Aggregation-induced negative differential resistance in graphene oxide quantum dots
文献信息
Sonia Sharma, Chieh-An Cheng, Svette Reina Merden Santiago, Denice N. Feria, Chi-Tsu Yuan, Sheng-Hsiung Chang, Tai-Yuan Lin, Ji-Lin Shen
Negative differential resistance (NDR) devices have attracted considerable interest due to their potential applications in switches, memory devices, and analog-to-digital converters. Modulation of the NDR is an essential issue for the development of NDR-based devices. In this study, we successfully synthesized graphene oxide quantum dots (GOQDs) using graphene oxide, cysteine, and H2O2. The current–voltage characteristics of the GOQDs exhibit a clear NDR in the ambient environment at room temperature. A peak-to-valley ratio as high as 4.7 has been achieved under an applied voltage sweep from −6 to 6 V. The behavior of the NDR and its corresponding peak-to-valley ratio can be controlled by adjusting the range of applied voltages, air pressure, and relative humidity. Also, the NDR is sensitive to the the concentration of H2O2 added in the synthesis. The charge carrier injection through the trapping states, induced by the GOQD aggregation, could be responsible for the NDR behavior in GOQDs.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.














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