An integrated RF energy-harvesting system with broad input voltage range and high power conversion efficiency.

By 2050, countries around the world are expected to be gradually phasing out fossil fuels and implementing greener energy technologies. In this work, we present a system employing Energy harvesting, a self-powered technology that can recycle energy from the surrounding environment. A high-efficiency radio frequency (RF) energy-harvesting chip was designed and fabricated. With an off-chip antenna and rectifier, the system scavenges ambient RF energy and converts it into usable energy, which is then stored in energy storage elements (such as a supercapacitor or a rechargeable battery). The system can further be implemented as an energy source for charging smart devices. The system-on-chip design consists of a cold start block, a boost converter with maximum power point tracking functionalities, and a charging block. The chip was fabricated using AMS 350 nm technology. Although the system was optimized for harvesting RF energy, it can be easily adapted to harvest other energy sources (i.e., mechanical and thermal energy sources). Using an optimized cold start architecture, the circuit has a cold start voltage of 380 mV. With an improved control strategy of power conversion, the system is capable of continuously charging up to 4.5 V with a broad input voltage range of 100 mV to 10 V and has a peak charging efficiency of 82%.

Highly Indistinguishable Single Photons from Droplet-Etched GaAs Quantum Dots Integrated in Single-Mode Waveguides and Beamsplitters.

Integration of on-demand quantum emitters into photonic integrated circuits (PICs) has drawn much attention in recent years, as it promises a scalable implementation of quantum information schemes. A central property for several applications is the indistinguishability of the emitted photons. In this regard, GaAs quantum dots (QDs) obtained by droplet etching epitaxy show excellent performances, making the realization of these QDs into PICs highly appealing. Here, we show the first implementation in this direction, realizing the key passive elements needed in PICs, i.e., single-mode waveguides (WGs) with integrated GaAs-QDs and beamsplitters. We study the statistical distribution of wavelength, linewidth, and decay time of the excitonic line, as well as the quantum optical properties of individual emitters under resonant excitation. We achieve single-photon purities as high as 1 - g(2)(0) = 0.929 ± 0.009 and two-photon interference visibilities of up to VTPI = 0.953 ± 0.032 for consecutively emitted photons.

Research on the Performance of Thermoelectric Self-Powered Systems for Wireless Sensor Based on Industrial Waste Heat.

The issue of energy supply for wireless sensors is becoming increasingly severe with the advancement of the Fourth Industrial Revolution. Thus, this paper proposed a thermoelectric self-powered wireless sensor that can harvest industrial waste heat for self-powered operations. The results show that this self-powered wireless sensor can operate stably under the data transmission cycle of 39.38 s when the heat source temperature is 70 °C. Only 19.57% of electricity generated by a thermoelectric power generation system (TPGS) is available for use. Before this, the power consumption of this wireless sensor had been accurately measured, which is 326 mW in 0.08 s active mode and 5.45 µW in dormant mode. Then, the verified simulation model was established and used to investigate the generation performance of the TPGS under the Dirichlet, Neumann, and Robin boundary conditions. The minimum demand for a heat source is cleared for various data transmission cycles of wireless sensors. Low-temperature industrial waste heat is enough to drive the wireless sensor with a data transmission cycle of 30 s. Subsequently, the economic benefit of the thermoelectric self-powered system was also analyzed. The cost of one thermoelectric self-powered system is EUR 9.1, only 42% of the high-performance battery cost. Finally, the SEPIC converter model was established to conduct MPPT optimization for the TEG module and the output power can increase by up to approximately 47%. This thermoelectric self-powered wireless sensor can accelerate the process of achieving energy independence for wireless sensors and promote the Fourth Industrial Revolution.

Differential BroadBand (1-16 GHz) MMIC GaAs mHEMT Low-Noise Amplifier for Radio Astronomy Applications and Sensing.

