23.5 A Sub-1V 810nW Capacitively-Biased BJT-Based Temperature Sensor with an Inaccuracy of ±0.15°C (3σ) from -55°C to 125°C

BJT-based temperature sensors are widely used because they can achieve excellent accuracy after 1-point calibration. However, they typically dissipate mu textWs of power and require supply voltages above 1V [1]. Although sensors based on DTMOSTs [2], [3], capacitively biased (CB) diodes and BJTs [4,5] have demonstrated sub-1V operation, this...

23.7 A BJT-Based Temperature Sensor with ±0.1 C(3σ) Inaccuracy from -55°C to 125°C and a 0.85pJ.K²Resolution FoM Using Continuous-Time Readout

BJT-based temperature sensors are widely used due to their high accuracy over a wide temperature range with a low-cost 1-point trim. Although resistor-based sensors can achieve better energy efficiency, they typically require a 2-point trim to achieve comparable accuracy, while thermal-diffusivity based sensors achieve superior accuracy at...

A Sub-1 V Capacitively Biased BJT-Based Temperature Sensor With an Inaccuracy of ± 0.15 ∘ C (3 σ ) From − 55 ∘ C to 125 ∘ C

This article presents a sub-1 V bipolar junction transistor (BJT)-based temperature sensor that achieves both high accuracy and high energy efficiency. To avoid the extra headroom required by conventional current sources, the sensor’s diode-connected BJTs are biased by precharging sampling capacitors to the supply voltage and then discharging...

Unwieldy Object Delivery With Nonholonomic Mobile Base: A Stable Pushing Approach

This letter addresses the problem of pushing manipulation with nonholonomic mobile robots. Pushing is a fundamental skill that enables robots to move unwieldy objects that cannot be grasped. We propose a stable pushing method that maintains stiff contact between the robot and the object to avoid consuming repositioning actions. We prove that...

The competition and equilibrium in power markets under decarbonization and decentralization

Equilibrium analysis has been widely studied as an effective tool to model gaming interactions and predict market results. However, as competition modes are fundamentally changed by the decarbonization and decentralization of power systems, analysis techniques must evolve. This article comprehensively reviews recent developments in modelling...

Molecular Dynamics Simulation of Sintering Densification of Multi-Scale Silver Layer

Based on molecular dynamics (MD), in this study, a model was established to simulate the initial coating morphology of silver paste by using a random algorithm, and the effects of different sizes of particles on sintering porosity were also analyzed. The MD result reveals that compared with the sintering process using large-scale silver...

Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee

This paper presents a deep reinforcement learning (DRL) algorithm for orientation estimation using inertial sensors combined with a magnetometer. Lyapunov’s method in control theory is employed to prove the convergence of orientation estimation errors. The estimator gains and a Lyapunov function are parametrised by deep neural networks and...

Data driven discovery of cyber physical systems

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction...