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Micro-electro-mechanical system (MEMS) sensors have been widely used in the automotive field owing to their small size, low cost, and high reliability. Various defects are caused by complicated environments and multistep processes in the manufacturing process of automotive MEMS pressure sensors. These defects are often small in size but can significantly impact the performance of products. The traditional detection method is inefficient and inaccurate. In this study, an improved you only look once v8 (YOLOv8) C2f-RFCBAMConv (CR) network is proposed to detect the defects of the automotive MEMS pressure sensors. The network is an improved version of YOLOv8. The faster version of the CSP bottleneck with two convolutions (C2f) and receptive-field convolutional block attention (RFCBAMConv) modules are applied. The ablation experiments confirm the impact of C2f and RFCBAMConv modules on network performance. The improved YOLOv8-CR network can effectively enhance the accuracy and speed of defect detection of the automotive MEMS pressure sensor. Furthermore, comparisons are made between the improved YOLOv8-CR network and other networks such as YOLOv8-large, YOLOv5, and faster region-based convolutional neural network (Fast-RCNN), demonstrating its effectiveness in identifying five types of defects in the automotive MEMS pressure sensors. The improved YOLOv8-CR exhibits considerably superior defect detection capabilities with a mean average precision (mAP) of 94.98% and a single picture detection time of 42.68 ms on the test set. The improved YOLOv8-CR network is helpful in realizing real-time and accurate online monitoring of product quality in the key process of the automotive MEMS pressure sensors.

Laser powder bed fusion (LPBF) is a cutting-edge metal additive manufacturing technology with promising applications in aerospace, biomedicine, and industrial automation. Its ability to fabricate intricate geometric shapes, achieve high surface precision, and deliver comprehensive results renders it highly advantageous. In LPBF process, several factors such as the interference of laser processing fluctuations, rapid cooling rate, and environmental gas, contribute to the initiation and expansion of defects including pores and cracks, limiting the application of LPBF components. Laser ultrasonic testing (LUT) is a promising non-destructive evaluation method that can accurately detected defects in LPBF manufactured components by non-contact generation and detection. In this paper, a multi-physical field LUT model for the pores and cracks in LPBF additively manufactured Ti6Al4V alloy is proposed. The interaction of ultrasound with defects produces defect reflection echo wave, diffracted wave, and transmission wave. The transmission and diffraction phenomena occur in the longitudinal sound waves at defects. Furthermore, the echo wave reflected at crack exhibited enhanced prominence and an irregular shape. Clear differences were observed in the effects of laser ultrasonic detection on different defect types, pore depths and sizes. Finally, the LUT technology achieved the detection of 90 μm pore defects in LPBF manufactured Ti6Al4V alloy.

Laser powder bed fusion (LPBF) manufactured parts often suffer from porosity defects due to the rapid cooling and solidification processes, as well as the complex flow dynamics within the molten pool. These defects directly affect the mechanical properties of the manufactured components. Therefore, it is imperative to investigate control methods for mitigating pore defects and further improve the development of LPBF technology. This work delved into the evolution mechanism of multi pores in LPBF built AlSi10Mg and Inconel 718 alloys. A multi-physics coupled finite element model was developed based on the level-set method, incorporating heat transfer, Marangoni flow, and mass transfer associated with recoil pressure. The results clearly demonstrate that the shielding gas flow has a non-negligible effect on the pore evolution and significantly reduces the porosity in alloys with different dynamic viscosities. The pores are completely eliminated within two alloys as the shielding gas velocity is 2.0 m/s, 3.0 m/s, and 4.0 m/s, respectively. However, the escape time of pores in AlSi10Mg alloys increases dramatically as the velocity is too excessive to over 2.0 m/s, indicating the increase by 92.5 μs and 120.0 μs, respectively, when the velocity reaches 3.0 m/s and 4.0 m/s. The escape time of pores in Inconel 718 is in obvious contrast to that in AlSi10Mg alloy, meaning that the escape time decreases by 5.0 μs at 3.0 m/s and 40.0 μs at 4.0 m/s, respectively. The experimental results show that the shielding gas velocity significantly affects the porosity and mechanical properties of the components.

