The demand for lightweight energy-absorbing structures has rapidly increased. Auxetic structures, such as re-entrant honeycombs, exhibit negative Poisson’s ratio behavior and high impact stability; however, their compressive response is highly nonlinear and sensitive to geometric parameters, making them computationally expensive and design inefficient. In this study, we present an end-to-end machine learning design acceleration framework for a quasi-2D re-entrant honeycomb that integrates PyAnsys Geometry and PyMechanical. The proposed framework employs automated geometry generation and finite element analysis (FEA) to build a dataset (n = 40) for interpretable surrogate modeling and covariance matrix adaptation evolution strategy optimization. Experimental validation was conducted using printed digital light processing specimens. An ensemble surrogate model (combining polynomial regression and gradient boosting regression) achieved the best 5-fold cross-validated performance (R² = 0.729). Surrogate-based optimization yielded an optimal design that increased energy absorption density (EAD) in refined-mesh FEA by 63.6
Triboelectric nanogenerators (TENG) are emerging as promising solutions for decentralised energy generation due to the growing need for sustainable power sources. These devices convert wasted mechanical energy into electricity under ambient conditions, offering advantages such as eco-friendly operation, material versatility, and effective energy scavenging. Despite these benefits, their relatively low electrical output compared to conventional sources like batteries and fuel cells remains a limitation. Microalgae have attracted attention for their ability to produce bioelectricity through photosynthesis and respiration while simultaneously capturing carbon dioxide. Immobilising microalgal cells on conductive substrates improves electron transfer and metabolic activity. In this context, living Chlorella vulgaris TISTR 8580 with varied cell densities was immobilised on aluminium electrodes and incorporated into a TENG platform to explore energy harvesting from solid-solid and solid-liquid interactions. The highest output of 110 V and 330 nA was generated, confirming the microalgae as a promising tribolayer and extending the conventional triboelectric series. However, sustaining cell viability over extended periods remains a challenge, highlighting the need for optimised light and nutrient conditions in future developments.
Freeze-casting-assisted direct ink writing (DIW) enables the fabrication of three-dimensional (3D) aerogel architectures with improved geometric versatility. However, multilayer deposition often produces inter-layer microstructural nonuniformity because the pre-frozen underlying layers introduce additional thermal resistance. To address this challenge, we investigated a homogeneous solidification strategy using a computational fluid dynamics (CFD) model. The framework incorporates a moving substrate boundary condition, constant-temperature thermal boundary, and interface tracking, while the nanocomposite ink properties are explicitly modeled as functions of temperature and shear rate. Using the CFD results and a custom digital image-processing algorithm, the freezing time required for the extruded filaments to fully solidify on a cold substrate is quantified. Based on the extracted freezing-time data, we determined the substrate-temperature pairs that yield identical freezing times across sequential layers. The resulting process map provides practical guidelines for mitigating layer-to-layer thermal variations and enables the reliable printing of aerogels with uniform inter-layer microstructures.
Multi-walled carbon nanotubes (MWCNTs) have emerged as promising sensing materials due to their advantages such as room-temperature operation, durability, large-area coating capability, and tunable electrical properties. While considerable research has focused on surface modification of CNTs, the influence of the contact area between the sensing material and the electrode has largely been overlooked. In this study, we systematically investigated the effect of contact area on the sensing performance of MWCNT-based ammonia gas sensors. Sensors with different contact areas were fabricated, and the resistance changes under ammonia gas exposure were measured. The results showed that the response characteristics increased sharply up to a contact area of 10 mm2, followed by a gradual saturation trend. Analysis of the response rate per unit area revealed that the most efficient contact area was around 14 mm2. This behavior can be attributed to the percolation threshold effect, which induces a steep resistance change at very small contact areas, and the dominance of parallel resistance behavior at larger areas, leading to a gradual decrease in slope.
