Single-walled carbon nanotube (SWCNT) films hold great promise for advancing flexible thermoelectric generators. However, achieving a high power factor for the films as well as device output power remains challenging. Herein, a scalable dip-coating strategy to fabricate vacuum-filtered SWCNT films conformally coated with poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) is reported. This approach enhances interfacial charge transport and enables precise control over the SWCNT film coating. By optimizing the coating duration, the SWCNT/PEDOT:PSS composite films achieved a power factor of ∼340 µW/mK2 near room temperature. These values exceed those of pristine SWCNT films by ∼30% and outperform most previously reported films prepared via direct mixing or drop-casting. To demonstrate practical applicability, five pairs of SWCNT/PEDOT:PSS composite films were integrated onto an Ecoflex substrate to fabricate a flexible thermoelectric generator. The device provided a power density of ∼0.32 µW/cm2 at a 30 K temperature gradient with stable performance over repeated cycles. The combination of scalability, low-cost processing, and improved thermoelectric performance highlights dip-coating as a compelling and versatile route for the development of next-generation SWCNT-based flexible thermoelectric generators.

Flexible thermoelectric generators (TEGs) featuring out-of-plane thermoelement architecture and operating without internal interconnects are essential for achieving efficient power generation. In this work, a flexible TEG is designed and fabricated featuring monolithically integrated p-type single-walled carbon nanotube (SWCNT)/poly(3,4-ethylenedioxythiophene): polystyrene sulfonate composite films and n-type SWCNT films arranged in an out-of-plane configuration. This monolithic architecture eliminates the internal metallic interconnects, substantially reducing the internal resistance and enhancing the temperature gradient (ΔT) across the device. The thermoelectric films, prepared by vacuum filtration and drop-casting, exhibit Seebeck coefficients of 52.7 µV/°C for the p-type and − 42.1 µV/°C for the n-type films. Finite element analysis of the TEG confirmed a linear dependence of the open-circuit voltage (Voc) on ΔT, consistent with theoretical predictions. The fabricated flexible TEG, consisting six p- and n-type thermoelement pairs, generated Voc values approximately 3.48 mV and 14 mV under ΔT of 10.1 °C and 30.6 °C, respectively. Correspondingly, a maximum output power of approximately 1.6 µW and an areal power density of 0.9 µW/cm² was achieved by the TEG at a ΔT of 30.6 °C. These findings demonstrate a simple and scalable route toward architecturally optimized flexible TEGs based on monolithically integrated thin-film thermoelements.

Gradient descent, computed through backpropagation (BP), has been widely used to train spiking neural networks (SNNs). However, the approach has several limitations. It requires manual intervention to tune the network architecture, is prone to catastrophic forgetting of previously learned information when exposed to data containing new information, and is computationally demanding. To address these issues, we propose brain-mimetic developmental spiking neural networks (BDNNs), which emulate the postnatal development of biological neural circuits. We evaluated BDNNs using a neuromorphic tactile system with the task of classifying objects through grasping. Our findings show that BDNNs grow dynamically in response to input data by incrementally recruiting hidden neurons, leading to steadily increasing classification accuracy without the need for manual architecture tuning. The growth process adapts autonomously to the complexity of incoming data. BDNNs also exhibit strong knowledge transfer capabilities, which effectively leverage previously learned knowledge about grasping objects to incrementally learn about new objects. Furthermore, in comparative experiments using the same dataset and hardware, BDNNs achieved classification performance comparable to the standard BP-based method and its variants, while learning one to three orders of magnitude faster. Furthermore, the BDNN outperforms existing continual learning algorithms in the performance and speed. These results highlight BDNNs as a promising approach for continual learning and real-time edge computing applications. The source code of our work is publicly available at https://github.com/1jiaqixing/BDNNversion1

