PolyU develops quantum-tunnelling field-effect transistor to overcome barriers to integrated-circuit chip development
The next generation of microelectronics relies on radical improvements in transistor switching performance to advance computing power. However, conventional semiconductor technology has hit a physical limit known as the "Boltzmann tyranny," which restricts the energy efficiency of traditional transistors and stalls progress in high-performance electronics. To address this key bottleneck, a research team at The Hong Kong Polytechnic University (PolyU) has engineered a novel tunnelling field-effect transistor (TFET) utilising two-dimensional (2D) nanomaterials. The breakthrough brings this long-awaited experimental technology closer to commercial reality, offering a fundamental building block for energy-efficient computing and next-generation artificial intelligence (AI) chips.
The research was led by Prof. Jianhua HAO, Head of the Department of Physics and Materials, Chair Professor of Materials Physics and Devices and Associate Director of PolyU-Wuhan Technology and Innovation Research Institute at PolyU, in collaboration with researchers from the National University of Singapore, The Hong Kong University of Science and Technology, Peking University, and the Singapore University of Technology and Design. The landmark findings have been published in the prestigious international scientific journal Science.
Integrated circuits (ICs), composed of transistors switching between ON and OFF states, form the foundation of modern computing. Conventional complementary metal–oxide–semiconductor field-effect transistors (MOSFETs) rely on thermionic emission of electrical charges over a barrier, driven by the gating voltage, the minimum of which is just 60 millivolts (mV). However, the notorious Boltzmann limit, or “Boltzmann tyranny”, makes subthreshold swing (SS, a measure of switching barrier) values below 60 mV decade⁻¹ at room temperature a physical impossibility for MOSFETs, putting the brakes on further progress in high-performance electronics.
Prof. Jianhua Hao said, “The International Roadmap for Devices and Systems (IRDS) has identified TFETs as the most promising alternative to MOSFETs. By replacing thermionic emission with quantum tunnelling, our 2D heterostructure transistor breaks through this 60 mV decade⁻¹ boundary, overcoming the standard MOSFET limit. Our TFET paves the way for ultra-low-power, high-performance ICs essential for emerging AI chips and advanced semiconductor applications.”
To solve the performance limitations of previous TFET designs, Prof. Hao’s team created ultra-thin heterostructure of 2D bismuth (Bi) and indium selenide (InSe) alternating layers using pulsed laser deposition (PLD). By exercising precise control over the layer structure at nanoscale, the normally semi-metallic bismuth transforms into a semiconductor in 2D form, creating ideal energy band alignment for charge carriers to tunnel efficiently into InSe through quantum tunnelling mechanism.
The resulting Bi/InSe TFET achieved SS values well below the 60 mV decade⁻¹ thermionic limit across six orders of magnitude of current switching. Operating at room temperature on standard centimetre-scale silicon substrates, the device required a gate-voltage range of only 160 mV—far lower than the 800 mV required by advanced MOSFETs.
Crucially, the device resolved a long-standing challenge in experimental TFETs by delivering a high output current of up to several microamps per micrometre (μA μm⁻¹) alongside an exceptionally high ON/OFF current ratio. High output current is essential for driving multiple downstream logic gates (fan-out), demonstrating diminished circuit-delay, and ensuring compatibility with and even generational upgrade for the existing IC chips.
The study also demonstrates the practical viability of PLD for high-precision, wafer-scale manufacturing of 2D materials that appreciated for future transistors with ultra-short channel lengths. Given its seamless integration capability with traditional silicon-based manufacturing processes, this breakthrough provides a scalable roadmap for energy-efficient microchips and specialised hardware powering AI applications.
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