Microsystems & Nanoengineering最新文献

Topological insulator originally found in electronic systems has inspired an analogue in phononic crystals, which has revolutionized fundamental concepts of elastic and acoustic transmission, offering one-way propagation edge modes immune to backscattering. Nevertheless, for traditional topological phononic crystal (TPC), once the structure is made, only a particular bandgap frequency can occur. Realization of reconfigurability and frequency tuning of topological one-way transmission is challenging. To solve the problem, the TPC is made active on penetration with thermosensitive acoustic hydrogels to produce a reconfigurable bandgap of acoustic wave. We explore that at a certain frequency range, the topological edge state (TES) within the TPC can be reversibly turned on/off as changing the state of (vinyl alcohol) poly-N-isopropylacrylamide (PVA-PNI-PAm) hydrogel between hydrophilic and hydrophobic. In addition, the topology of the TPC does not vary as the TES was tuned by varying the sound group velocity of PVA-PNI-PAm rather than the structural geometry. Such a feature enables a continuous tuning of the central frequency of phononic bandgap and TES by gradually changing the state of PVA-PNI-Pam. The state transition of PVA-PNI-Pam thermal-acoustic hydrogel from hydrophilic to hydrophobic and vice versa has been experimentally realized. Our proposed proof of concept may provide a platform for intelligent acoustic devices with dynamically programmable and reconfigurable functionalities, leading to various potential applications in acoustic wave guiding and control, integrated acoustics, acoustic security, and information processing etc.

Peripheral blood circulating glioma cells (CGCs) are crucial for glioma screening, prognostic evaluation, and diagnostic applications. However, reliable methods for efficient CGCs capture and comprehensive clinical evaluation on whether CGCs could faithfully represent complicated heavy equipment (such as MRI) remain insufficiently explored. Here, we present an antibody modification and size screening-based microfluidic (ASM) chip for effectively capturing CGCs, specifically designed for potential clinical translational applications. The ASM chip consists of one inlet, three outlets, one white blood cell clearance area, and one CGC capture area. The performance of the chip was optimized with two typical cell subtypes, namely SU-DHL-4 (to simulate leukocytes) and U251MG-ZsGreen (to simulate CGCs), and the capture rate reached more than 96% at a flow rate of 1.2 mL/h. In real-life applications, CGCs (1-25/mL) were detected in 21 out of 35 glioma patients. We found that the number of CGCs was relatively high in patients with wild-type IDH1 and was positively correlated with Ki67 expression (p = 0.026). The enrichment of CGC was correlated with neutrophils (p = 0.041) and heparin-binding protein (p = 0.0064), suggesting neutrophil-mediated metastasis. Radiomics linked a higher presence of CGCs with larger tumors, severe necrosis, and extensive edema, suggesting a poor prognosis for patients. The ASM chip can effectively capture and quantify CGCs for guiding the diagnosis and predicting the potential prognosis of clinical glioma patients.

We present an optomechanical device platform for characterization of rheological, optical and thermal properties of fluids on the micron scale. A suspended silicon microdisk resonator with a vibrating mass of 100 pg and an effective probing volume of less than a pL is used to monitor properties of different fluids at rest. By employing analytical models for fluid-structure interactions, thermo-optical effects and thermal diffusion, our platform determines the viscosity, density, compressibility, refractive index and thermal conductivity of the fluid, in a compact measurement setup. A single measurement takes as short as 70 μs, and the employed power can be less than 100 μW, guaranteeing measurement at rest and in thermal equilibrium.

Micro-electro-mechanical systems (MEMS) gravimeters are emerging as promising next-generation tools to overcome the high costs and large dimensions of conventional gravimeters. However, persistent sensitivity limitations have hindered their practical adoption. This paper presents a pioneering force-balanced MEMS gravimeter with enhanced sensitivity, achieved using quasi-zero-stiffness (QZS) springs and an arrayed capacitive displacement sensor. A novel two-step tuning method, combining saturated-ions enhanced lateral plasma thinning and thermo-mechanical coupling, precisely adjusts the QZS state and attains optimal sensitivity in displacement transducers, successively. The gravimeter achieves a resonant frequency of 0.6 Hz and a self-noise of 0.1 μGal/√Hz at 0.14 Hz, setting a new benchmark for MEMS gravimeters. To address bandwidth constraints imposed by the ultra-low resonant frequency, an electromagnetic feedback control module is introduced, expanding the bandwidth to 108 Hz. A 45-day Earth tide observation demonstrated a residual standard deviation of 2.3 μGal, reflecting exceptional long-term stability. This MEMS gravimeter breaks through sensitivity and bandwidth barriers, offering a compact, cost-effective solution for next-generation gravimetry.

Maximizing sensitivity while minimizing manufacturing complexity and costs remains a challenge in the development of flexible gas sensors. Two-dimensional transition metal dichalcogenides (TMDCs) have emerged as potential candidates; however, further enhancement of their gas sensitivity is required without increasing fabrication complexity. Here, we report ultrasensitive and selective gas sensors fabricated by mechanically drawing compressed TMDCs on flexible cellulose paper. This method rapidly and cost-effectively integrates nanolayered TMDCs, such as WSe₂ and MoS₂, onto the rough paper surface while abundantly exposing their edge sites. Notably, WSe₂ exhibits a high response of ~1978.63% toward 10 ppm NO₂ with exceptional sensitivity (~139.9% ppm⁻¹ at 0.1 to 1 ppm NO₂) and an ultra-low detection limit (1.25 ppb), far exceeding the responses to NH₃, CO, and six species of volatile organic compounds. These high responses remain stable under severe mechanical deformations. Furthermore, we present a portable wireless sensing device that enables real-time gas monitoring on a smartphone, using the TMDC-drawn paper as a replaceable sensor in a 3D-printed frame. Compared to conventional flexible gas sensors, our approach not only simplifies fabrication but also offers outstanding sensitivity.