A broadband differential-MMIC low-noise amplifier (DLNA) using metamorphic high-electron-mobility transistors of 70 nm in Gallium Arsenide (70 nm GaAs mHEMT technology) is presented. The design and results of the performance measurements of the DLNA in the frequency band from 1 to 16 GHz are shown, with a high dynamic range, and a noise figure (NF) below 1.3 dB is obtained. In this work, two low-noise amplifiers (LNAs) were designed and manufactured in the OMMIC foundry: a dual LNA, which we call balanced, and a differential LNA, which we call DLNA. However, the paper focuses primarily on DLNA because of its differential architecture. Both use a 70 nm GaAs mHEMT space-qualified technology with a cutoff frequency of 300 GHz. With a low power bias Vbias/Ibias (5 V/40.5 mA), NF < 1.07 dB "on wafer" was achieved, from 2 to 16 GHz; while with the measurements made "on jig", NF = 1.1 dB, from 1 to 10 GHz. Furthermore, it was obtained that NF < 1.5 dB, from 1 to 16 GHz, with a figure of merit equal to 145.5 GHz/mW. Finally, with the proposed topology, several LNAs were designed and manufactured, both in the OMMIC process and in other foundries with other processes, such as UMS. The experimental results showed that the NF of the DLNA MMIC with multioctave bandwidth that was built in the frequency range of the L-, S-, C-, and X-bands was satisfactory.

Polymer-Waveguide-Integrated 2D Semiconductor Heterostructures for Optical Communications.

The demand for high-speed and low-loss interconnects in modern computer architectures is difficult to satisfy by using traditional Si-based electronics. Although optical interconnects offer a promising solution owing to their high bandwidth, low energy dissipation, and high-speed processing, integrating elements such as a light source, detector, and modulator, comprising different materials with optical waveguides, presents many challenges in an integrated platform. Two-dimensional (2D) van der Waals (vdW) semiconductors have attracted considerable attention in vertically stackable optoelectronics and advanced flexible photonics. In this study, optoelectronic components for exciton-based photonic circuits are demonstrated by integrating lithographically patterned poly(methyl methacrylate) (PMMA) waveguides on 2D vdW devices. The excitonic signals generated from the 2D materials by using laser excitation were transmitted through patterned PMMA waveguides. By introducing an external electric field and combining vdW heterostructures, an excitonic switch, phototransistor, and guided-light photovoltaic device on SiO2/Si substrates were demonstrated.

Batteryless wireless magnetostrictive Fe30Co70/Ni clad plate for human coronavirus 229E detection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been garnered increasing for its rapid worldwide spread. Each country had implemented city-wide lockdowns and immigration regulations to prevent the spread of the infection, resulting in severe economic consequences. Materials and technologies that monitor environmental conditions and wirelessly communicate such information to people are thus gaining considerable attention as a countermeasure. This study investigated the dynamic characteristics of batteryless magnetostrictive alloys for energy harvesting to detect human coronavirus 229E (HCoV-229E). Light and thin magnetostrictive Fe-Co/Ni clad plate with rectification, direct current (DC) voltage storage capacitor, and wireless information transmission circuits were developed for this purpose. The power consumption was reduced by improving the energy storage circuit, and the magnetostrictive clad plate under bending vibration stored a DC voltage of 1.9 V and wirelessly transmitted a signal to a personal computer once every 5 min and 10 s under bias magnetic fields of 0 and 10 mT, respectively. Then, on the clad plate surface, a novel CD13 biorecognition layer was immobilized using a self-assembled monolayer of -COOH groups, thus forming an amide bond with -NH2 groups for the detection of HCoV-229E. A bending vibration test demonstrated the resonance frequency changes because of HCoV-229E binding. The fluorescence signal demonstrated that HCoV-229E could be successfully detected. Thus, because HCoV-229E changed the dynamic characteristics of this plate, the CD13-modified magnetostrictive clad plate could detect HCoV-229E from the interval of wireless communication time. Therefore, a monitoring system that transmits/detects the presence of human coronavirus without batteries will be realized soon.

3.6 mW Active-Electrode ECG/ETI Sensor System Using Wideband Low-Noise Instrumentation Amplifier and High Impedance Balanced Current Driver.

An active electrode (AE) and back-end (BE) integrated system for enhanced electrocardiogram (ECG)/electrode-tissue impedance (ETI) measurement is proposed. The AE consists of a balanced current driver and a preamplifier. To increase the output impedance, the current driver uses a matched current source and sink, which operates under negative feedback. To increase the linear input range, a new source degeneration method is proposed. The preamplifier is realized using a capacitively-coupled instrumentation amplifier (CCIA) with a ripple-reduction loop (RRL). Compared to the traditional Miller compensation, active frequency feedback compensation (AFFC) achieves bandwidth extension using the reduced size of the compensation capacitor. The BE performs three types of signal sensing: ECG, band power (BP), and impedance (IMP) data. The BP channel is used to detect the Q-, R-, and S-wave (QRS) complex in the ECG signal. The IMP channel measures the resistance and reactance of the electrode-tissue. The integrated circuits for the ECG/ETI system are realized in the 180 nm CMOS process and occupy a 1.26 mm2 area. The measured results show that the current driver supplies a relatively high current (>600 µApp) and achieves a high output impedance (1 MΩ at 500 kHz). The ETI system can detect resistance and capacitance in the ranges of 10 mΩ-3 kΩ and 100 nF-100 µF, respectively. The ECG/ETI system consumes 3.6 mW using a single 1.8 V supply.

