Micro and Nano Systems Letters最新文献

Dissolving microneedles (DMNs) represent an innovative advancement in drug delivery and skincare technologies, offering significant advantages compared to traditional needles. This paper presents an overview of the historical evolution of microneedles and the rise of dissolving types, exploring their definition, concept, and diverse clinical applications such as vaccinations, drug delivery, and skincare treatments. Design and manufacturing considerations cover the materials employed, fabrication techniques, and methods for characterizing DMNs, focusing on aspects like mechanical strength, dissolution rate, and delivery efficiency. The mechanism of action section examines skin penetration mechanics, the process of microneedle dissolution, controlled release of active compounds, and considerations of biocompatibility and safety. Recent developments in DMNs encompass technological advancements, improved delivery systems, and updates on clinical trials and studies. Challenges and opportunities in scaling up production, overcoming market adoption barriers, and future research directions are discussed, aiming to address unmet medical needs and expand applications. In summary, DMNs have the potential to transform drug delivery and skincare treatments, with ongoing advancements aimed at tackling current challenges and unlocking new opportunities for enhanced healthcare outcomes.

Graphical Abstract

Cancer survivors undergo meticulous examinations, including regular magnetic resonance imaging (MRI) scans, to monitor the risk of disease recurrence. The use of magnetic iron nanoparticles (MNPs) enhances MRI accuracy. However, post-injection, MNPs exhibit a notable affinity for binding with proteins and biomolecules, forming a dynamic protein coating called a protein corona (CORONA). While there are reports of its elimination in the liver and kidney metabolism system, patients undergoing this method have shown symptoms of liver problems and related enzyme alterations. This study aims to discern whether the impact of MNPs on liver enzymes significantly contributes to liver damage. The investigation focuses on the effects of magnetic nanoparticles (MNPs) on selected enzymes, including alanine aminotransferase (ALT), aspartate transaminase (AST), α-amylase, and lipase. Employing 104 experiments over a central composite design (CCD), the study evaluates the effects of agents on MNP and enzyme structure, stability, and properties: enzyme assay, electron microscopy, and circular dichroism of secondary structure after interaction with MNPs. The study’s findings unveil the intricate relationship between MNPs and liver enzymes, providing valuable insights for clinical practices and refining the safety profile of MRI. This comprehensive exploration contributes to our understanding of potential implications and aids in optimizing the use of MNPs in medical imaging for cancer survivors.

Bulk micromachining is commonly used to fabricate microstructures such as deep cavities, through-holes, and microchannels in glass wafers, which have diverse applications in the areas of science and technology. The methods for glass bulk micromachining include mechanical, dry, and wet etching; among them, wet etching is widely used due to its multifaceted advantages. Masking layer plays an eminent role in wet etching. In the current study, Cr thin film combined with positive photoresist (AZ1512HS) is investigated as the masking layer to develop deep cavities in Borofloat glass wafers via wet etching route. Initially, DC magnetron sputtered Cr thin film is deposited at room temperature, 200 °C, and 400 °C, respectively, on three different glass wafers, followed by spin coating of photoresist on it. Photolithography process is used for patterning, and then selective etching of Cr is performed. Thereafter, wet etching of glass wafers is executed in 10% hydrofluoric acid (HF) solution. This work shows that the sustainability of the masking layer is highly dependent on the deposition temperature of Cr thin film, and the sustainability increases with the increase in the deposition temperature. The high temperature (400 °C) deposited Cr thin film along with photoresist exhibits superior sustainability as a masking layer, and it relatively provides a longer etch time of 380 min, excellent etch depth of  ~  245 µm with negligible surface defects and well-defined structures on glass wafer when etched in 10% HF solution.

As the dangers of volatile organic compounds (VOCs) and their potential as non-invasive diagnosis biomarkers have been reported, there has been a need for instrument capable of real-time and in-situ monitoring of multiple low-concentration VOCs in indoor air or human metabolites. A promising technology that can qualitatively and quantitatively analyze numerous VOCs as an alternative to conventional bench-top instruments is a micro-gas chromatography (µ-GC) system, which integrates three main components: a micro-gas preconcentrator, a µ-GC column, and a mini- or micro-detector fabricated using microelectromechanical system (MEMS) processes. This review covers the integration methods, features, and analysis capabilities of recently developed µ-GC systems and examines the materials, designs, and principles of the three main components. In addition, the challenging issues that must be addressed for the commercialization of this technology are discussed.

Identifying the phononic crystal (PnC) with bandgap is a problematic process because all phononic crystals don’t have bandgap. Predicting the Phononic bandgaps (PnBGs) is a computationally expensive task. Here we explore the potential of machine learning (ML) tools to expedite the prediction and maximize the resonator based PnBG. The Gaussian process regression (GPR) model is trained to learn the relationship between complicated shape and band structure of cavity. Bayesian optimization (BO) derives a new shape by leveraging the fast inference of the trained model, which is updated with the augmentation of newly explored structures to escalate the prediction power over performance expansion through active learning. Artificial intelligence (AI) assisted optimization requires a small number of generations to achieve convergence. The obtained results are validated via experimental measurements.