Sub-picometer precision displacement measurement at the tip position is a key goal in high-precision characterization techniques such as piezoresponse force microscopy, photo-induced force microscopy, and scanning Joule expansion microscopy (SJEM). However, these methods require specialized atomic force microscopy (AFM) probes, which increase cost and complexity. This work proposes a generalized strategy and demonstrates its implementation in SJEM. By exploiting the torsional response of a tilted AFM probe to amplify the deformation signal, we enhanced the sensitivity by nearly an order of magnitude, achieving a record-breaking displacement resolution of 0.37 pm. This method allows flexible adjustment of sensitivity and decouples in-plane and out-of-plane displacements. This work establishes a transferable, AFM-based strategy for high-sensitivity displacement detection, providing valuable guidance for high-precision characterization and analysis of materials and devices at the nanoscale.

This paper proposes a novel 3D printing technology for fabricating high-performance volumetric electronic circuits. It introduces a particle-free conductive system based on a nontoxic reductant-functionalized polymer coating, offering a microscopic localized enhancement technique. By in-situ reducing silver onto custom-designed substrates, highly conductive and controllable coatings are formed, allowing frequency selective surfaces (FSS) to be extended from planar to spatial volumes (3DFSS). As a result, more desirable FSS characteristics can be achieved, such as significantly stable filtering performance for different incident angles and polarization modes of electromagnetic waves regardless of obliquity, compared to corresponding 2DFSS. The proposed FSS achieves a bandwidth of 4.4-7.8 GHz (fractional bandwidth of 54.8%) with a reflection coefficient below -10 dB. Design guidelines based on the equivalent circuit model (ECM) illustrate the transition from this 3DSS to a filter response. The designed array FSS boasts excellent structural compactness and mechanical robustness, enabling seamless integration with building materials. It provides electromagnetic signal modulation across scales, offering a technological solution for electromagnetic compatibility and signal transmission quality issues in miniaturized communication systems.

Chronic wounds represent a major global healthcare burden, demanding integrated solutions for both continuous wound monitoring and on-demand therapeutic intervention. In this work, we present monolithic barbed microneedles (3D-BMN) for wound impedance sensing and barbed hollow microneedles (3D-BHMN) for drug delivery, fabricated with high-precision projection micro-stereolithography (PμSL) 3D printing. Inspired by natural barbed structures like bee stingers, the barbed geometry balances penetration efficiency with mechanical interlocking, enabling stable anchorage to wound dressings. Conductivization with Ag/AgCl and AuNPs imparts robust electrochemical performance, allowing accurate monitoring of wound impedance, which correlates with wound status. 3D-BHMN integrates an ultrasonic atomizer for efficient drug delivery. A closed-loop feedback system couples 3D-BMN and 3D-BHMN, forming a closed-loop system for on-demand delivery of therapeutic agents modulated by the sensed impedance value that aligns with the dynamic wound status. This integrated platform advances smart wound management by combining diagnostics and therapeutics, offering broad translational potential.

Silicon resonant sensors are essential to a wide range of applications that involve the detection of pressure, acceleration, and magnetic fields. In general, they operate by monitoring a shift in the resonant frequency of silicon micromechanical resonators when subjected to perturbations due to the aforementioned parameters. This frequency shift manifests as a linear dependence on the perturbation. The demand for ever more precise silicon resonant sensors has catalyzed research endeavors aimed at boosting their sensitivity beyond geometrical constraints, including attempts to utilize synchronization phenomenon in coupled silicon resonators. Here, we establish and experimentally demonstrate a method using non-Hermitian singularities, or an exceptional point (EP), to amplify sensitivity. This method reveals that the frequency shift in nonlinear parity-time symmetric silicon micromechanical resonators exhibits a cubic root singularity of perturbations. In the small perturbation limits, we observe an increase in sensitivity by several orders of magnitude when compared to traditional configurations. Our findings pave the way towards the next generation of ultrasensitive silicon resonant sensors.

Detecting ammonia (NH₃) in human breath is vitally important for early warning and disease detection. Polymer composite nanomaterials, which serve as high-performance NH₃ gas sensors, have become a prominent research focus in this field. In this study, polypyrrole (PPy) and various gallium nitride (GaN) nanostructures were selected for synthesis. PPy/GaN gas sensors were successfully fabricated by employing the precisely controllable metal-organic chemical vapor deposition (MOCVD) process in conjunction with in situ oxidative polymerization methods. The gas sensing performance of the sensors was systematically analyzed. The PPy/GaN-1 sensor demonstrated an ultra-wide detection range for NH₃ (100 ppb-1000 ppm) at room temperature, along with exceptional moisture resistance and long-term stability. This can be attributed to the excellent uniformity of the film distribution, which enabled optimal synergy between GaN and PPy. Furthermore, an experiment detecting human exhaled breath was carried out using a sensor array to validate its high sensitivity. With the assistance of machine learning algorithms, high-precision prediction of gases within the low-concentration range was achieved (with an error of 1.17 ppm). Overall, this study offers valuable insights into the development of early warning systems for chronic kidney disease (CKD).