Advanced Materials Technologies最新文献

Artificial Tactile Perception Systems

In article number 2400338, Tingting Zhao, Jianhua Zhang, an co-workers present an artificial tactile perception system capable of sensing, encoding, and learning spatio-temporal information of pressure stimuli. It combines piezoelectric nanogenerators and a multiple-gate synaptic transistor for sensing and processing. Exploiting the modulation capability of the gate electrode positioned variably relative to the channel on the proton migration, the spatial position and time sequence of the applied pressure can be distinguished.

Biological and mechanical mismatches between engineered scaffolds and native tissues poses widespread challenges for tissue restoration. Native-like anisotropy is a critical characteristic for functional tissue replacements, yet it is an often-overlooked aspect when designing new scaffolds. In this study, fiber-reinforced tubular scaffolds are developed, mimicking the anisotropic characteristics of natural tissues, using native-like silk fibroin. To predict the mechanical behavior of these innovative scaffolds, a mathematical model is employed, utilizing the properties of the scaffolds’ constituent materials, and experimentally validated through tensile testing. This approach addresses significant challenges in the design of new scaffold implants by enabling to efficiently predict the performance of several configurations, narrowing down the experimental research space. The proposed platform constitutes an appealing tool for the development of clinically relevant tissue-equivalents.

Innovations in chewable dosage forms provide solutions for swallowing difficulties faced by certain patient populations. Chewable softgel capsules (SGC) offer opportunities to expand the benefits of SGC, excelling in the delivery of lipid-based formulations by optimizing the mechanical properties of the shell material without compromising industrial-scale manufacturing. This study employs an original approach, with a target product profile that aims to combine processability and chewability, to develop optimized chewable dosage forms. Through a mixture design of experiments, key factors such as plasticizer content and the addition of acid-modified thin-boiling corn starch are explored, focusing on response parameters critical to achieving the desired properties of the capsule shell material. Optimal shell compositions—one starch-free and another containing 9% w/w starch, with respective gelatin/non-volatile plasticizer ratios of 0.81 and 0.67 are determined and evaluated by manufacturing chewable SGC at pilot scale using rotary die technology. The successful manufacturing and resulting capsules, which exhibit the intended properties, highlight the efficiency of this approach in striking the right balance between processability, soft texture, and quick disintegration time.

A novel spoof surface plasmon polaritons (SSPP) structure is applied to the design of radio frequency (RF) power amplifiers (PAs) in this work. Both standard SSPP and the proposed SSPP structures are used as input and output matching networks of a multioctave PA design. An analysis and discussion of the electromagnetic characteristics of the proposed SSPP structures is presented. Further optimization of PA performance is achieved by utilizing the gradient algorithm of the Advanced Design System tool. According to the test results, the newly developed SSPP-based PA achieves output power ranging from 40.5 to 42.6 dBm, while the power additional efficiency varies between 60% and 66.55%, with a total layout size of 59.8 mm × 14.6 mm in the frequency band of 0.8–3.2 GHz. In comparison with recent published work, the PA designed in this work expands the bandwidth while maintaining high output power and efficiency while being smaller in size.

Non-diffraction Airy beams with self-accelerating properties have many potential applications in the microwave band, such as providing a viable solution to bypass obstacles for microwave-based wireless power transfer (WPT) and communication. However, most of the recent work on Airy beams exhibits singular functionality and operates solely in linear polarization, with complex generation setups, which will constrain the applications of the beam in the microwave band. In this paper, based on the anisotropic holographic impedance metasurface (AHIM) with low complexity, a new method is proposed to manipulate Airy beams in multiple dimensions, including circularly polarization state, number of beams, direction of acceleration, and launch position of beam. The underlying principle is the combination of plane coordinate transformation, anisotropy of AHIM, and impedance superposition theory. Further, to validate the proposed method, an AHIM prototype for simultaneously generating two Airy beams with orthogonal circular polarization, different directions of acceleration, and different spatial distribution is designed, simulated, and measured. The proposed method based on AHIM for manipulating the Airy beams multidimensionally in the microwave band offers an efficient strategy to control the energy coverage and polarization state of the beam in different WPT scenarios.

Extrusion-based 3D printing technology is currently demonstrating considerable potential in the field of tissue engineering scaffolds, enabling the construction of in vitro models with complex structures and functions using a wide range of biomaterials and cells at a low cost. In recent years, researchers have spent considerable effort developing novel bio-inks and employing a greater variety of cell sources to enhance biological compatibility and functionality. However, the majority of current bio-ink materials are unprintable due to their low viscosity and long curing time, as well as insufficient shape fidelity before the secondary cross-linking process. The study aims to bridge this gap by optimizing the material ratios and predicting the printing process before work. This article presents new strategies for the design, fabrication, and analysis of a new composite bio-ink material. The optimal ink ratios are verified by a design of experiments (DOE) experimental design and evaluation metrics for printing printability (Pr) values. A machine learning model is used to predict the ink printing area and determine the printing process parameters. The influence mechanism of ink materials with different concentrations of poly (ethylene glycol) diacrylate (PEGDA) ratios on printed fibers is investigated. Finally, the optimal results are used as an example to demonstrate the printability of multilayer stents. Thus, the design approach allows for the rapid and cost-effective exploration of novel ink ratios, while also providing higher fidelity and more accurate process metrics for the fabrication of tissue structures with multidimensional variables.