Shape Memory Polymers (SMPs) have emerged as adaptable and promising biomaterials in biomedical engineering, enabling innovative solutions for minimally invasive procedures and personalized therapies. This review presents a comprehensive overview of SMPs, focusing on their unique shape memory effects, tuneable material properties, and emerging biomedical applications. Unlike previous reviews that primarily focused on performance enhancement through conductive fillers or crosslinking strategies, this work highlights both the tailored modification of SMP characteristics and their functional integration within biomedical contexts. Key SMP types, such as poly(lactic acid), polycaprolactone, polyurethane, poly(methyl methacrylate) and bile acid-based polymers are critically evaluated with respect to their biocompatibility, biodegradability, and responsiveness to external stimuli. Moreover, biomedical applications such as controlled drug delivery, vascular stenting, dental devices, and tissue engineering are also discussed, with particular attention to recent advances and persisting challenges. Furthermore, the review identifies essential considerations for SMP selection, including mechanical robustness, physiological compatibility, and regulatory requirements. By synthesizing current developments and outlining emerging research directions, this article provides a framework to guide both researchers and clinicians in leveraging the full potential of SMPs for next-generation biomedical devices and therapeutic platforms.

This study presents a numerical analysis of thermoelectric generators (TEGs) integrated with a heat sink and phase change materials (PCMs), focusing on their combined impact on thermal management and power output. The module, comprising a bismuth telluride (Bi2Te3)-based TEG coupled with a paraffin wax PCM, was evaluated using finite element analysis across a range of PCM thicknesses. Results indicate that incorporating PCM effectively reduces the cold-side temperature during the melting process, thereby sustaining a more stable temperature gradient (ΔT) across the module. This leads to significant enhancement in the output power by maintaining a higher ΔT between the hot and cold junctions during the phase change process. As a result, the peak output power increased by approximately 3.5 times compared to a standalone TEG operating under identical conditions. While peak power magnitude varied only slightly with PCM thickness, the duration of peak output improved significantly from 60 s at 1 mm to 360 s at 3 mm. Among the configurations studied, a PCM thickness of 3 mm delivered the most effective balance between thermal buffering and power stability. These findings offer quantitative insights for the design of compact PCM-assisted TEG modules intended for operation under fluctuating thermal inputs.

Organic thermoelectric generators (TEGs) typically use in-plane thermoelement configurations with rigid electrodes, which limit temperature gradients (ΔT) and mechanical flexibility, thereby hindering their applicability for wearable applications. In this work, a flexible and stretchable TEG with an out-of-plane architecture is proposed, incorporating four pairs of p-type poly(3,4-ethylenedioxythiophene):polystyrene sulfonate and n-type single-walled carbon nanotube film-based thermoelements. The thermoelements are electrically connected via serpentine-patterned copper electrodes and encapsulated within a soft, skin-compatible Ecoflex elastomer substrate. The films were prepared using vacuum filtration and drop-casting techniques, while the electrodes and substrate were formed through laser patterning and three-dimensional printed mold, respectively. This structural design improves ΔT across the device while maintaining substantial mechanical durability and electrical stability under diverse deformation conditions. Experimental results indicate that the TEG generates an open-circuit voltage of ∼6.09 mV at a ΔT of 29.4 °C, corresponding to a maximum output power of ∼887.5 nW. The device retains stable functionality up to 289 mechanical stretch-release cycles and tolerates elongation up to ∼28 %. As a proof of concept, the TEG was tested on the wrist and dorsal hand, producing maximum output powers of ∼103 nW and ∼94.82 nW, respectively. These findings highlight the potential of the proposed TEG architecture for next-generation wearable energy harvesting applications.

In this paper, we propose an integrated model of the cell-based and pool-based spectrum handoff (SH) process of a non-stationary cognitive user (CU) under a heterogeneous spectrum environment (HetSE) in a 6G-enabled cognitive radio cellular network (CRCN). We model the Link Maintenance Probability (LMP) and Link Failure Probability (LFP) of the CUs under a Heterogeneous Spectrum Environment (HSE) with licenced and unlicensed spectrum pools. These performance measuring metrics are derived for various SH schemes: intracell/intrapool SH, intracell/interpool SH, intercell/intrapool SH, and intercell/interpool SH, considering the primary user (PU) activity model and CU mobility. Considering Dth as the waiting threshold period for CU, we analyze the effect PU's arrival rate and Dth on the performance measuring metrics in two different network architectures: Cognitive Radio-Vehicular Ad-Hoc Network (CR-VANET) and Cognitive Radio-Vehicular Centralized Network (CR-VCNET). In addition, we derive the LMP and LFP of a non-stationary CU in kth cell and compare the results among various cells. Further, we realize the effect of various service time distributions of PUs and CUs on the performance metrics, and lognormal service time distribution offers better SH performance as compared to the exponential and Erlangen distribution models. We also perform Monte-Carlo simulation for the performance measuring metrics to validate the proposed integrated SH model in CRCNs.

