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Two-dimensional materials and their heterostructures have thus far been identified as leading candidates for nanoelectronics owing to the near-atom thickness, superior electrostatic control, and adjustable device architecture. These characteristics are indeed advantageous for neuro-inspired computing hardware where precise programming is strongly required. However, its successful demonstration fully utilizing all of the given benefits remains to be further developed. Herein, we present van der Waals (vdW) integrated synaptic transistors with multistacked floating gates, which are reconfigured upon surface oxidation. When compared with a conventional device structure with a single floating gate, our double-floating-gate (DFG) device exhibits better nonvolatile memory performance, including a large memory window (>100 V), high on–off current ratio (∼107), relatively long retention time (>5000 s), and satisfactory cyclic endurance (>500 cycles), all of which can be attributed to its increased charge-storage capacity and spatial redistribution. This facilitates highly effective modulation of trapped charge density with a large dynamic range. Consequently, the DFG transistor exhibits an improved weight update profile in long-term potentiation/depression synaptic behavior for nearly ideal classification accuracies of up to 96.12% (MNIST) and 81.68% (Fashion-MNIST). Our work adds a powerful option to vdW-bonded device structures for highly efficient neuromorphic computing.

Copper (Cu) oxide compounds (CuxO), which include cupric (CuO) and cuprous (Cu2O) oxide, have been recognized as a promising p-channel material with useful photovoltaic properties and superior thermal conductivity. Typically, deposition methods or thermal oxidation can be used to obtain CuxO. However, these processes are difficult to apply to flexible substrates because plastics have a comparatively low glass transition temperature. Also, additional patterning steps are needed to fabricate applications. In this work, we fabricated a metal–semiconductor–metal photodetector using laser-induced oxidation of thin Cu films under ambient conditions. Raman spectroscopy, scanning electron microscopy–energy-dispersive X-ray spectroscopy, and atomic force microscopy were used to study the composition and morphology of our devices. Moreover, the photoresponse of this device is reported herein. We performed an in-depth analysis of the relationship between the channel size and number of carriers using scanning photocurrent microscopy. The carrier transport behaviors were identified; the photocurrent decreased as the length and width of the channel increased. Furthermore, we verified the suitability of the device as a flexible photodetector using a variety of bending tests. Our in-depth analysis of this Cu-based flexible photodetector could play an important role in understanding the mechanisms of other flexible photovoltaic applications.

Owing to India's success, offshore software outsourcing attracts much attention from developing countries as a strategic industry for economic development. Vietnam wants to follow the Indian way of development in its software industry. FPT Software is one of the top performers among software companies in Vietnam. This paper aims to investigate the success factors of the largest offshore software outsourcing company in Vietnam. We argue the key success factor of FPT Software is its learning capabilities. Based on the theories of organizational learning, we propose one aspect of organizational learning processes, i.e., knowledge acquisition, as a key to explaining how FPT Software became a fast learner. While discussing the significance of this process in the company's organizational learning, we identify and discuss the roles played by actors in the case including the CEO, Japanese clients, Indian and Chinese competitors. In conclusion, we contend organizational learning is a key success factor of developing offshore software outsourcing businesses.

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