Novel sensing and actuation technologies have notably advanced haptic interfaces, paving the way for more immersive user experiences. We introduce a haptic system that transcends traditional pressure-based interfaces by delivering more comprehensive tactile sensations. This system provides an interactive combination of a robotic hand and haptic glove to operate devices within the wireless communication range. Each component is equipped with independent sensors and actuators, enabling real-time mirroring of user’s hand movements and the effective transmission of tactile information. Remarkably, the proposed system has a multimodal feedback mechanism based on both vibration motors and Peltier elements. This mechanism ensures a varied tactile experience encompassing pressure and temperature sensations. The accuracy of tactile feedback is meticulously calibrated according to experimental data, thereby enhancing the reliability of the system and user experience. The Peltier element for temperature feedback allows users to safely experience temperatures similar to those detected by the robotic hand. Potential applications of this system are wide ranging and include operations in hazardous environments and medical interventions. By providing realistic tactile sensations, our haptic system aims to improve both the performance and safety of workers in such critical sectors, thereby highlighting the great potential of advanced haptic technologies.

This study deals with the process of developing and optimizing the spray coating method for large-area deposition of carbon nanotubes. Carbon nanotubes have excellent electrical and thermal properties and strength, so they are used in various fields of application. However, existing deposition methods have limitations. In this study, the possibility of the spray coating method for large-area deposition of carbon nanotubes is presented, and additional conditions for this are introduced. A spray coating solution was prepared using dichlorobenzene as a solvent for 3 mg carbon nanotubes. By controlling the spray coating speed, the spray coating conditions were optimized by analyzing the surface shape, structure, and resistance of the deposited carbon nanotubes. As a result, we confirmed the possibility of depositing carbon nanotubes on a large area through the spray coating method, and it is expected to contribute to increasing the application possibilities in industrial and scientific fields.

Laser-induced graphene (LIG) is a three-dimensional graphene structure fabricated through the irradiation of a polymer substrate with laser energy (or fluence, equivalently). This methodology offers a cost-effective and facile means of producing 3D nanostructures, yielding graphene materials characterized by extremely high surface area and superior electrical properties, rendering them advantageous for various electrochemical applications. Nonetheless, it is imperative to acknowledge that the structures and material properties of LIG are subject to substantial variations contingent upon processing parameters, thereby underscoring the necessity for systematic inquiry and systematic comprehension of processing conditions, such as fluence and multi-passing, and resultant outcomes. Herein, we explored the impact of different laser fluence levels on the structural and material properties of LIG. We, especially, focused on how laser fluence affected substrate temperature and found that it caused polyimide (PI) substrate pyrolysis, resulting in changes in 3D structures and material density to LIG properties. We also investigated the effects of a multi-passing process on 3D LIG structures and material qualities, varying fluences, and temperature fluctuations. Lastly, we assessed electrochemical properties using LIGs produced under different conditions as working electrodes, leading to distinct impedance profiles and cyclic voltammetry (CV) curves. These variations were linked to the unique structural and material characteristics of the LIG samples.

A quasi-static (QS) MEMS mirror scanner with concentric vertical combs (CVC) is presented. The increase rate of overlapped area of the CVC, tends to show larger values and more uniform than that of conventional vertical combs, resulting in improved linearity and scanning angle, respectively. In this paper, the performance of the QS scanner with CVC, whose equivalent mirror diameter is 3.9 mm, was theoretically analyzed and compared with the fabricated one and also other types of vertical combs such as staggered vertical combs (SVC) and angular vertical combs (AVC). The linearity was less than 0.1%, and the average value of the experimental OSA (optical scanning angle) was up to 13.5 degrees, which is only 1/3 and 39% larger than other scanners, respectively, under the condition that the configuration and dimension of each MEMS scanner is similar each other.

This investigation aimed to evaluate the thermal conductivity ratio (TCR) of SWCNT-CuO/Water nanofluid (NF) using experimental data in the T range of 28–50 ℃ and solid volume fraction range of SVF = 0.03 to 1.15% by an artificial neural network (ANN). MLP network with Lundberg-Marquardt algorithm (LMA) was utilized to predict data (TCR) by ANN. In the best case, from the set of various structures of ANN for this nanofluid, the optimal structure was chosen, which consists of 2 hidden layers, the first layer with the optimal structure consisting of 5 neurons and the second layer containing 7 neurons. Eventually, for the optimal structure, the R² coefficient and MSE are 0.9999029 and 6.33377E-06, respectively. Based on all ANN information, MOD is in a limited area of − 3% < MOD <  + 3%. Comparison of test, correlation yield, and ANN yield display that ANN evaluates laboratory information more exactly.