The design and development of a thermoelectric generator (TEG) with minimal internal resistance is crucial for achieving high output power in self-powered wearable technologies. This work presents a novel flexible TEG comprising single-walled carbon nanotube (SWCNT) thermoelements, fabricated through a sacrificial molding process. Different from the traditional TEG structural design, our TEG's {p}-and {n}-type SWCNT thermoelements are formed monolithically without any interconnections. This integration eliminates the presence of internal resistance within the device. Equipped with eight pairs of the {p}-and {n}-type SWCNT thermoelements, the TEG exhibits an open-circuit voltage ( {V}_{text {oc}}{)} of 21.82 mV and an internal resistance of sim 16.56~Omega & , corresponding to a maximum output power of approximately 7.19~mu text{W} at a temperature gradient (Delta {T}) of 50 °C. Additionally, the TEG demonstrated its capability to harvest energy from a fingertip, generating a {V}_{text {oc}} of around 2.58 mV at a Delta {T} of 8.8 °C. These results highlight the potential of the monolithically formed SWCNT thermoelements for achieving high-power density TEGs.

Strain sensors have garnered considerable interest, particularly in human motion and health monitoring, owing to their high stretchability and sensitivity. In this paper, resistive strain sensors comprising carbon black (CB)/Ecoflex and multi-wall carbon nanotube (MWCNT)/Ecoflex with high sensitivity and large mechanical strain are presented. These sensors were developed using solution casting and dip-coating techniques. In addition, toluene and acetone were used to enhance the adhesion of CB and MWCNT to the Ecoflex substrate, thereby increasing electrical conductivity, sensitivity, and flexibility of the sensors while maintaining their high stretchability. Toluene-treated strain sensors exhibited the highest sensitivity for both CB/Ecoflex and MWCNT/Ecoflex strain sensors. As a result, the CB/Ecoflex sensor with toluene treatment achieved the highest gauge factor (GF) of ∼1131, which is 19 times higher than the original samples without surface treatment. Meanwhile, a GF of ∼106 is exhibited by the MWCNT/Ecoflex sensor, with toluene treatment improving sensitivity by a factor of 2 over untreated samples. These promising findings demonstrate the potential and prospects for flexible and wearable sensor applications.

The development of a soft actuator with high displacement is crucial for the effective operation of micropumps, ensuring a high fluid pump rate. This study introduces an innovative approach by presenting the design and fabrication of a novel electrostatic-hydraulic coupled soft actuator for a micropump within a microfluidic system. This pioneering soft actuator, leveraging electrostatic-hydraulic coupling, showcases a unique solution to enhance the performance of micropumps. The versatility of such a soft actuator makes it particularly promising for biomedical applications. The actuator comprises dielectric fluid in an elastomeric shell and electrodes to form the out-of-plane fluid-amplified displacement. This displacement amplification was used to generate a pumping actuation in the micropump. The actuator was characterized in terms of dielectric fluid volume, electrode size, temporal response, and amplification displacement. The soft actuator showed a maximum amplified displacement of 0.51 mm at 10 kV of the applied voltage, but a higher voltage caused a dielectric breakdown. Moreover, the actuator demonstrated the ability to operate at frequencies of 0.25 Hz and 0.1 Hz. The results of the study indicate that the fabricated electrostatic-hydraulic coupled soft actuator is a dependable and effective method of actuation for a micropump in a microfluidic system. The experimental characterization of the micropump revealed a maximum flow rate of 2304 μl min−1

Rapid advancements in technology have facilitated the development of functional micro-electromechanical system (MEMS) actuators. The use of such actuators has recently witnessed a surge in a variety of biomedical applications, owing to their high precision and conformity. This review aims to provide a comprehensive survey of the recently developed MEMS actuators and their use in biomedical applications. In the context of these applications, we discuss the most appropriate and extensively used actuation techniques such as thermo-responsive, magnetic, piezoelectric, and soft actuation. In addition, state-of-the-art biomedical systems, tools, and devices are categorically reviewed with recently utilized actuation techniques, to provide insight into the prospects of implementation. The key parameters responsible for the enhanced performance and efficiency of the actuators were also addressed. Finally, the future research trends in actuation techniques for biomedical applications are discussed.

