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Wide-bandgap semiconductors exhibit much larger energy bandgaps than traditional semiconductors such as silicon, rendering them very promising to be applied in the fields of electronics and optoelectronics. Prominent examples of semiconductors include SiC, GaN, ZnO, and diamond, which exhibit distinctive characteristics such as elevated mobility and thermal conductivity. These characteristics facilitate the operation of a wide range of devices, including energy-efficient bipolar junction transistors (BJTs) and metal-oxide-semiconductor field-effect transistors (MOSFETs), as well as high-frequency high-electron-mobility transistors (HEMTs) and optoelectronic components such as light-emitting diodes (LEDs) and lasers. These semiconductors are used in building integrated circuits (ICs) to facilitate the operation of power electronics, computer devices, RF systems, and other optoelectronic advancements. These breakthroughs include various applications such as imaging, optical communication, and sensing. Among them, the field of power electronics has witnessed tremendous progress in recent years with the development of wide bandgap (WBG) semiconductor devices, which is capable of switching large currents and voltages rapidly with low losses. However, it has been proven challenging to integrate these devices with silicon complementary metal oxide semiconductor (CMOS) logic circuits required for complex control functions. The monolithic integration of silicon CMOS with WBG devices increases the complexity of fabricating monolithically integrated smart integrated circuits (ICs). This review article proposes implementing CMOS logic directly on the WBG platform as a solution. However, achieving the CMOS functionalities with the adoption of WBG materials still remains a significant hurdle. This article summarizes the research progress in the fabrication of integrated circuits adopting various WBG materials ranging from SiC to diamond, with the goal of building future smart power ICs.

In the pursuit for scalable quantum processors, significant effort has been devoted to the development of cryogenic classical hardware for the control and readout of a growing number of qubits. The current work presented a novel approach called impedancemetry that is suitable for measuring the quantum capacitance of semiconductor qubits connected to a resonant LC-circuit. The impedancemetry circuit exploits the integration of a complementary metal-oxide-semiconductor (CMOS) active inductor in the resonator with tunable resonance frequency and quality factor, enabling the optimization of readout sensitivity for quantum devices. The realized cryogenic circuit allows fast impedance detection with a measured capacitance resolution down to 10 aF and an input-referred noise of 3.7 aF/$\sqrt{Hz}$. At 4.2 K, the power consumption of the active inductor amounts to 120 μW, with an additional dissipation for on-chip current excitation (0.15 μW) and voltage amplification (2.9 mW) of the impedance measurement. Compared to the commonly used schemes based on dispersive RF reflectometry which require millimeter-scale passive inductors, the circuit exhibits a notably reduced footprint (50 μm × 60 μm), facilitating its integration in a scalable quantum-classical architecture. The impedancemetry method has been applied at 4.2 K to the detection of quantum effects in the gate capacitance of on-chip nanometric CMOS transistors that are individually addressed via multiplexing.

This paper demonstrated the fabrication, characterization, data-driven modeling, and practical application of a 1D SnO₂ nanofiber-based memristor, in which a 1D SnO₂ active layer was sandwiched between silver (Ag) and aluminum (Al) electrodes. This device yielded a very high R_OFF : R_ON of ∼10⁴ (I_ON : I_OFF of ∼10⁵) with an excellent activation slope of 10 mV/dec, low set voltage of V_SET ∼ 1.14 V and good repeatability. This paper physically explained the conduction mechanism in the layered SnO₂ nanofiber-based memristor. The conductive network was composed of nanofibers that play a vital role in the memristive action, since more conductive paths could facilitate the hopping of electron carriers. Energy band structures experimentally extracted with the adoption of ultraviolet photoelectron spectroscopy strongly support the claims reported in this paper. An machine learning (ML)–assisted, data-driven model of the fabricated memristor was also developed employing different popular algorithms such as polynomial regression, support vector regression, k nearest neighbors, and artificial neural network (ANN) to model the data of the fabricated device. We have proposed two types of ANN models (type I and type II) algorithms, illustrated with a detailed flowchart, to model the fabricated memristor. Benchmarking with standard ML techniques shows that the type II ANN algorithm provides the best mean absolute percentage error of 0.0175 with a 98% R² score. The proposed data-driven model was further validated with the characterization results of similar new memristors fabricated adopting the same fabrication recipe, which gave satisfactory predictions. Lastly, the ANN type II model was applied to design and implement simple AND & OR logic functionalities adopting the fabricated memristors with expected, near-ideal characteristics.

The mitigation of dephasing poses a significant challenge to improving the performance of error-prone superconducting quantum computing systems. Here, the dephasing of a transmon qubit in a dispersive readout regime was investigated by adopting a Josephson traveling-wave parametric amplifier as the preamplifier. Our findings reveal that the potent pump leakage from the preamplifier may lead to severe dephasing. This could be attributed to a mixture of measurement-induced dephasing, ac Stark effect, and heating. It is showed that pulse-mode readout is a promising measurement scheme to mitigate qubit dephasing while minimizing the need for bulky circulators. Our work provides key insights into mitigating decoherence from microwave-pumped preamplifiers, which will be critical for advancing large-scale quantum computers.

