Model-based design for self-sustainable sensor nodes

Long-term and maintenance-free operation is a critical feature for large-scale deployed battery-operated sensor nodes. Energy harvesting (EH) is the most promising technology to overcome the energy bottleneck of today’s sensors and to enable the vision of perpetual operation. However, relying on fluctuating environmental energy requires an application-specific analysis of the energy statistics combined with an in-depth characterization of circuits and algorithms, making design and verification complex. This article presents a model-based design (MBD) approach for EH-enabled devices accounting for the dynamic behavior of components in the power generation, conversion, storage, and discharge paths. The extension of existing compact models combined with data-driven statistical modeling of harvesting circuits allows accurate offline analysis, verification, and validation. The presented approach facilitates application-specific optimization during the development phase and reliable long-term evaluation combined with environmental datasets. Experimental results demonstrate the accuracy and flexibility of this approach: the model verification of a solar-powered wireless sensor node shows a determination coefficient () of 0.992, resulting in an energy error of only -1.57 % between measurement and simulation. Compared to state-of-practice methods, the MBD approach attains a reduction of the estimated state-of-charge error of up to 10.2 % in a real-world scenario. MBD offers non-trivial insights on critical design choices: the analysis of the storage element selection reveals a 2–3 times too high self-discharge per capacity ratio for supercapacitors and a peak current constrain for lithium-ion polymer batteries

Wearable Nano-Based Gas Sensors for Environmental Monitoring and Encountered Challenges in Optimization

With a rising emphasis on public safety and quality of life, there is an urgent need to ensure optimal air quality, both indoors and outdoors. Detecting toxic gaseous compounds plays a pivotal role in shaping our sustainable future. This review aims to elucidate the advancements in smart wearable (nano)sensors for monitoring harmful gaseous pollutants, such as ammonia (NH3), nitric oxide (NO), nitrous oxide (N2O), nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxide (CO2), hydrogen sulfide (H2S), sulfur dioxide (SO2), ozone (O3), hydrocarbons (CxHy), and hydrogen fluoride (HF). Differentiating this review from its predecessors, we shed light on the challenges faced in enhancing sensor performance and offer a deep dive into the evolution of sensing materials, wearable substrates, electrodes, and types of sensors. Noteworthy materials for robust detection systems encompass 2D nanostructures, carbon nanomaterials, conducting polymers, nanohybrids, and metal oxide semiconductors. A dedicated section dissects the significance of circuit integration, miniaturization, real-time sensing, repeatability, reusability, power efficiency, gas-sensitive material deposition, selectivity, sensitivity, stability, and response/recovery time, pinpointing gaps in the current knowledge and offering avenues for further research. To conclude, we provide insights and suggestions for the prospective trajectory of smart wearable nanosensors in addressing the extant challenges

Design and Fabrication of Photo-Thermal and Thermo-Electric Materials and Systems

Thermal energy is all around us. How to control and utilize it is an important topic in advanced manufacturing. This dissertation is focused on the design and fabrication of photo-thermal and thermo-electric materials and systems and is divided into three topics: pH-responsive Au@silica semi-shell nanoparticles (NPs), thermo-osmotic ionogel (TOI), and HClO₄-enhanced Fe(III/II) thermocells (TECs). pH-responsive photothermal therapy holds promise for non-invasive antitumor treatment, but the preparation of smart photothermal agents (PTAs) remains challenging. In the first topic (Chapter 3), a simple two-step approach was developed for the precise synthesis of anisotropic Au@silica semi-shell NPs, which were then used as pH-responsive PTAs for non-invasive antitumor therapy. In the synthesis of Au@silica semi-shell NPs, the isotropic solution-synthesized Au@silica core-shell NPs were firstly self-assembled on silicon wafers to form monolayer films by drop-casting technique. Then, Au@silica semi-shell NPs were obtained after selective and directional removal of part of the silica shell by reactive ion etching. After functionalization with pH-sensitive 4-mercaptobenzoic acid (4-MBA) molecules, the semi-shell NPs achieved pH-responsive rod-shaped assembly/disassembly in physiological saline solution, thereby exhibiting pH-responsive photothermal effects. In addition, the 4-MBA-semi-shell NPs have been successfully applied to in vitro photothermal therapy of tumor cells, showing great application potential in non-invasive antitumor therapy. Low efficiency in recovering low-grade heat remains unresolved despite decades’ attempts. In the second topic (Chapter 4), a novel thermo-osmotic ionogel (TOI) composite was designed and fabricated to recover low-grade heat to generate electric power through thermo-induced ion gradient and selective ion diffusion. The TOI composite was assembled with crystalline ionogel (polymer-confined LiNO₃-3H₂O) film, cation exchange membrane, and hydrogel film. With a 90 °C heat supply, the single TOI composite produced a high open-circuit voltage of 0.52 V, a differential thermal voltage of ~26 mV/K, a peak power density of 0.4 W/m², and a ground-breaking peak energy conversion efficiency of 11.17%. Eight pieces of such TOI composite were connected in series, demonstrating an open-circuit voltage of 3.25 volts. Such a TOI system was also demonstrated to harvest body temperature for powering a LED, opening numerous opportunities for powering wearable devices. This work opens a new door for efficient harvesting of low-grade heat by embedding thermo-osmotic conversion as an intermedia stage of thermo-electric conversion. In addition to thermo-ionic capacitors (Chapter 4), emerging thermocells (TECs) can convert a temperature gradient into electricity continuously and thus are promising for low-grade heat harvesting. However, it’s challenging to simultaneously improve the thermopower (Se, a thermodynamics parameter) and ionic conductivity (σᵢ, a kinetics parameter) of TECs due to the well-known inherent interdependence between thermodynamics and kinetics. In the third topic (Chapter 5), a simple perchloric acid (HClO₄) incorporation method has been developed to enhance the charge density of the oxidant Fe(III) ions in the state-of-the-art n-type Fe(III/II)-ClO₄ redox pair, thereby improving the Se and σᵢ simultaneously. In Fe(III/II)-ClO₄ electrolyte, the addition of HClO₄ composed of protons and weakly coordinating anions suppresses the deprotonation of [Fe(H₂O)₆]³⁺ without inducing Fe(III)-anion coordination. The n-type TEC using HClO₄-acidified Fe(III/II)-ClO₄ as electrolyte and hydrophilic carbon fiber cloth as the electrode was charactered and demonstrated a Se of 1.5 mV/K (comparable to -1.4 mV/K of benchmark p-type Fe(CN)₆³⁻/Fe(CN)₆⁴⁻ TECs) and an excellent temperature normalized power density of 1.19 mW/m²/K² (2.64 times higher than that of the state-of-the-art n-type TECs using carbon electrodes), overcoming barriers for practical p-n integrated TEC applications