Estimating the performance of an optimally designed thermoelectric generator is essential for energy harvesting applications. This paper presents a numerical simulation of a thermoelectric generator consisting of vertically aligned p-type poly(3,4-ethylene-dioxythiophene):poly (styrene sulfonate) films and n-type aluminum wire-based thermoelements, using finite element analysis. It also determines the optimal length of the thermoelements to achieve the highest temperature gradient with the lowest internal resistance, resulting in improved thermoelectric generator output performance. The thermoelectric generator with five pairs of thermoelements produces a maximum open-circuit voltage of 3.22 mV at a temperature gradient of 50 °C. Following that, the generator provides a maximum output power of 2.54 μW and a power density of 394 nWcm-2, at a temperature gradient of 50 °C. The proposed design concept could result in a better temperature gradient as well as improved output performance.

Wearable sensors and biomedical devices have attracted a great deal of attention among users. Despite technological advancements in this field, a mixture of both progress and setbacks has been witnessed. The limited battery life of these devices for long-term operation remains a major challenge. In this context, thermoelectric generators have emerged as potential candidates for harvesting energy from temperature gradients to power wearable sensors and devices. This review focuses on the working mechanism of a thermoelectric generator, as well as the current progress of a variety of promising and widely used inorganic and organic thermoelectric materials. Encouragingly, the highest ZT values of 2.27, 2.5, 2.8, 2.3, and 1.85 are obtained for bismuth telluride, lead telluride, tin selenide, copper selenide, and magnesium antimonide, respectively, at various temperature ranges. Meanwhile, organic materials such as poly (3,4-ethylenedioxythiophene) polystyrene sulfonate, polyaniline composite, and graphdiyne showed the highest ZT values of 0.75, 0.74, and 4.8, respectively, at near-room temperature. Furthermore, numerous novel thermoelectric generator-powered wearable health monitoring sensors and Internet of Things devices are also presented. Finally, the current challenges and perspectives on the future development of thermoelectric generator, in particular for efficient materials and self-powered devices, are also discussed.

Surface acoustic wave (SAW) gas sensors with a nanostructured material-based sensing layer are highly desirable in microelectromechanical systems (MEMS) gas sensors to achieve improved sensitivity, time response, and recovery time. Herein, a novel SAW gas sensor with a nanostructured silicon (Si)-based sensing layer was developed. Finite element analysis was employed to determine the dimensions of the sensing material. Moreover, a SAW sensor with a four-pair input/output aluminium interdigital transducer (IDT) was fabricated and tested with carbon dioxide gas (CO2), with a concentration in the range of 500-2000 ppm. The results reveal that an Si nanostructure produces better sensitivity, and faster response and recovery time, compared to a layered Si-based SAW sensor. At 2000 ppm, a frequency shift of 4.62 kHz was recorded, while the time response and recovery time of 31 s and 40.5 s was reported, respectively. The proposed Si nanostructure as the sensing layer for the SAW gas sensor demonstrated significant performance with higher sensitivity than previously reported devices, and has the potential to act as a next generation MEMS SAW gas sensor.

Estimating the sensitivity of a surface acoustic wave (SAW) gas sensor accurately and effectively is essential for gas sensing applications. In this paper, the sensitivity of a SAW gas sensor without sensitive material, as well as with a sensing layer comprised of silicon and silicon nanowire arrays (SiNWA), are studied and analyzed via finite element method. Correspondingly, the effect of the length of the sensing material and the gas concentration on the SAW gas sensor sensitivity is being investigated. The proposed SiNWA-based SAW sensor showed high sensitivity at a length of 700 nm, owing to the high surface-to-volume ratio of sensing layer material. Meanwhile, it demonstrated a frequency shift of 270.3 kHz when exposed to a 5000-ppm carbon dioxide gas concentration through the sensing layer. Overall, the SAW gas sensor with SiNWA sensing layer provided significant sensing response.