Research on Motion Control and Wafer-Centering Algorithm of Wafer-Handling Robot in Semiconductor Manufacturing.

This paper studies the AWC (Active Wafer Centering) algorithm for the movement control and wafer calibration of the handling robot in semiconductor manufacturing to prevent wafer surface contact and contamination during the transfer process. The mechanical and software architecture of the wafer-handling robot is analyzed first, which is followed by a description of the experimental platform for semiconductor manufacturing methods. Secondly, the article utilizes the geometric method to analyze the kinematics of the semiconductor robot, and it decouples the motion control of the robot body from the polar coordinates and joint space. The wafer center position is calibrated using the generalized least-square inverse method for AWC correction. The AWC algorithm is divided into calibration, deviation correction, and retraction detection. These are determined by analyzing the robot's wafer calibration process. In conclusion, the semiconductor robot's motion control and AWC algorithm are verified through experiments for correctness, feasibility, and effectiveness. After the wafer correction, the precision of AWC is <± 0.15 mm, which meets the requirements for transferring robot wafers.

A CMOS Image Readout Circuit with On-Chip Defective Pixel Detection and Correction.

Images produced by CMOS sensors may contain defective pixels due to noise, manufacturing errors, or device malfunction, which must be detected and corrected at early processing stages in order to produce images that are useful to human users and image-processing or machine-vision algorithms. This paper proposes a defective pixel detection and correction algorithm and its implementation using CMOS analog circuits, which are integrated with the image sensor at the pixel and column levels. During photocurrent integration, the circuit detects defective values in parallel at each pixel using simple arithmetic operations within a neighborhood. At the image-column level, the circuit replaces the defective pixels with the median value of their neighborhood. To validate our approach, we designed a 128×128-pixel imager in a 0.35µm CMOS process, which integrates our defective-pixel detection/correction circuits and processes images at 694 frames per second, according to post-layout simulations. Operating at that frame rate, our proposed algorithm and its CMOS implementation produce better results than current state-of-the-art algorithms: it achieves a Peak Signal to Noise Ratio (PSNR) and Image Enhancement Factor (IEF) of 45 dB and 198.4, respectively, in images with 0.5% random defective pixels, and a PSNR of 44.4 dB and IEF of 194.2, respectively, in images with 1.0% random defective pixels.

A Cost-Driven Method for Deep-Learning-Based Hardware Trojan Detection.

The Cyber-Physical System and even the Metaverse will become the second space in which human beings live. While bringing convenience to human beings, it also brings many security threats. These threats may come from software or hardware. There has been a lot of research on managing malware, and there are many mature commercial products, such as antivirus software, firewalls, etc. In stark contrast, the research community on governing malicious hardware is still in its infancy. Chips are the core component of hardware, and hardware Trojans are the primary and complex security issue faced by chips. Detection of hardware Trojans is the first step for dealing with malicious circuits. Due to the limitation of the golden chip and the computational consumption, the existing traditional detection methods are not applicable to very large-scale integration. The performances of traditional machine-learning-based methods depend on the accuracy of the multi-feature representation, and most of the methods may lead to instability because of the difficulty of extracting features manually. In this paper, employing deep learning, a multiscale detection model for automatic feature extraction is proposed. The model is called MHTtext and provides two strategies to balance the accuracy and computational consumption. After selecting a strategy according to the actual situations and requirements, the MHTtext generates the corresponding path sentences from the netlist and employs TextCNN for identification. Further, it can also obtain non-repeated hardware Trojan component information to improve its stability performance. Moreover, a new evaluation metric is established to intuitively measure the model's effectiveness and balance: the stabilization efficiency index (SEI). In the experimental results for the benchmark netlists, the average accuracy (ACC) in the TextCNN of the global strategy is as high as 99.26%, and one of its stabilization efficiency index values ranks first with a score of 71.21 in all comparison classifiers. The local strategy also achieved an excellent effect, according to the SEI. The results show that the proposed MHTtext model has high stability, flexibility, and accuracy, in general.