As semiconductor processes scale down to sub-10 nm nodes, airborne molecular contaminants (AMCs) have become critical factors affecting product yield and quality. Conventional analytical techniques face limitations in implementing real-time, multi-point monitoring across increasingly large cleanroom facilities due to high costs and spatial constraints. As an alternative, chemoresistive gas sensors have gained significant attention owing to their high sensitivity, cost-effective design, and facile electronic integration. This review highlights the impact of AMCs on device performance in semiconductor manufacturing environments and systematically summarizes the latest sensing strategies for each AMC group, including acidic, basic, and other species, such as volatile organic compounds (VOCs). By integrating research on chemoresistive sensors in environmental monitoring and safety applications, it also presents comprehensive strategies for developing high-performance sensors applicable to the semiconductor industry. Finally, the review discusses both the potential and the remaining technical challenges of implementing real-time AMC monitoring systems in future semiconductor manufacturing environments.
Heavy metal ions (HMIs), such as mercury (Hg), lead (Pb), cadmium (Cd), arsenic (As), and chromium (Cr), are a serious environmental issue due to their toxicity, bioaccumulation, and long-term persistence, making it necessary to develop sensitive and selective detection technologies. Laboratory-based methods, such as atomic absorption spectroscopy, provide high accuracy, but their point-of-need deployment is limited by their reliance on large equipment and complicated sample preparation. This review highlights the critical role of nanomaterial in sensing platforms in overcoming these limitations and advancements across electrochemical and optical detection techniques. The integration of nanomaterials-including carbon-based, metallic-based, silicon-based, and quantum dots-is shown to significantly enhance sensor performance through increased surface area, electron transfer efficiency, and plasmonic effects. Despite this progress, challenges such as matrix interference, ensuring signal reproducibility, and developing scalable fabrication methods remain. Future research will focus on developing hybrid, multiplexed, and antifouling sensor architectures integrated with digital technologies like the Internet of Things (IoT) to realize next-generation, ultra-sensitive HMIs monitoring platforms.
We propose a quantitative metric, the Index of Vibration Influence (IVI), to assess how external random vibrations affect resonant MEMS scanning mirrors that embed a mirror-angle sensor. The setup excites the mirror with PSD-specified random profiles while the mirror is driven near its resonant frequency. The IVIo, which quantifies vibration‑induced scan‑angle perturbations, is defined at the operating frequency (fo), as the ratio of the mirror-angle spectra influenced by external vibration to those without random vibration. We validate the linearity error of the embedded sensor as small as 1.25
Laser micromanufacturing is an emerging technique that holds significant implications in a variety of sectors, including biomedical engineering, additive manufacturing, sensors, industrial manufacturing, and microfabrication technologies. The key advantage is the precision as well as efficiency it provides when creating micro and nanostructures, which are becoming more and more important for modern-day applications. As laser microfabrication enables maskless processing, it lowers setup times and costs. It offers an easier alternative to fabricate complicated geometries and conduct rapid prototyping compared to conventional photolithography techniques. Several research works have been reported in this field in the last two decades. However, a major limitation of many of these research works is the fact that they use expensive laser sources such as ultrafast femtosecond lasers. Though femtosecond lasers provide several advantages, it is often not a cost effective method for micromanufacturing. In contrast, low power laser micromanufacturing platforms offer several economic advantages from an industrial point of view such as minimized capital investment, low maintenance costs, and sustainable production due to reduced energy consumption. In this review, we specifically examine cost effective, low power laser micromanufacturing techniques, recent advancements in this field, and future perspectives.
Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants whose remarkable chemical stability and bioaccumulative nature pose significant environmental and health concerns. Conventional analytical techniques such as liquid and gas chromatography–mass spectrometry (LC-MS and GC-MS) offer excellent sensitivity and specificity but remain costly, labor-intensive, and unsuitable for rapid field deployment. Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a promising micro/nano-enabled technology for real-time, label-free, and ultrasensitive detection of PFAS in aqueous systems. This mini-review provides a critical overview of current advances in nanostructured SERS platforms, emphasizing the mechanisms of PFAS–surface interactions, rational design of metallic and hybrid substrates, and progress toward miniaturized and microfluidic detection schemes. Persistent challenges, including limited adsorption affinity, spectral interference, and substrate reproducibility, are analyzed alongside emerging strategies such as surface functionalization, hierarchical nano-structuring, and data-driven spectral interpretation. Finally, future perspectives highlight the integration of SERS with machine learning and scalable fabrication to enable portable, field-deployable environmental sensors. Therefore, the review underscores the potential of SERS as a next-generation analytical tool for sustainable PFAS monitoring and environmental protection.