Thermoelectric generators (TEGs) facilitate maintenance-free sustainable energy transduction, making them attractive and feasible options for self-powered wearable electronics. Nonetheless, their energy-conversion process suffers from inadequate design and rigidity owing to the use of brittle inorganic materials, making them inapt for wearable applications. Thus, the development of a TEG made of flexible materials with high deformability is required. In this study, a novel wearable TEG was designed and fabricated with vertically aligned p-type PEDOT:PSS and n-type SWCNT film-based thermoelements. Finite element analysis was used to optimize the thermoelement length, which was essential for enhancing the overall TEG output performance. This study also examined the effects of acid-based post-treatment and polyethylenimine concentration on the thermoelectric properties of PEDOT:PSS and SWCNT films, respectively. As a proof of concept, the proposed TEG, composed of five pairs of thermoelements, generated an open-circuit voltage of 1.75 mV while produced a maximum power and a power density of ~6.1 nW and 10.17 nWcm−2, respectively, at a ΔT of 11.24°C by harvesting energy from the wrist. The proposed design represents a significant step toward developing a next-generation flexible organic TEG that can pave the way for self-powered wearable electronics in a sustainable manner utilizing body heat.

Energy harvesting technology has become important for wearable electronics, where a continuous power supply is essential. Although a wearable thermoelectric generator (TEG) is a promising option in this context, maintaining a substantial temperature gradient (ΔT) between the hot and cold sides of the TEG and a low thermal contact resistance between the TEG and the human body is challenging due to its structural configuration. Herein, a novel structural solution to these problems has been presented with vertically aligned p-type poly (3,4-ethylene-dioxythiophene):poly (styrene sulfonate) (PEDOT:PSS) thin film and n-type aluminum wire-based thermoelements integrated wearable TEG. The developed wearable TEG with five pairs of thermoelements reported an open-circuit voltage (Voc) of up to 1.46 mV when applied to the wrist. Subsequently, the generator was tested at a higher temperature, and the characterization results revealed that the TEG produced a maximum Voc of 5.15 mV at a ΔT of 80 °C. Inclusively, the TEG provided a maximum output power and an output power density of ∼2.4 nW and 1.5 nWcm−2, respectively, at a ΔT of 80 °C. The proposed TEG design concept demonstrates elevated performance with great flexibility and has the potential to act as a viable alternative for next-generation energy harvesting devices.

Surface acoustic wave (SAW) gas sensors with nanostructured material-based sensing layers are desirable in gas sensing owing to their high sensitivity, and their fast response and recovery time. In this work, a novel SAW gas sensor with a nanostructured silicon (Si)-based sensing layer with four pairs of aluminum-based input and output interdigital transducer (IDT) is developed and fabricated. A finite-element analysis (FEA) is used to determine the sensitivity while varying the height of the nanostructured Si. As a proof of concept, the SAW sensor is tested for carbon dioxide (CO2) gas concentrations, ranging from 500 to 2000 ppm. The results demonstrate that the developed SAW sensor with a nanostructured Si-based sensing layer showed a maximum frequency shift of 4.62177 kHz with a response and a recovery time of 31 and 40.5 s, respectively, for a 2000-ppm CO2 gas concentration. The developed nanostructured Si as a sensing layer for the SAW gas sensor demonstrated higher sensitivity than previously reported devices and has promising potential to be used as a sensing layer for next-generation MEMS SAW gas sensors.