Stability, Mounting, and Measurement Considerations for High-Power GaN MMIC Amplifiers.

In this paper, the precise design of a high-power amplifier (HPA) is shown, along with the problems associated with the stability of "on-wafer" measurements. Here, techniques to predict possible oscillations are discussed to ensure the stability of a monolithic microwave-integrated circuit (MMIC). In addition, a deep reflection is made on the instabilities that occur when measuring both on wafer and using a mounted chip. Stability techniques are used as tools to characterize measurement results. Both a precise design and instabilities are shown through the design of a three-stage X-band HPA in gallium nitride (GaN) from the WIN Semiconductors Corp. foundry. As a result, satisfactory performance was obtained, achieving a maximum output power equal to 42 dBm and power-added efficiency of 32% at a 20 V drain bias. In addition to identifying critical points in the design or measurement of the HPA, this research shows that the stability of the amplifier can be verified through a simple analysis and that instabilities are often linked to errors in the measurement process or in the characterization of the measurement process.

Automated Age-Related Macular Degeneration Detector on Optical Coherence Tomography Images Using Slice-Sum Local Binary Patterns and Support Vector Machine.

Artificial intelligence has revolutionised smart medicine, resulting in enhanced medical care. This study presents an automated detector chip for age-related macular degeneration (AMD) using a support vector machine (SVM) and three-dimensional (3D) optical coherence tomography (OCT) volume. The aim is to assist ophthalmologists by reducing the time-consuming AMD medical examination. Using the property of 3D OCT volume, a modified feature vector connected method called slice-sum is proposed, reducing computational complexity while maintaining high detection accuracy. Compared to previous methods, this method significantly reduces computational complexity by at least a hundredfold. Image adjustment and noise removal steps are excluded for classification accuracy, and the feature extraction algorithm of local binary patterns is determined based on hardware consumption considerations. Through optimisation of the feature vector connection method after feature extraction, the computational complexity of SVM detection is significantly reduced, making it applicable to similar 3D datasets. Additionally, the design supports model replacement, allowing users to train and update classification models as needed. Using TSMC 40 nm CMOS technology, the proposed detector achieves a core area of 0.12 mm2 while demonstrating a classification throughput of 8.87 decisions/s at a maximum operating frequency of 454.54 MHz. The detector achieves a final testing classification accuracy of 92.31%.

A 2-V 1.4-dB NF GaAs MMIC LNA for K-Band Applications.

A 1.4-dB Noise Figure (NF) four-stage K-band Monolithic Microwave Integrated Circuit (MMIC) Low-Noise Amplifier (LNA) in UMS 100 nm GaAs pHEMT technology is presented. The proposed circuit is designed to cover the 5G New Release n258 frequency band (24.25-27.58 GHz). Momentum EM post-layout simulations reveal the circuit achieves a minimum NF of 1.3 dB, a maximum gain of 34 dB, |S11| better than -10 dB from 23 GHz to 29 GHz, a P1dB of -18 dBm and an OIP3 of 24.5 dBm. The LNA draws a total current of 59.1 mA from a 2 V DC supply and results in a chip size of 3300 × 1800 µm2 including pads. We present a design methodology focused on the selection of the active device size and DC bias conditions to obtain the lowest NF when source degeneration is applied. The design procedure ensures a minimum NF design by selecting a device which facilitates a simple input matching network implementation and obtains a reasonable input return loss thanks to the application of source degeneration. With this approach the input matching network is implemented with a shunt stub and a transmission line, therefore minimizing the contribution to the NF achieved by the first stage. Comparisons with similar works demonstrate the developed circuit is very competitive with most of the state-of-the-art solutions.

An MMIC LNA for Millimeter-Wave Radar and 5G Applications with GaN-on-SiC Technology.