Low-cost preparation of nanostructured materials is one of the important factors for the commercialization of sensors. This study reports the sustainable and low-cost synthesis of pure SnO2 and SnO2-CuO nanostructures using a domestic microwave annealing approach. The material obtained was structurally examined using X-ray diffraction and a scanning electron microscope. The pure SnO2 and SnO2-CuO inks were deposited over laser-induced graphene interdigitated electrodes. Towards the volatile organic compounds, the pure SnO2 and SnO2-CuO went through ethanol sensing. The SnO2-CuO-based sensor demonstrated strong response and selectivity for detecting ethanol at room temperature with a response of 11
This paper demonstrates a simulation-based analysis of highly sensitive gas sensor design to detect the Chloroform gas based on an advanced Gate All Around Junctionless MOSFET (GAA-JLMOS). In this design, traditional polysilicon gate is replaced with Iridium-Rhodium/Palladium nano-composite (Ir-Rh/Pd) which is responsible for a linear shift in gate work-function in presence of chloroform gas. The work-function modification results into the changes in drain current (Id) and threshold voltage (Vth), showing a reliable detection from no gas to 50 ppm CHCl3concentrations by MOS sensor. Additionally, the subthreshold swing optimization leads to faster switching and response times. The simulation results showa significant improvement in the sensitivity of proposed sensor compared to conventional MOS based designs. This manuscript proposes better selectivity towards the detection of chloroform vapors compared to the existing MOS based gas sensors. The simulation results meet a 2x times increase in threshold voltage and 100x times reduction in the leakage current from no gas to 50 ppm concentration of CHCl3. The proposed GAA-JLMOS shows high sensitivity, low leakage current, and enhanced scalability, providing a possible pathway toward next-generation nanoscale gas sensors. An ATLAS 3D TCAD simulator is used for the sensor design and simulations.
Water-based triboelectric nanogenerators (TENGs) have recently attracted attention as promising solutions for distributed micro energy harvesting. These devices provide a way to provide sustainable power to low-power electronics and self-driving sensors by converting the kinetic energy of water droplets, flowing water, and sea waves into electricity through contact electrification and electrostatic induction. This review provides a comprehensive overview of recent progress focused on the working mechanisms, structural design, and performance improvements in various water environments of water-based TENGs. Key mechanisms such as bulk-effect water droplet-based electricity generation and electrode ground capacitance are summarized. Finally, we discuss current challenges and prospects for scalable and durable self-driving systems, along with their potential applications in environmental monitoring, wearable electronics, and marine sensing.
This paper examines the feasibility of using an AC Joule-heated stainless-steel (SS304) suspended microtube as a combined heater/thermometer to identify the thermal conductivity k_l and volumetric heat capacity (ρ c_p)_l of nanoliter-scale liquids, including electrically conducting liquid metals. The analysis builds on the 3ω technique, wherein a sinusoidal drive at frequency f produces temperature oscillations at 2ω and a third-harmonic voltage V3ω carrying the sample’s thermal signature. A first-order axial heat-flow model is formulated for a circular microtube and extended to treat two electrical boundary conditions inside the tube: (A) a conformal inner insulator (no electrical shunting through the liquid) and (B) direct electrical contact to a conductive liquid, which creates a parallel electrical path and modifies both Joule power and effective temperature coefficient of resistance. This study outlines an identification workflow for k_l , (ρ c_p)_l from the complex V3ω(f), discuss implementation constraints, and present representative spectra computed for real liquids and for a high-k liquid metal (NaK). The results indicate that, after calibration, the insulated case can recover k_l , (ρ c_p)_l from frequency response alone, and that even when the liquid is electrically conducting, the degradation in signal can be modeled and corrected if the parallel conduction is characterized.