Silicon (Si) micromachining techniques have recently witnessed significant advancement, attributable to the high surge in demand for microelectromechanical and microelectronic devices. Micromachining techniques are widely used to cut or pattern Si, in order to obtain high-quality surface finishes for the fabrication of devices. Micromachining techniques are used for the fabrication of three-dimensional (3D) microstructures for microelectromechanical devices. In this work, the capabilities and competencies of non-traditional Si micromachining techniques, including ultrasonic, ion beam milling, laser machining, and electrical discharge machining, are discussed and compared accordingly. The working principles, advantages, limitations, and Si microstructures that have been fabricated before are discussed in detail. Additionally, this work covers the performance reported by multiple researchers on these micromachining methods, spanning the temporal range of 1990 to 2020. The key outcomes of this study are explored and summarized.

Harvesting human wrist heat with a thermoelectric generator (TEG) has received prominence, which has the ability to power portable electronic devices. This paper presents a study and analysis of a bismuth telluride-based TEG for human wrist heat harvesting. The performance of the TEG was evaluated using the finite element analysis method. The actual heat harvesting environment from the human wrist was developed during the simulation. Based on the analysis, an output voltage and power of 40.7 mV and 4.245 mW, respectively, were obtained from the proposed TEG module at a temperature gradient of 12.5 K. Besides, the generator was able to produce a maximum power efficiency factor of 0.66 μWmm-2K-2. The output of the developed wearable TEG could be improved by employing more thermocouples, which can potentially be used to power devices.

Accurate and effective performance estimation of thermoelectric generators with optimized structure is essential for large-scale energy harvesting applications. This paper aims to study and analyze a bismuth telluride-based thermoelectric generator using finite element analysis. The impact of thermoelements length and area on obtaining an optimal temperature gradient, output voltage generation, and maximum output power is investigated. The proposed thermoelectric generator module, which is consisted of eight pairs of p-type and n-type bismuth telluride thermoelements, produced an optimum temperature gradient and output voltage of 96.6 mV with each thermoelement length of 8 mm and area of 1 mm2. In addition, the effect of varying thermoelements area with optimal length on thermoelectric generator performances is also presented. These outcomes could be utilized to fabricate a bismuth telluride-based thermoelectric generator with optimized thermoelements.

Silicon (Si) wafers are primary substrate materials in the microelectronic and microelectromechanical area because of its superior properties, which can be adjusted. In this chapter, we first provide an overview of the electrical discharge machining techniques. In addition, the capability and performance results of electrical discharge machining techniques for machining three-dimensional cavities on Si with optimum parameter settings are also discussed. The machining performance results of Si with two-different resistivities are discussed using a die-sinking micro-electrical discharge machining technique while varying discharge energy parameters. Moreover, a novel heat-assisted micro-electrical discharge machine technique is performed for machining Si without any conductive layer involved. The machining performance results are presented and discussed in terms of material removal rate, surface quality and materials characterization. Finally, the chapter concludes by discussing the main outcomes of the machining performance.

Shape-memory alloys (SMAs) have received a great deal of interest due to their excellent properties, which make them significant for various applications. Despite its unique properties, the processing of these alloys is often challenging as it endures a solid-state transition. This chapter thus aims to explore non-conventional machining techniques such as laser beam machining (LBM), electrical discharge machining (EDM) and its associated techniques for the processing of these alloys without altering their intrinsic properties. Both the techniques are discussed in terms of their working mechanism and contribution to the processing of SMA alloys. In addition, the use of EDM processed SMA alloys in various actuators, in particular micromanipulator, micro-positioning stage and tunable coil, is also discussed. Finally, it concludes by discussing the main outcomes of the chapter.

Energy harvesters (EHs) are widely used to transform ambient energy sources into electrical energy, and have tremendous potential to power wearables electronics and biomedical devices by eliminating, or at least increasing, the battery life. Nevertheless, the use of EHs for a specific application depends on various aspects including the form of energy source, the structural configuration of the device, and the properties of materials. This paper presents a comprehensive review of the classification of EHs, notably thermoelectric generators (TEGs), triboelectric nanogenerators (TENGs), and piezoelectric generators (PEGs) that allows a wide variety of devices to be operated. The EHs are discussed in terms of their operating principles, optimization factors, state-of-the-art materials, and device structure, that directly influence their operational efficiency. Besides, the breakthrough performance of each of the EHs listed above is highlighted. From the review and analysis, the maximum output power density of 9.2 mW cm−2, 50 mW cm−2, and 64.9 µW cm−2, respectively, are obtained from the TEG, TENG, and PEG, respectively. Furthermore, recent applications relevant to a specific EH and their output performance, are also enlightened. Eventually, the essential outcomes and future direction from this review are discussed and encapsulated.