This paper presents a monolithic microwave integrated circuit (MMIC) low noise amplifier (LNA) that is compatible with n257 (26.5-29.5 GHz) and n258 (24.25-27.5 GHz) frequency bands for fifth-generation mobile communications system (5G) and millimeter-wave radar. The total circuit size of the LNA is 2.5 × 1.5 mm2. To guarantee a trade-off between noise figure (NF) and small signal gain, the transmission lines are connected to the source of gallium nitride (GaN)-on-SiC high electron mobility transistors (HEMT) by analyzing the nonlinear small signal equivalent circuit. A series of stability enhancement measures including source degeneration, an RC series network, and RF choke are put forward to enhance the stability of designed LNA. The designed GaN-based MMIC LNA adopts hybrid-matching networks (MNs) with co-design strategy to realize low NF and broadband characteristics across 5G n257 and n258 frequency band. Due to the different priorities of these hybrid-MNs, distinguished design strategies are employed to benefit small signal gain, input-output return loss, and NF performance. In order to meet the testing conditions of MMIC, an impeccable system for measuring small has been built to ensure the accuracy of the measured results. According to the measured results for small signal, the three-stage MMIC LNA has a linear gain of 18.2-20.3 dB and an NF of 2.5-3.1 dB with an input-output return loss better than 10 dB in the whole n257 and n258 frequency bands.

Subthreshold Schottky-contacted carbon nanotube network film field-effect transistors for ultralow-power electronic applications.

Ultralow-power electronics is critical to wearable, portable, and implantable applications where the systems could only have access to very limited electrical power supply or even be self-powered. Here, we report on a type of Schottky barrier (SB) contacted single-walled carbon nanotube (SWCNT) network film field-effect-transistors (FETs) that are operated in the subthreshold region to achieve ultralow-power applications. The thin high-k gate dielectric and the overlap between the gate and the source electrodes offer highly efficient gate electrostatic control over the SWCNT channel and the SB at the source contact, resulting in steep subthreshold switching characteristics with a small subthreshold swing (∼67 mV dec-1), a large current on/off ratio (∼106), and a low off-state current (∼0.5 pA). Ap-channel metal-oxide-semiconductor inverter built with the subthreshold SB-SWCNT-FETs exhibits a well-defined logic functionality and small-signal amplification capability under a low supply voltage (∼0.5 V) and an ultralow power (∼0.05 pWµm-1). The low-voltage and deep subthreshold operations reported here could lay an essential foundation for high-performance and ultralow-power SWCNTs-based electronics.

Miniaturization of Laser Doppler Vibrometers-A Review.

Laser Doppler vibrometry (LDV) is a non-contact vibration measurement technique based on the Doppler effect of the reflected laser beam. Thanks to its feature of high resolution and flexibility, LDV has been used in many different fields today. The miniaturization of the LDV systems is one important development direction for the current LDV systems that can enable many new applications. In this paper, we will review the state-of-the-art method on LDV miniaturization. Systems based on three miniaturization techniques will be discussed: photonic integrated circuit (PIC), self-mixing, and micro-electrochemical systems (MEMS). We will explain the basics of these techniques and summarize the reported miniaturized LDV systems. The advantages and disadvantages of these techniques will also be compared and discussed.

Synthesis of High-Input Impedance Electronically Tunable Voltage-Mode Second-Order Low-Pass, Band-Pass, and High-Pass Filters Based on LT1228 Integrated Circuits.

This paper introduces two new high-input impedance electronically tunable voltage-mode (VM) multifunction second-order architectures with band-pass (BP), low-pass (LP), and high-pass (HP) filters. Both proposed architectures have one input and five outputs, implemented employing three commercial LT1228 integrated circuits (ICs), two grounded capacitors, and five resistors. Both proposed architectures also feature one high-impedance input port and three low-impedance output ports for easy connection to other VM configurations without the need for VM buffers. The two proposed VM LT1228-based second-order multifunction filters simultaneously provide BP, LP, and HP filter transfer functions at Vo1, Vo2, and Vo3 output terminals. The pole angular frequencies and the quality factors of the two proposed VM LT1228-based second-order multifunction filters can be electronically and orthogonally adjusted by the bias currents from their corresponding commercial LT1228 ICs, and can be independently adjusted in special cases. In addition, both proposed VM LT1228-based second-order multifunction filters have two independent gain-controlled BP and LP filter transfer functions at Vo4 and Vo5 output terminals, respectively. Based on the three commercial LT1228 ICs and several passive components, simulations and experimental measurements are provided to verify the theoretical predictions and demonstrate the performance of the two proposed high-input impedance electronically tunable VM LT1228-based second-order multifunction filters. The measured input 1-dB power gain compression point (P1dB), third-order IMD (IMD3), third-order intercept (TOI) point, and spurious-free dynamic range (SFDR) of the first proposed filter were -7.1 dBm, -48.84 dBc, 4.133 dBm, and 45.02 dBc, respectively. The measured input P1dB, IMD3, TOI, and SFDR of the second proposed filter were -7 dBm, -49.65 dBc, 4.316 dBm, and 45.88 dBc, respectively. Both proposed filters use a topology synthesis method based on the VM second-order non-inverting/inverting HP filter transfer functions to generate the BP, LP and HP filter transfer functions simultaneously, making them suitable for applications in three-way crossover networks.