This paper presents the design and performance evaluation of an optical energy harvesting system for a wireless actuated micro-electro-mechanical system (MEMS) The latter consists of an antagonistic double beam and two active shape memory alloy elements (SMA: 3*1*0.1 mm^3 ) responsible for actuating the beams among the two stable positions, when heated by a laser diode. The research focuses on harvesting the unused laser energy using a vertical multi-junction photovoltaic cell (PV cell: 3*3*0.4 mm^3 ). To extract the maximum efficiency, the energy harvesting system is optimized by homogenizing the laser beam using an N-BK7 light pipe homogenizing rod. The uniformity test is validated experimentally by using an optoelectronic system able to move along the output and measure the power on different zone of the surface; resulting a percentage of uniformity ( across a surface of 3.5*3 mm^2 , with a standard deviation of ± 3 W/cm^2 , resulting a maximum power of 25.2 mW with a fill factor of 84 37.4 mJ for the first cycle. This cycle is repeated 50 times to calculate the cumulative amount of energy harvested then 300 times to charge 90
Semiconductor-based ion-trap chips are a leading platform for scalable quantum computing, but their performance is often limited by photogenerated charge carriers accumulating on exposed silicon surfaces. In this work, we present a comprehensive fabrication process for silicon-on-insulator (SOI) wafer–based ion-trap chips that addresses this challenge through optimized scallop smoothing and angled gold evaporation. We compare two scallop smoothing methods–frontside reactive ion etching (RIE) and backside RIE–and develop optimized process recipes for each using iterative test structures. Backside RIE smoothing achieves near-complete scallop removal with minimal undercut, while frontside RIE smoothing, although requiring tighter control to minimize undercut, remains viable when preservation of the buried oxide (BOX) layer is necessary. The use of SOI substrates ensures consistent device-layer thickness by leveraging the BOX as an etch-stop layer during backside deep RIE, further enhancing the reproducibility of smoothing. Finally, angled gold evaporation following the scallop smoothing process yields uniform gold coverage on vertical sidewalls without causing electrical shorts between electrode structures. Scanning electron microscopy confirms clean sidewalls and defect-free gold films. These process improvements suppress semiconductor charging, stabilize ion confinement, and enable reliable, high-fidelity quantum operations in quantum charge-coupled device architectures.
Microphysiological systems (MPS) have shown their capabilities in mimicking in vivo-like structural and functional complexity and are seeing significant increase in their utilization in the field of drug discovery and toxicology. However, the major time-consuming steps in the fabrication, utilization, and analyses of MPS devices limit the throughput for broader adoption. Here, we advanced the previously developed two-chamber MPS model of the female reproductive tracts from a single unit chip to an array type chip that is compatible with multi-channel pipettor or automated liquid handling robot for rapid and more efficient operation. To enable this array model, a new microfabrication method was developed, incorporating a microplate holder, bonding guide plate, and soft lithography cassette to minimize device-to-device variation. To validate its compatibility with multi-channel pipettors in chemical toxicity testing, cadmium, a chemical previously shown to elicit cytotoxicity in the two-chamber feto-maternal interface MPS model, was utilized to demonstrate highly uniform cell loading (variance < 100 cells/mm(2)) and consistent dose-dependent cytotoxic response. Additionally, a liquid handling robotic system was also utilized, with no operational errors such as air bubble introduction (zero bubbles out of 100 devices) during cell/chemical loading process, and no unintended cytotoxic effects (> 97% viability). These results highlight that this automation-compatible array type MPS device can provide highly consistent cell culture performance and significantly reduced chip-to-chip and operation-to-operation variations, overcoming the limitations of typical MPS devices.
