This paper presents a single-chip CMOS-MEMS flow sensing system for high-precision bidirectional gas flow detection, featuring a pulse-excited constant temperature difference (CTD) control scheme and a low-noise analog front-end using capacitively coupled chopper instrumentation amplifier (CCIA). The MEMS sensing structure is fabricated using a cost-effective surface micromachining process and thinned to$1.38~\mu $m, significantly enhancing system sensitivity and thermal efficiency. Two sensor prototypes, with MEMS opening sizes of$130~\mu $m and$170~\mu $m (named as Sensor 130 and Sensor 170), achieve record-high sensitivities of 24.74 mV/(m/s) and 30.84 mV/(m/s), respectively, within a linear flow range of ±5 m/s. Leveraging pulse excitation, the system dramatically reduces heating power down to 1.63 mW (Sensor 130) and 1.85 mW (Sensor 170). The CCIA readout circuit exhibits an ultra-low input-referred noise density of 5.86nV/$\surd $Hz, with a 1/$f$noise corner below 0.1 Hz, greatly improving low-flow detection capabilities of the sensor system. As a result, the overall system output noise density is measured at$1.93~\mu $V/$\surd $Hz, enabling minimum detectable flow velocities (MDFV) of 0.51 mm/s (Sensor 130) and 0.41 mm/s (Sensor 170). With its compact design, low power, and exceptional circuit performance, this cost-effective CMOS-MEMS flow sensing system is well-suited for high-precision flow measurement in industrial and IoT applications.

In this paper, we present a system-level model for an ambient temperature-compensated CMOS MEMS Thermal Flow (C2MTF) sensor. The system-level model is first validated by a computational fluid dynamics (CFD) model and is further used for a fully coupled simulation between the microstructure, heat transfer, and interface circuits. Correspondingly, a monolithically integrated C2MTF sensor is designed and optimized using a 0.18 μm 1P6M CMOS MEMS technology. The designed System on Chip (SoC) C2MTF sensor has a flow range of -10~10 m/s, and its highest sensitivity is 0.274 V/(m/s) with a system power consumption of less than 3.6 mW. In comparison with the more than 50% output drift for the uncompensated counterpart, the output drift of the designed C2MTF sensor is reduced to 7% under an ambient temperature of 0~50 °C. In addition, based on the proposed system-level model, the additional optimizations show that the output drift can be greatly reduced to 0.5%, by arranging another on-chip overheated temperature-regulating resistor Rcin the future, delicately.

In this paper, we present a novel physical unclonable function (PUF) based on dual entropy sources of a 2-transistor voltage reference (2T-VR) and a four-stage diode-clamped comparator. Featuring excellent stability over wide range of supply voltage and temperature, the proposed 2T-VR is constructed with one native transistor plus one PMOS transistor that are compensated to minimize its temperature coefficient. Moreover, different from most previous PUF implementations where a digital comparator with offset-cancellation is needed for digitizing the mismatched voltages/currents from the prior entropy stage, in this work, the customized diode-clamped comparator’s offset is well-exploited as an additional entropy source, which can be superposed on the above 2T-VR-based entropy to significantly elevate the whole PUF structure’s reliability. Besides, a near zero-overhead in-cell entropy sign based stabilization (ESS) scheme is proposed to further enhance the reliability by stabilizing the scenario with the dual entropy sources having opposite signs. The designed dual-entropy-superposed PUF is fabricated using a 65-nm standard CMOS process, and its excellent randomness is validated using the widely-accepted National Institute of Standards and Technology (NIST) PUB 800-22/800-90B and autocorrelation function (ACF) test tools. With the test chips repeatedly challenged at normal condition up to 4000 times, the measured native bit error rate (BER) and unstable bits are reported to be 0.16% and 1.3%, respectively. Moreover, with the operating temperature changing from −50°C to 130°C and the supply voltage changing from 0.8 V to 1.4 V, the native BER’s VT sensitivities without stabilization are measured to be 0.195%/10°C and 0.651%/0.1 V, respectively, which can be further reduced by$4.5\times $and$1.5\times $with the proposed ESS scheme applied.

Developing efficient metal-organic framework (MOF) based nanocomposite sensor with superior performance for fast, sensitive and selective detection of ammonia (NH3) is essential for environmental protection and human health. This work reports synthesis of Pd-Co@IRMOF- 1 nanocomposite based gas sensor for the detection/sensing of ammonia (NH3) at room temperature. The successful synthesis of Pd-Co@IRMOF-1 nanocomposite was confirmed with spectroscopic and structural characterizations. Unlike earlier realizations, the fabricated Pd-Co@IRMOF-1 nanocomposite based sensor showed notable detection sensitivity for NH3 at concentrations down to 1ppm level. Distinctly, the MOF based nanocomposite sensor exhibited the excellent sensitivity and long-time stability to NH3. In contrast to other reported MOFs, Pd-Co@IRMOF-1 showed remarkable selectivity towards ammonia in comparison to formaldehyde, ethanol, acetone, Isopropyl alcohol and benzene. The Pd-Co@IRMOF-1 based sensor exhibited excellent performance for sensing of ammonia which can be helpful for future in wearable sensor device applications.

