength of 532 nm. This work would, therefore, offer a practical route to improve the performance of 2D dichalcogenide-based devices for future consideration in optoelectronics research.
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http://dx.doi.org/10.3390/nano12081365 | DOI Listing |
PeerJ
January 2025
School of Biological, Environmental, and Earth Sciences, University of Southern Mississippi, Hattiesburg, MS, United States.
Background: Four species support recreational and commercial fisheries along the U.S. Atlantic Ocean and the Gulf of Mexico, with the Gulf of Mexico stock being overfished for over three decades.
View Article and Find Full Text PDFNat Commun
January 2025
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, PR China.
All-perovskite tandem solar cells (APTSCs) offer the potential to surpass the Shockley-Queisser limit of single-junction solar cells at low cost. However, high-performance APTSCs contain unstable methylammonium (MA) cation in the tin-lead (Sn-Pb) narrow bandgap subcells. Currently, MA-free Sn-Pb perovskite solar cells (PSCs) show lower performance compared with their MA-containing counterparts.
View Article and Find Full Text PDFEnviron Res
January 2025
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada; School of the Environment, University of Toronto, Toronto, Ontario, Canada. Electronic address:
Growing epidemiological studies indicate a significant fraction of asthma cases can be attributed to traffic-related air pollution (TRAP). Zero emission vehicle (ZEV) mandates-one of the most forward-looking climate policies in the United States-aim to reduce TRAP by mandating automakers to sell a certain fraction of Electric Vehicles (EVs) annually; however, their public health benefits are largely unknown. We conduct the screening step of the health impact assessment (HIA) of real-world EV sales to estimate the impact of ZEV mandates in reducing childhood asthma.
View Article and Find Full Text PDFJ Am Chem Soc
January 2025
Department of Chemistry, University of Southern California, Los Angeles, California 90089, United States.
The polycrystalline nature of perovskites, stemming from their facile solution-based fabrication, leads to a high density of grain boundaries (GBs) and point defects. However, the impact of GBs on perovskite performance remains uncertain, with contradictory statements found in the literature. We developed a machine learning force field, sampled GB structures on a nanosecond time scale, and performed nonadiabatic (NA) molecular dynamics simulations of charge carrier trapping and recombination in stoichiometric and doped GBs.
View Article and Find Full Text PDFSci Adv
January 2025
Center for Quantum Information, Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, PR China.
Quantum simulators with hundreds of qubits and engineerable Hamiltonians have the potential to explore quantum many-body models that are intractable for classical computers. However, learning the simulated Hamiltonian, a prerequisite for any quantitative applications of a quantum simulator, remains an outstanding challenge due to the fast increasing time cost with the qubit number and the lack of high-fidelity universal gate operations in the noisy intermediate-scale quantum era. Here, we demonstrate the Hamiltonian learning of a two-dimensional ion trap quantum simulator with 300 qubits.
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