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Current additive manufacturing (AM) techniques and methods, such as liquid-crystal display (LCD) vat photopolymerization, offer a wide variety of surface-sensing solutions, but customizable internal sensing is both scarce in presence and narrow in scope. In this work, a fabrication process for novel customizable embedded ceramic temperature sensors is investigated. The fabrication techniques and materials are evaluated, followed by extensive characterization via spectral analysis and thermomechanical testing. The findings indicate that LCD-manufactured ceramic sensors exhibit promising sensing properties, including strong linear thermal sensitivity of 0.23% per °C, with an R2 of at least 0.97, and mechanical strength, with a hardness of 570 HV, making them suitable for adverse environmental conditions. This research not only advances the field of AM for sensor development but also highlights the potential of LCD technology in rapidly producing reliable and efficient ceramic temperature sensors. 

Additive manufacturing (AM) technology has recently seen increased utilization due to its versatility in using functional materials, offering a new pathway for next-generation conformal electronics in the smart sensor field. However, the limited availability of polymer-based ultraviolet (UV)-curable materials with enhanced piezoelectric properties necessitates the development of a tailorable process suitable for 3D printing. This paper investigates the structural, thermal, rheological, mechanical, and piezoelectric properties of a newly developed sensor resin material. The polymer resin is based on polyvinylidene fluoride (PVDF) as a matrix, mixed with constituents enabling UV curability, and boron nitride nanotubes (BNNTs) are added to form a nanocomposite resin. The results demonstrate the successful micro-scale printability of the developed polymer and nanocomposite resins using a liquid crystal display (LCD)-based 3D printer. Additionally, incorporating BNNTs into the polymer matrix enhanced the piezoelectric properties, with an increase in the voltage response by up to 50.13%. This work provides new insights for the development of 3D printable flexible sensor devices and energy harvesting systems. 

The inflammation marker Interleukin 6 (IL-6) typically remains below 5 pg/mL in the serum of healthy individuals but can increase tenfold during inflammation in chronic conditions like COVID-19 and rheumatoid arthritis, as well as acute conditions like sepsis. This study is focused on the rapid detection of IL-6 to monitor both chronic and acute diseases. The novel sensor, designed with gold-coated micropyramids on the electrodes, was fabricated using the two-photon polymerization method, enabling low-volume sensing capabilities (2-3 μL). The micropyramids were surface functionalized with interleukin-6 antibodies towards developing an affinity biosensor specific to the physiological relevant range of IL-6 of 5.1 and 18.8 pg/mL in mild inflammation. Sensing was achieved by measuring impedance changes associated with IL-6 binding to the antibodies on the micropyramids interfaced using electrochemical impedance spectroscopy. It was observed that the signals from the lowest detection concentration was enhanced by 3 times at 1500 hz when the 532 nm green laser was incident on the micropyramids. This innovative approach can be expanded to the detection of cytokines not only in serum but also in respiratory samples. As a result, it opens up new avenues for monitoring local inflammation within the lungs and assessing systemic inflammation levels throughout the body. 

Polymer nanofibers hold promise in a wide range of applications owing to their diverse properties, flexibility, and cost effectiveness. In this study, we introduce a polymer nanofiber drawing process in a scanning electron microscope and focused ion beam (SEM/FIB) instrument with in situ observation. We employed a nanometer-sharp tungsten needle and prepolymer microcapsules to enable nanofiber drawing in a vacuum environment. This method produces individual polymer nanofibers with diameters as small as ∼500 nm and lengths extending to millimeters, yielding nanofibers with an aspect ratio of 2000:1. The attachment to the tungsten manipulator ensures accurate transfer of the polymer nanofiber to diverse substrate types as well as fabrication of assembled structures. Our findings provide valuable insights into ultrafine polymer fiber drawing, paving the way for high-precision manipulation 

