Behavior of gold-doped silicon substrate under small- and large-RF signal

In this paper, small- and large-signal performances of passive devices integrated on high-resistivity, trap-rich and gold-doped silicon wafers are presented and compared through measurements and simulations. The gold-doped silicon substrate was produced starting from standard silicon having a nominal resistivity of 56 cm. We show that the gold-doped substrate presents high effective resistivity and low losses suitable for RF applications. This has been demonstrated by measuring coplanar waveguides, crosstalk, inductors and band pass filter where we observed similar performances for small-signal measurements compared with trap-rich substrate. Large-signal measurements of gold-doped substrates show 60 dBm lower harmonic distortion than high-resistivity substrates, and 10 dB lower than trap-rich substrate at 0 V DC bias. However, a large DC bias dependence on the harmonic distortion induced by the gold-doped substrate is observed. This unexpected behavior is explained using the Fermi level localization in the silicon bandgap for the different DC bias conditions

Selection by current compliance of negative and positive bipolar resistive switching behaviour in ZrO_2−x/ZrO₂ bilayer memory

We report here a ZrO2−x /ZrO2-based bilayer resistive switching memory with unique properties that enables the selection of the switching mode by applying different electroforming current compliances. Two opposite polarity modes, positive bipolar and negative bipolar, correspond to the switching in the ZrO2 and ZrO2−x layer, respectively. The ZrO2 layer is proved to be responsible for the negative bipolar mode which is also observed in a ZrO2 single layer device. The oxygen deficient ZrO2−x layer plays the dominant role in the positive bipolar mode, which is exclusive to the bilayer memory. A systematic investigation of the ZrO2−x composition in the bilayer memory suggests that ZrO1.8 layer demonstrates optimum switching performance with low switching voltage, narrow switching voltage distribution and good cycling endurance. An excess of oxygen vacancies, beyond this composition, leads to a deterioration of switching properties. The formation and dissolution of the oxygen vacancy filament model has been proposed to explain both polarity switching behaviours and the improved properties in the bilayer positive bipolar mode are attributed to the confined oxygen vacancy filament size within the ZrO2−x layer

Selection by current compliance of negative and positive bipolar resistive switching behaviour in ZrO_2−x/ZrO₂ bilayer memory

We report here a ZrO2−x /ZrO2-based bilayer resistive switching memory with unique properties that enables the selection of the switching mode by applying different electroforming current compliances. Two opposite polarity modes, positive bipolar and negative bipolar, correspond to the switching in the ZrO2 and ZrO2−x layer, respectively. The ZrO2 layer is proved to be responsible for the negative bipolar mode which is also observed in a ZrO2 single layer device. The oxygen deficient ZrO2−x layer plays the dominant role in the positive bipolar mode, which is exclusive to the bilayer memory. A systematic investigation of the ZrO2−x composition in the bilayer memory suggests that ZrO1.8 layer demonstrates optimum switching performance with low switching voltage, narrow switching voltage distribution and good cycling endurance. An excess of oxygen vacancies, beyond this composition, leads to a deterioration of switching properties. The formation and dissolution of the oxygen vacancy filament model has been proposed to explain both polarity switching behaviours and the improved properties in the bilayer positive bipolar mode are attributed to the confined oxygen vacancy filament size within the ZrO2−x layer

Segmented thermoelectric generator modelling and optimization using artificial neural networks by iterative training

Renewable energy technologies are central to emissions reduction and essential to achieve net-zero emission. Segmented thermoelectric generators (STEG) facilitate more efficient thermal energy recovery over a large temperature gradient. However, the additional design complexity has introduced challenges in the modelling and optimization of its performance. In this work, an artificial neural network (ANN) has been applied to build accurate and fast forward modelling of the STEG. More importantly, we adopt an iterative method in the ANN training process to improve accuracy without increasing the dataset size. This approach strengthens the pro- portion of the high-power performance in the STEG training dataset. Without increasing the size of the training dataset, the relative prediction error over high-power STEG designs decreases from 0.06 to 0.02, representing a threefold improvement. Coupling with a genetic algorithm, the trained artificial neural networks can perform design optimization within 10 s for each operating condition. It is over 5,000 times faster than the optimization performed by the conventional finite element method. Such an accurate and fast modeller also allows mapping of the STEG power against different parameters. The modelling approach demonstrated in this work indicates its future application in designing and optimizing complex energy harvesting technologies

Reduction of Parasitic Capacitance in Vertical MOSFETs by Spacer Local Oxidation

Application of double gate or surround-gate vertical metal oxide semiconductor field effect transistors (MOSFETs) is hindered by the parasitic overlap capacitance associated with their oayout, which is considerably larger than for a lateral MOSFET on the same technology node. A simple self-aligned procfess has been developed to reduce the parasitic overlap capacitance in MOSFETs using nitride spacers on the sidewalls of the trench or pillar and a local oxidation. This will result in an oxide layer on all exposed planar surfaces, but no oxide layer on the protected vertical channel area of the pillar. The encroachment of the oxide on the side of the pillar is studied by transmission electron microscopy (TEM)which is used to calibrate the nitride viscosity in the process simulations. Surround gate vertical transistors incorporating the spacer oxidation have been fabricated, and these transistors show the integrity of the process and excellent subthreshold slope and drive current. The reduction in intrinsic capacitance is calculated to be a factor of three. Pillar capacitors with a more advanced process have been fabricated and the total measured capacitance is reduced by a factor of five compared with structures without the spacer oxidation. Device simulations confirm the measured reduction in capacitance

Reservoir computing using back-end-of-line SiC-based memristors

The increasing demand for intellectual computers that can efficiently process substantial amounts of data has resulted in the development of a wide range of nanoelectronics devices. Reservoir computing offers efficient temporal information processing capability with a low training cost. In this work, we demonstrate a back-end-of-line SiC-based memristor that exhibits short-term memory behaviour and is capable of encoding temporal signals. A physical reservoir computing system using our SiC-based memristor as the reservoir has been implemented. This physical reservoir computing system has been experimentally demonstrated to perform the task of pattern recognition. After training, our RC system has achieved 100% accuracy in classifying number patterns from 0 to 9 and demonstrated good robustness to noisy pixels. The results shown here indicate that our SiC-based memristor devices are strong contenders for potential applications in artificial intelligence, particularly in temporal and sequential data processing.</p

Passive thermal radiation control based on thermochromic W-doped VO2 metasurfaces

Radiative cooling becomes a popular research topic targeting an energy efficient solution for thermal management. Vanadium dioxide (VO2), as a thermochromic material, is able to switch optical property between dielectric and metallic states depending on its temperature. We present a passive thermal management solution through a VO2 based metasurface. Through a novel ALD process, the fabricated VO2 metasurface on polyimide substratehas a room-temperature transition and a high infrared emissivity of ~0.4

(Ba, Sr)(Ti, Mn)O3 Perovskite Films for Co-Planar Waveguide Tunable Microwave Phase Shifters

BaxSr1-xTiyMn1-yO 3 BSTO thin films have been synthesized using a molecular beam epitaxy system. Novel coplanar waveguide tunable phase shifters have been developed using these Mn-doped perovskite films. The presented phase shifters operate with a phase shift angle of 12 degrees at 10GHz. at an applied bias of 10V on an area smaller than 1mm 2 , Insertion loss of ~3.2 dB is extracted from the S-parameter measurement. Small changes of composition lead to a significant variation of device phase shift, demonstrating the importance of synthesizing suitable structure BSTO film