A novel transparent photothermoelectric device has been developed, leveraging the advantageous thermoelectric properties of transparent conductive oxide thin films such as aluminium-doped zinc oxide (AZO), and the absorption or reflectance properties of indium thin oxide (ITO) for near-infrared (NIR) radiation. AZO exhibits transmittance exceeding 70% across a broad range of wavelengths (400–2200 nm) and a high Seebeck coefficient (120–150 µV K⁻¹). Through heat treatments between 300 and 500 °C, ITO's NIR absorption is optimized to values above 40% in the 1–1.5 µm range. The optimized thickness of the ITO/Ag/ITO multilayer structure has an 80% reflectance for wavelengths above 1.2 µm. Integrating these two layers on a transparent thermoelectric AZO film creates a thermal gradient induced by infrared (IR) radiation. This gradient results in a photothermal potential that is sensitive to sunlight intensity, with a sensitivity measured at 1.5 mV W⁻¹. This innovation marks a significant advancement in technology, showcasing the potential for transparent devices in smart windows.

Methodological improvement to single-cell manipulation is critical for exploring the fundamentals of cellular life and unraveling biological complexity. Although micro-manipulation technologies capable of precise cell localization have been widely established, scaling existing platforms for highly efficient single-cell immobilization without sacrificing cell viability and sample quantity has proven challenging. Here, a highly efficient single-cell trapping and arraying approach is introduced by advancing the performance of a microfluidic mechanical trapping chip. The chip can achieve representative single-cell capture with over 99% efficiency and at least a 75% success rate of perfect capture, a precisely controlled single-cell array, absolute sequential cell captures without cell loss, and the maintenance of high cell viability during the whole manipulation process. This approach enables diverse single-cell trapping, large-scale arraying manipulations, and dynamic cellular and molecular analysis, and offers a path toward the development of high-performance single-cell systems.

A machine learning (ML) guided approach is presented for the accelerated optimization of chemical vapor deposition (CVD) synthesis of 2D materials toward the highest quality, starting from low-quality or unsuccessful synthesis conditions. Using 26 sets of these synthesis conditions as the initial training dataset, our method systematically guides experimental synthesis towards optoelectronic-grade monolayer MoS₂ flakes. A-exciton linewidth (σ_A) as narrow as 38 meV could be achieved in 2D MoS₂ flakes after only an additional 35 trials (reflecting 15% of the full factorial design dataset for training purposes). In practical terms, this reflects a decrease of the possible experimental time to optimize the parameters from up to one year to about two months. This remarkable efficiency was achieved by formulating a constrained sequencing optimization problem solved via a combination of constraint learning and Bayesian Optimization with the narrowness of σ_A as the single target metric. By employing graph-based semi-supervised learning with data acquired through a multi-criteria sampling method, the constraint model effectively delineates and refines the feasible design space for monolayer flake production. Additionally, the Gaussian Process regression effectively captures the relationships between synthesis parameters and outcomes, offering high predictive capability along with a measure of prediction uncertainty. This method is scalable to a higher number of synthesis parameters and target metrics and is transferrable to other materials and types of reactors. This study envisions that this method will be fundamental for CVD and similar techniques in the future.

Metal-organic frameworks (MOFs) are porous materials with numerous chemical and structural possibilities. Due to their ease of modification, well-organized structure, and diverse guest molecule chemistry, MOFs are ideal platforms for uncovering improved functional material design characteristics. Quantitative analysis of glucose is crucial, especially in some food products, for quality control as well as evaluation of the glucose levels helps diagnose and treat diabetes. Recent glucose sensing devices have relied heavily on MOFs and other nanomaterials to enable user-friendly and safe non-invasive sensing methods. Nevertheless, the conventional synthesis methods involve multi-day reactions, cooling, and depressurization processes. This study demonstrates the unprecedented high-power laser-induced rapid synthesis (LIRS) of Ni-based MOF nanospheres with interconnected nano-rods and noncentrosymmetric primitive triclinic crystalline structure, highlighting their multifunctional usage in sensing and gas sorption applications. Ab initio simulations show excellent agreement with the experimental physical and gas sorption properties. Furthermore, the Ni-MOF-based biosensor accurately measures glucose real-life beverage samples, yielding promising glucose detection biosensor results with a low limit of the detection (LOD) of 13.96 µM and high sensitivity of 120.606 µA mM⁻¹ cm⁻².