Photonic Label-Free Biosensors for Fast and Multiplex Detection of Swine Viral Diseases.

In this paper we present the development of photonic integrated circuit (PIC) biosensors for the label-free detection of six emerging and endemic swine viruses, namely: African Swine Fever Virus (ASFV), Classical Swine Fever Virus (CSFV), Porcine Reproductive and Respiratory Syndrome Virus (PPRSV), Porcine Parvovirus (PPV), Porcine Circovirus 2 (PCV2), and Swine Influenza Virus A (SIV). The optical biosensors are based on evanescent wave technology and, in particular, on Resonant Rings (RRs) fabricated in silicon nitride. The novel biosensors were packaged in an integrated sensing cartridge that included a microfluidic channel for buffer/sample delivery and an optical fiber array for the optical operation of the PICs. Antibodies were used as molecular recognition elements (MREs) and were selected based on western blotting and ELISA experiments to ensure the high sensitivity and specificity of the novel sensors. MREs were immobilized on RR surfaces to capture viral antigens. Antibody-antigen interactions were transduced via the RRs to a measurable resonant shift. Cell culture supernatants for all of the targeted viruses were used to validate the biosensors. Resonant shift responses were dose-dependent. The results were obtained within the framework of the SWINOSTICS project, contributing to cover the need of the novel diagnostic tools to tackle swine viral diseases.

Technological Requirements and Challenges in Wireless Body Area Networks for Health Monitoring: A Comprehensive Survey.

With the rapid growth in healthcare demand, an emergent, novel technology called wireless body area networks (WBANs) have become promising and have been widely used in the field of human health monitoring. A WBAN can collect human physical parameters through the medical sensors in or around the patient's body to realize real-time continuous remote monitoring. Compared to other wireless transmission technologies, a WBAN has more stringent technical requirements and challenges in terms of power efficiency, security and privacy, quality of service and other specifications. In this paper, we review the recent WBAN medical applications, existing requirements and challenges and their solutions. We conducted a comprehensive investigation of WBANs, from the sensor technology for the collection to the wireless transmission technology for the transmission process, such as frequency bands, channel models, medium access control (MAC) and networking protocols. Then we reviewed its unique safety and energy consumption issues. In particular, an application-specific integrated circuit (ASIC)-based WBAN scheme is presented to improve its security and privacy and achieve ultra-low energy consumption.

High-Performance Pockels Effect Modulation and Switching in Silicon-Based GaP/Si, AlP/Si, ZnS/Si, AlN/3C-SiC, GaAs/Ge, ZnSe/GaAs, and ZnSe/Ge Superlattice-On-Insulator Integrated Circuits.

We propose new a Si-based waveguided Superlattice-on-Insulator (SLOI) platforms for high-performance electro-optical (EO) 2 × 2 and N × M switching and 1 × 1 modulation, including broad spectrum and resonant. We present a theoretical investigation based on the tight-binding Hamiltonian of the Pockels EO effect in the lattice-matched undoped (GaP)N/(Si2)M, (AlP)N/(Si2)M, (ZnS)N/(Si2)M, (AlN)N/(3C-SiC)M, (GaAs)N/(Ge2)M, (ZnSe)N/(GaAs)M, and (ZnSe)N/(Ge2)M wafer-scale short-period superlattices that are etched into waveguided networks of small-footprint Mach-Zehnder interferometers and micro-ring resonators to yield opto-electronic chips. The spectra of the Pockels r33 coefficient have been simulated as a function of the number of the atomic monolayers for "non-relaxed" heterointerfaces. The large obtained r33 values enable the SLOI circuit platforms to offer a very favorable combination of monolithic construction, cost-effective manufacturability, high modulation/switching speed, high information bandwidth, tiny footprint, low energy per bit, low switching voltage, near-IR-and-telecom wavelength coverage, and push-pull operation. By optimizing waveguide, clad, and electrode dimensions, we obtained very desirable values of the VπL performance metric, in the range of 0.062 to 0.275 V·cm, portending a bright future for a variety of applications, such as sensor networks or Internet of Things (IoT).