This review provides a comprehensive survey of contemporary strategies for minimizing signal crosstalk in resistive temperature sensors, with particular focus on engineering approaches that achieve strain insensitivity. The discussion is structured to parallel the central themes of material selection, geometric structural design, and post-fabrication processing. First, the review categorizes conductive materials, including carbon-based nanomaterials, metallic nanostructures, and conductive polymers, highlighting how their intrinsic properties and structural forms determine sensor performance in terms of conductivity, flexibility, and mechanical robustness. The role of geometry-inspired designs, such as serpentine, multipolygonal, and Kirigami architectures, in enhancing mechanical compliance and contributing to the decoupling of thermal and mechanical signals is examined. Additionally, recent advances in post-fabrication processes, including welding, soldering, and surface treatments, are evaluated for their roles in maintaining long-term electrical stability and device reliability. By systematically integrating these multidisciplinary engineering strategies, this review delineates practical design principles for the advancement of next-generation resistive temperature sensors and provides a foundation for the robust integration of flexible electronics into a broad spectrum of emerging application domains. These insights are expected to accelerate innovation in wearable technology and other emerging fields, paving the way for the development of reliable, high-performance, flexible sensing systems.
Bone regeneration remains a critical challenge, especially in complex defects where conventional pharmacological and surgical treatments are inadequate. This review critically evaluates recent progress in micro- and nanoscale biomimetic scaffold systems and stem cell technologies, highlighting how structural design at the micro/nano level directly influences stem cell fate and osteogenesis. We analyze advances in fabrication techniques including 3D bioprinting, electrospinning, and micro/nanofabrication that enable hierarchical porosity, controlled surface nano-topographies, and dynamic biochemical environments. Particular attention is given to structure–function relationships, where scaffold mechanics, biochemical cues, and spatial patterning govern mesenchymal stem cell (MSC) adhesion, proliferation, and differentiation. Unlike conventional descriptive accounts, this review emphasizes both the therapeutic potential and the unresolved limitations of current approaches, such as reproducibility, host integration, and immunomodulation. Finally, we outline future perspectives in AI-driven scaffold design, and smart biomaterials, providing a roadmap for the translation of biomimetic scaffold–stem cell systems into clinically effective bone regeneration strategies.
For more than five decades, vibrating tube resonators have evolved from fragile laboratory devices into versatile platforms used in industrial metrology, biomedical research, and education. This technology originated with glass U-tube densitometers, which established the foundation for resonance-based density measurements. Later, metallic tubes extended operation to harsh conditions, including high pressure, elevated temperature, and cryogenic environments, enabling applications ranging from supercritical fluid studies to aerospace propulsion. The vibrating tube principle also inspired Coriolis flowmeters, which can monitor both density and mass flow. Miniaturization through microelectromechanical systems (MEMS) has led to microchannel resonators that can weigh biomolecules, nanoparticles, and cells with high sensitivity. Subsequent innovations improved readout using piezoresistive and piezoelectric schemes, increased throughput with array architectures, and integrated heaters for thermal property measurements. More recent advances include integrating capacitive electrodes, enabling access to electrical and dielectric properties of liquids. Meanwhile, renewed interest in glass and metallic tube resonators has highlighted their robustness, scalability, and utility for handling larger biological entities and for educational purposes. Macro- and micro-scale approaches complement each other, ensuring continuity across scales and pointing toward future integration with optical, magnetic, and quantum modalities.
Nanofillers are one of the most important additives in the creation of natural fibre reinforced polymer composite (NFRPC), as they greatly improve the properties of the material even at low doses. Such Nanofillers enhance the bonding of fibers and matrix that result in an increase of the mechanical and functional properties of composite. Clays, nanomaterials of carbon, metal and metal oxide nanoparticles, cellulose nanocrystals are some of the most prevalent Nano fillers. NFRPC, with the current advantages of low cost, renewability, biodegradability, and desirable specific properties, have taken off as an alternative to synthetic composites in biomedical applications. Although such composites present the advantage of desirable mechanical strength, thermal stability, and acoustic performance, the addition of Nanofillers enhances the performance further by increasing structure-property associations and processing. Also, Nano filler-enhanced composites have a promising biomedical future, especially when used in tissue engineering, wound healing, antimicrobial systems, and load bearing implants. The review is a compilation of recent developments of natural and synthetic nano filler applications in combination of natural fibers and is therefore a complete reference to any researcher or scientist who will be interested in designing high-performance composites by the synergistic combination of fibers, polymer matrices, and Nanofillers.