The multi-Fano interference, which is obtained through the simultaneous acquisition of bright and dark states in different phase transitions of Eu³⁺ : BiPO₄ (7 : 1, 6 : 1, 1 : 1, and 0.5 : 1) and Eu³⁺ : NaYF₄ (1 : 1/4) crystals, were reported in this work. Multidressed spontaneous four-wave mixing and multidressed fluorescence (multiorder) were adopted to optimize the strong photon–phonon nested dressing effect, which results in more obvious multi-Fano interference. Firstly, the multi-Fano is produced through interference in continuous and multibound states. Secondly, five multi-Fano dips are originated from the nested five dressings (one photon and four phonons) under symmetrical splitting of ⁷F₁ energy level. It is found that the pure H-phase (0.5 : 1) sample exhibits the strongest photon–phonon dressed effect (five Fano dips). Further, high-order non-Hermitian exceptional points in multi-Fano interference were investigated by adjusting the ratio of Rabi frequency to dephase rate through nested photon and phonon dressing. The experimental results are validated by theoretical simulations, which may be applied to designing optoelectronic devices such as non-Hermitian multi-Fano interferences (multichannel) router.

With major signal analytical elements situated away from the measurement environment, extended gate (EG) ion-sensitive field-effect transistors (ISFETs) offer prospects for whole chip circuit design and system integration of chemical sensors. In this work, a highly sensitive and power-efficient ISFET was proposed based on a metal–ferroelectric–insulator gate stack with negative capacitance–induced super-steep subthreshold swing and ferroelectric memory function. Along with a remotely connected EG electrode, the architecture facilitates diverse sensing functions for future establishment of smart biochemical sensor platforms.

Moore's Law has been the driving force behind the semiconductor industry for several decades, but as silicon-based transistors approach their physical limits, researchers are searching for new materials to sustain this exponential growth. Two-dimensional transition metal dichalcogenides (TMDs), with their atomically thin structure and enticing physical properties, have emerged as the most promising candidates for downsizing and improving device integration. Emboldened by the direction of achieving large-area and high-quality TMDs growth, wafer-scale TMDs growth strategies have been continuously developed, suggesting that TMDs are poised to become a new platform for next-generation electronic devices. In this review, advanced synthesis routes and inherent properties of wafer-scale TMDs were critically assessed. In addition, the performance in electronic devices was also discussed, providing an outlook on the opportunities and challenges that lie ahead in their development.

High-sensitivity mass sensors under ambient conditions are essential in various fields such as biological research, gas sensing and environmental monitoring. In the current work, a phonon lasing enhanced mass sensor was proposed based on an optomechanical crystal cavity under ambient conditions. The phonon lasing was harnessed to achieve ultra-high resolution since it resulted in an extremely narrow mechanical linewidth (less than 10 kHz). Masses with different weights were deposited on the cavity, it is predicted that the maximum resolution for mass sensing can be 65 ± 19 zg, which approaches the mass order of a protein and an oligonucleotide. This implies the potential application of the proposed method in the biomedical fields such as oligonucleotide drug delivery area and the Human Proteome Project.

Cryogenic electronics refers to the devices and circuits operated at cryogenic temperatures (below 123.15 K), which are made from a variety of materials such as insulators, conductors, semiconductors, superconductors and topological materials. The cryogenic electronics are endowed with some unique advantages that cannot be realized in room temperature, including high computing speed, high power performance and so on. Choosing the appropriate refrigeration technology is critical for achieving the best performance of the cryogenic electronics. In this review, the cryogenic technology was divided into non-optical refrigeration and optical refrigeration, where non-optical refrigeration technologies are relatively conventional refrigeration technologies, while optical refrigeration is an emerging research field for the cooling of the chips. In the current work, the fundamental principles, applications and development prospects of the non-optical refrigeration was introduced, also the research history, fundamental principles, existing problems and application prospects of the optical refrigeration was thoroughly reviewed.

In the past few decades, circuits based on gallium nitride high electron mobility transistor (GaN HEMT) have demonstrated exceptional potential in a wide range of high-power and high-frequency applications, such as the new generation mobile communications, object detection and consumer electronics, etc. As a critical intermediary between GaN HEMT devices and circuit-level applications, GaN HEMT large-signal models play a pivotal role in the design, application and development of GaN HEMT devices and circuits. This review provides an in-depth examination of the advancements in GaN HEMT large-signal modeling in recent decades. Detailed and comprehensive coverage of various aspects of GaN HEMT large-signal model was offered, including large-signal measurement setups, classical formulation methods, model classification and non-ideal effects, etc. In order to better serve follow-up researches, this review also explored potential future directions for the development of GaN HEMT large-signal modeling.