Plants are remarkable in their ability to adapt to changing environments, with receptor-like kinases (RLKs) playing a pivotal role in perceiving and transmitting environmental cues into cellular responses. Despite extensive research on RLKs from the plant kingdom, the function and activity of many kinases, i.e., their substrates or “clients”, remain uncharted. To validate a novel client prediction workflow and learn more about an important RLK, this study focuses on P2K1 (DORN1), which acts as a receptor for extracellular ATP (eATP), playing a crucial role in plant stress resistance and immunity. We designed a Kinase-Client (KiC) assay library of 225 synthetic peptides, incorporating previously identified P2K phosphorylated peptides and novel predictions from a deep-learning phosphorylation site prediction model (MUsite) and a trained hidden Markov model (HMM) based tool, HMMER. Screening the library against purified P2K1 cytosolic domain (CD), we identified 46 putative substrates, including 34 novel clients, 27 of which may be novel peptides, not previously identified experimentally. Gene Ontology (GO) analysis among phosphopeptide candidates revealed proteins associated with important biological processes in metabolism, structure development, and response to stress, as well as molecular functions of kinase activity, catalytic activity, and transferase activity. We offer selection criteria for efficient furtherin vivoexperiments to confirm these discoveries. This approach not only expands our knowledge of P2K1’s substrates and functions but also highlights effective prediction algorithms for identifying additional potential substrates. Overall, the results support use of the KiC assay as a valuable tool in unraveling the complexities of plant phosphorylation and provide a foundation for predicting the phosphorylation landscape of plant species based on peptide library results. 

Recent developments in micro-scale additive manufacturing (AM) have opened new possibilities in state-of-the-art areas, including microelectromechanical systems (MEMS) with intrinsically soft and compliant components. While fabrication with soft materials further complicates micro-scale AM, a soft photocurable polydimethylsiloxane (PDMS) resin, IP-PDMS, has recently entered the market of two-photon polymerization (2PP) AM. To facilitate the development of microdevices with soft components through the application of 2PP technique and IP-PDMS material, this research paper presents a comprehensive material characterization of IP-PDMS. The significance of this study lies in the scarcity of existing research on this material and the thorough investigation of its properties, many of which are reported here for the first time. Particularly, for uncured IP-PDMS resin, this work evaluates a surface tension of 26.7 ± 4.2 mN/m, a contact angle with glass of 11.5 ± 0.6°, spin-coating behavior, a transmittance of more than 90% above 440 nm wavelength, and FTIR with all the properties reported for the first time. For cured IP-PDMS, novel characterizations include a small mechanical creep, a velocity-dependent friction coefficient with glass, a typical dielectric permittivity value of 2.63 ± 0.02, a high dielectric/breakdown strength for 3D-printed elastomers of up to 73.3 ± 13.3 V/µm and typical values for a spin coated elastomer of 85.7 ± 12.4 V/µm, while the measured contact angle with water of 103.7 ± 0.5°, Young’s modulus of 5.96 ± 0.2 MPa, and viscoelastic DMA mechanical characterization are compared with the previously reported values. Friction, permittivity, contact angle with water, and some of the breakdown strength measurements were performed with spin-coated cured IP-PDMS samples. Based on the performed characterization, IP-PDMS shows itself to be a promising material for micro-scale soft MEMS, including microfluidics, storage devices, and micro-scale smart material technologies. 

Abstract The demand for the capacitive sensor has attracted substantial attention in monitoring pressure due to its distinctive design and passive nature with versatile sensing capability. The effectiveness of the capacitive sensor primarily relies on the variation in thickness of the dielectric layer sandwiched between conductive electrodes. Additive manufacturing (AM), a set of advanced fabrication techniques, enables the production of functional electronic devices in a single-step process. Particularly, the 3D printing approach based on photocuring is a tailorable process in which the resin consists of multiple components that deliver essential mechanical qualities with enhanced sensitivity towards targeted measurements. However, the availability of photocurable resin exhibiting essential flexibility and dielectric properties for the UV-curing production process is limited. The necessity of a highly stable and sensitive capacitive sensor demands a photocurable polymer resin with a higher dielectric constant and conductive electrodes. The primary purpose of this study is to design and fabricate a capacitive device composed of novel photocurable Polyvinylidene fluoride (PVDF) resin utilizing an LCD process exhibiting higher resolution with electrodes embedded inside the substrate. The embedded electrode channels in PVDF substrate are filled with conductive silver paste by an injection process. The additively manufactured sensor provides pressure information by means of a change in capacitance of the dielectric material between the electrodes. X-Ray based micro CT-Scan ex-situ analysis is performed to visualize the capacitance based sensor filled with conductive electrodes. The sensor is tested to measure capacitance response with changes in pressure as a function of time that are utilized for sensitivity analysis. This work represents a significant achievement of AM integration in developing efficient and robust capacitive sensors for pressure monitoring or wearable electronic applications.