Micro-electromechanical system (MEMS) gas sensors represent a system that is capable of detecting the existence and concentration of gasses in the atmosphere. These sensors have become incredibly popular and have been widely used in a variety of fields, including the biomedical field. Over the years, several gas sensors have been developed to detect and analyze a wide range of gases. As sensor applications are expected to be further extended in the near future, it is, therefore, essential to review crucial types of gas sensors, their features, challenges, and a range of important applications. This paper presents a comprehensive review of the state-of-the-art gas sensors, which have been developed for gas sensing applications using MEMS technology. The working principle, the structure, the sensitive material and the important characteristics of each of these sensors are discussed. The focus of this review is on applications surrounding the use of electrochemical, optical and acoustic gas sensors for biomedical applications.

This paper presents the modelling and simulation of a π-shaped Mg3Sb2 based thermoelectric generator. The performance of the proposed thermoelectric generator is evaluated with finite element analysis. A number of thermocouples were varied for high output power and power efficiency factor. Based on the analysis, we demonstrated that enhancement of the temperature gradient and the number of thermocouples are beneficial for high output power and power efficiency factor of Mg3Sb2 based thermoelectric generator. A high output power and power efficiency factor of 8.89 mW and 3.47 mWmm-2K-2 were obtained at a temperature gradient of 500K across the hot and cold side for four Mg3Sb2 based thermocouples, respectively. The obtained results show that the developed device could be used to drive portable electronic devices.

Micro-electromechanical-system (MEMS) based actuators, which transduce certain domains of energy into mechanical movements in the microscopic scale, are increasingly contributing to the areas of biomedical engineering and healthcare applications. They are enabling new functionalities in biomedical devices through their unique miniaturized features. An effective selection of a particular actuator, among a wide range of actuator types available in the MEMS field, needs to be made through the assessment of many factors involved in both the actuator itself and the target application. This paper presents an overview of the state-of-the-art MEMS actuators that have been developed for biomedical applications. The actuation methods, working principle, and imperative features of these actuators are discussed along with their specific applications. An emphasis of this review is placed on temperature-responsive, electromagnetic, piezoelectric, and fluid-driven actuators towards various application areas including lab-on-a-chip, drug delivery systems, cardiac devices and surgical tools. It also highlights the key issues of MEMS actuators in light of biomedical applications.

Thermoelectric generator, which converts heat into electrical energy, has great potential to power portable devices. Nevertheless, the efficiency of a thermoelectric generator suffers due to inefficient thermoelectric material performance. In the last two decades, the performance of inorganic thermoelectric materials has been significantly advanced through rigorous efforts and novel techniques. In this review, major issues and recent advancements that are associated with the efficiency of inorganic thermoelectric materials are encapsulated. In addition, miscellaneous optimization strategies, such as band engineering, energy filtering, modulation doping, and low dimensional materials to improve the performance of inorganic thermoelectric materials are reported. The methodological reviews and analyses showed that all these techniques have significantly enhanced the Seebeck coefficient, electrical conductivity, and reduced the thermal conductivity, consequently, improved ZT value to 2.42, 2.6, and 1.85 for near-room, medium, and high temperature inorganic thermoelectric material, respectively. Moreover, this review also focuses on the performance of silicon nanowires and their common fabrication techniques, which have the potential for thermoelectric power generation. Finally, the key outcomes along with future directions from this review are discussed at the end of this article.