In this study, the finite-time formation control of multi-agent systems with region constraints is studied. Multiple agents have first-order dynamics and a common target area. A novel control algorithm is proposed using local information and interaction. If the communication graph is undirected and connected and the desired framework is rigid, it is proved that the controller can be used to solve the formation problem with a target area. That is, all agents can enter the desired region in finite time while reaching and maintaining the desired formation shapes. Finally, a numerical example is given to illustrate the results.

In this paper, a current mode physical unclonable function (PUF) based on the winner-take-all (WTA) scheme is presented. By using the process variation of the single transistor in the current mirror array, digital values with superior randomness can be produced. With the proposed WTA scheme, the time needed to acquire the currents' difference is significantly reduced. Meanwhile, the overall power consumption is also greatly lowered with the simplified peripheral circuitry. Moreover, unstable bit replacement circuitry is customized to remove the unstable bit caused by WTA's mismatch, which further improves the reliability of our proposed PUF. According to the simulation results using standard 65nm CMOS process, the proposed unstable replacement circuitry can replace up to 12.07% of the unstable bits. In addition, the superior averaged temperature reliability of the proposed implementation is 99.53% from -20° C to 100°C, with the overall power consumption as low as 892nW.

During navigation, a pedestrian needs to recognize a landmark at a certain decision point. If a potential landmark located at a decision point is complicated to recognize, the complexity of the decision point is significantly increased. Thus, it is important to compute routes that avoid complicated decision points (CDPs) but still achieve optimal navigation performance. In this paper, we propose an approach for computing routes that avoid CDPs while optimizing the performance of landmark-based pedestrian navigation. The approach includes (1) a model for identifying CDPs based on the structures of pedestrian networks and landmark data in real scenes, and (2) a modified genetic algorithm for computing routes that avoid the identified CDPs and find the shortest route possible. To demonstrate the advantages and effectiveness of the proposed approach, we conducted an empirical study on the pedestrian network in a real-world scenario. The experimental results show that our approach can effectively avoid CDPs while still minimizing travel distance. Furthermore, our approach can provide the routes with the shortest travel distance if the distances of the routes without CDPs exceed a certain threshold.

This paper presents a novel K times singular value decomposition (K-SVD) based denoising algorithm for the division-of-focal-plane (DoFP) polarization image sensors. In the proposed implementation, the input DoFP image can be expressed by the optimum sparse combination of the dictionary elements via K-SVD and orthogonal matching pursuit (OMP) algorithms. As a result, this implementation is capable of eliminating the Gaussian noise significantly and well-preserving the details and edges of the target DoFP image. Our extensive experimental results on various test images show that the proposed algorithm yields better visual quality and maintains a lower PSNR value while compared with a wide range of previous implementations.

Analyzing the concentration of acetone in human breath constitutes a promising non-invasive means to diagnose the onset of diabetes, with acetone levels of at least 1.8ppm typically associated to individuals suffering from diabetes. In this paper, we report the performance of a hierarchical ZnO nanostructure gas sensor for acetone detection. The fabricated gas sensor can detect concentrations as low as 1ppm while operating at a comparatively lower temperature of 200°C. In addition, the proposed gas sensor can be fabricated on a silicon wafer using a MEMS process, making it thereby possible to fully integrate gas sensing and electronic circuitry on a single silicon chip.

In this paper, we present a novel physical unclonable function (PUF) based on time-domain current difference measurement. By employing the aforesaid simplified current-mode PUF architecture, the proposed implementation completely removes the need of complex error correction circuitry, which is widely adopted in the previously demonstrated implementations. This leads to significant reduction of both the overall power consumption and the required chip area. In addition, the proposed implementation exhibits a superior bit error rate (BER) as low as 0 for the typical case scenario and 1.56% for the worst case scenario, respectively. Featuring an ultra-low power consumption of 11.29μW and an averaged silicon area of 13310μm2, the proposed implementation is validated by our reported extensive post-layout simulation results with UMC 0.18μm standard complementary-metal-oxide-semiconductor (CMOS) technology.

In this paper, a novel CMOS-compatible ZnO nanocomb-based gas sensor is presented. Compared with previously reported implementations, the proposed ZnO nanocombs feature multiple conducting channels and much larger effective sensing area, both of which result in dramatically improved sensitivity (6.54 for 250 ppm CO), response time (3.4 min) and recovery time (0.24 min). In addition, by operating the gas sensor at room temperature, additional power-hungry heating components inevitable in traditional implementations are completely removed. This not only leads to low power consumption, but also avoids the high-temperature-caused reliability degradation when integrated with CMOS circuitry.