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Zhenyu Wang

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Related publications (7)

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Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Zhenyu Wang

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

EPFL2024

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Defects in solids are unavoidable and can create complex electronic states that can significantly influence the electrical and optical properties of semiconductors. With the rapid progress in the integration of 2D semiconductors in practical devices, it is ...

2023

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Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector ...

2023

Stable Al 2 O 3 Encapsulation of MoS 2 ‐FETs Enabled by CVD Grown h‐BN

Aleksandra Radenovic, Andras Kis, Zhenyu Wang

Molybdenum disulfide (MoS2) has great potential as a two-dimensional semiconductor for electronic and optoelectronic application, but its high sensitivity to environmental adsorbents and charge transfer from neighboring dielectrics can lead to device varia ...

2022

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Aleksandra Radenovic, Andras Kis, Mukesh Kumar Tripathi, Zhenyu Wang, Guilherme Migliato Marega

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

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Metallic two-dimensional (2D) transition metal dichalcogenides (TMDCs) are attracting great attention because of their interesting low-temperature properties such as superconductivity, magnetism, and charge density waves (CDW). However, further studies and ...

2021

Logic-in-memory based on an atomically thin semiconductor

Aleksandra Radenovic, Andras Kis, Mukesh Kumar Tripathi, Zhenyu Wang, Ahmet Avsar, Yanfei Zhao, Guilherme Migliato Marega

The growing importance of applications based on machine learning is driving the need to develop dedicated, energy-efficient electronic hardware. Compared with von Neumann architectures, which have separate processing and storage units, brain-inspired in-me ...

2020