This review is focused on state-of-the-art thermoelectric materials (or thermoelements), from which the thermoelements with the highest figures of merit (z) along with the those having the greatest research interest and findings were surveyed and analyzed. These were in addition to the statistical analyses made in this review for categorizing z achievement ranges for all types of thermoelements. Almost 56% of positive thermoelements and 39.6% of negative thermoelements were discovered from 1950 to 2017, and a total of 62.2% of thermoelement research findings were reported in 2010–2017. Furthermore, nearly 47.65% of the discovered thermoelements preserved z in the range of 1–4.99 × 10−3 K−1, and only about 2.52% possessed less than 9.9 × 10−6 K−1. Chalcogenide was the major type of thermoelement studied to date, with overall representation of 37.2%. Nearly 68.9% of chalcogenide thermoelements were capable of reach 1–4.99 × 10−3 K−1, while 53% of metal oxide thermoelements ranged within 0.1–0.499 × 10−3 K−1. Nanostructure thermoelements achieved the highest z of 47 × 10−3 K−1 and 17 × 10−3 K−1 at 300 K, for Bi2Te3 quantum wires and Bi2Te3 quantum wells, respectively. Correspondingly, hybrid and conducting polymer thermoelements also reached z as high as 16 × 10−3 K−1 at 300 K for positive thermoelement: nano-Ag/regioregular poly(3-octylthiophene-2,5-diyl) and negative thermoelement: graphdiyne.

Thermoelectric generator is among the earliest initiated electricity-harvesting methods. It is a very potential power harvester that can convert wasteful thermal energy into electricity. However, it often suffers from low energy conversion rate due to its inconsistent heat source, inefficient thermoelectric material (or thermoelement) performance, and incompetent structural issues. Progressively for the first time, detailed methodological surveys and analyses are made for bulk, thick, and thin films in this review. This is in order to accommodate better insights and comprehensions on the emerging trends and progresses of thermoelectric generators from 1989 to 2017. The research interests in thermoelectric generators have started back in 1989, and have continuously experienced emerging progresses in the number of studies over the last years. The methodological reviews and analyses of thermoelectric generator showed that almost 46.6% of bulk and 46.1% of thick and thin film research works, respectively, are actively progressed in 2014 to 2017. Nearly 86.2% of bulk and 44.1% of thick and thin film thermoelectric generators are realizing in between 0.001 and 4 μW cm−2 K−2, while 43.1% of thick and thin films are earning among 10−6 to 0.001 μW cm−2 K−2. The highest achievement made until now is 2.5 W cm−2 at a temperature difference of 140 K and thermoelectric efficiency factor of 127.55 μW cm−2 K−2. This achievement remarked positive elevation for the field and interest in thermoelectric power generation. Consecutively, the research trends of fundamental devices' structure, thermoelement, fabrication, substrate, and heat source characteristics are analyzed too, along with the desired improvement highlights for the applications of thermoelectric generators.

The design, analysis, optimization, and fabrication of layered and nanostructure-based surface acoustic wave (SAW) gas sensors are presented. A lithium niobate and zinc oxide (ZnO) nano multilayer structure is proposed to enhance the sensitivity of the SAW-based gas sensor. Different materials are considered for the intermediate layer in the design for optimization purposes. The sensitivity of the sensor could be improved due to increased active surface area obtained by varying the aspect ratio of the nanorods, the thickness of the intermediate layer, and the gap between the electrodes. The total displacement and frequency shift of the device were significantly improved. Overall, the mechanically engineered surface-based (nanorod) SAW gas sensor offered better sensing response than the layered SAW gas sensor in terms of sensitivity performance.

Radar evasion or Stealth is a technology most desirable among all the military research areas currently pursued. Research organisations have focused their attention on electronic stealth technology or cancellation of waves since it is feasible now due to the improvement of high end processing and fast electronic systems. In an attempt to increase our understanding of this field, we have analysed the phenomenon through computer aided simulation. In this paper, we have created an electromagnetic wave simulation platform and using finite difference time domain method, analysed a method of active cancellation. We have found results showing complete effectiveness of this method assured by the accuracy of FDTD method.

This paper presents design, simulation and analysis of a platinum (Pt) based micro-heater for gas sensing applications. Finite element method (FEM) analysis is employed for the purpose of performing the tasks mentioned above thereby investigates the various properties of the high resistive material platinum (Pt) using COMSOL Multiphysics. The Micro-heater is principally designed to ensure minimum power consumption, low thermal mass and better temperature uniformity. Furthermore, the effect of variation of thickness of heating element with created temperature and power consumption of the MEMS micro-heater is observed and evaluated.