Flexible pressure sensors have shown great potential in medical field due to the advantages of excellent flexibility and comfortable wearing. In this article, a flexible inductive–capacitive (LC) sensor array is proposed for wireless multizone pressure monitoring. It consists of three pressure-sensitive LC sensors that operate in nonoverlapping frequency channels. Nano-Ag particles are inkjet printed on polyimide (PI) substrate to fabricate the LC circuits. A thin layer of polydimethylsiloxane (PDMS) is spin-coated onto the circuit, serving as both an electrical insulating layer to prevent shorting out and a deformable dielectric layer between the two capacitor plates when the circuit is folded. Benefiting from the folding design, the PI substrate acts as an external package that provides optimal protection for the entire device. Simulations and experiments are conducted to evaluate the performance in wireless multizone pressure monitoring using the LC sensor array. The results indicate a sensitivity of up to 0.235 MHz/kPa in the range of 0–100 kPa, as well as stability with a bias less than 0.15 MHz over 300 pressure cycles. Furthermore, the sensor array is successfully applied to detect finger flexion, smile, and swallow, showing a promising potential in human health monitoring.

Proper signal measurement and processing are crucial in electroencephalography (EEG)-based brain-computer interfaces (BCIs), as they form the basis of brain insight and precise BCI control. Currently, extensive papers have reported their progress and successful applications in this field. Nevertheless, a systematic review of progress and challenges in this field is still lacking, and the research challenges have not been thoroughly discussed. Herein, a systematic review of instrumentation, measurement, and signal processing in EEG-based BCIs is proposed. First, EEG signals and the application of EEG-based BCIs are introduced. Then, the components and products related to the measurement, processing, and control of EEG signals are analyzed. Specifically, detailed discussions are provided on the measurement methods and results. Moreover, typical EEG paradigms and the processing methods of EEG signals are analyzed. Finally, four major challenges in this field are proposed and discussed: BCIs for acquiring high-quality EEG signals, EEG-based BCIs for long-term tasks, EEG-based BCIs for mobile or dynamic scenarios, and EEG-based BCIs with user-centered designs. This study offers practitioners a comprehensive guide for the measurement and processing of EEG signals, encompassing instrument selection, methodology implementation, current challenges, and future considerations.

In view of the non-destructive and non-contact features, laser ultrasonic (LU) technology has long been the effective method to detect tiny defects for laser powder bed fusion (LPBF) additive manufactured specimens. Of larger concern is the variation and the corresponding mechanism on tested results of LU detection as the property of LPBF additive manufactured specimen is changed. Aiming at the property of surface roughness, this work investigated the propagation characteristics of excited ultrasonic waves in LPBF additive manufactured 316L stainless steel with different surface roughness, as well as the interaction between ultrasonic waves and artificial submillimeter holes. Both numerical simulated and experimental study were conducted. Simulated results revealed that the amplitudes of longitudinal wave (Lwave) and its echo wave L1 at the holes exhibited a discernible increase as the surface was coarser. The increase in surface roughness was detrimental to the resolution of defect detection as was expected from the increased amount of noise. LPBF fabrication and the subsequent LU pulse-echo detection were conducted for 316L stainless steel. Both B-scan and C-scan were able to detect the holes with the diameter of 0.6 mm. The speckle phenomenon deriving from the increase in surface roughness emerged, corresponding to the increased ultrasonic signal energy but deteriorated resolution of detected images. It is feasible to optimize LU detected effect by minimize the surface roughness of tested specimens.

Taking advantage of a hybrid generator to simultaneously collect polynary energy from a single energy source provides a feasible solution for the energy dilemma in the new era. Herein, we integrate a triboelectric nanogenerator and a thermoelectric generator for polynary energy harvesting and self-powered sensing of heatwaves in large-scale industrial factory buildings, which contains both thermal energy and wind energy. The new design of the fan-shaped rotation triboelectric nanogenerator (FR-TENG) makes it more compact and easily integrated. After structure modeling, the energy conversion efficiency of the FR-TENG can reach a maximum of 37.2%, which can successfully power a Bluetooth hygrothermograph transmitting environmental information wirelessly every 30 s at a wind speed of 4.67 m s−1. An all-inorganic flexible thermoelectric generator (iThEG) is developed based on copper and constantan with an output power density of 0.73 W m−3, and maintains its original mechanical properties after 10 000 bending tests. Moreover, a self-powered hot wind sensing system based on Labview is established which can display wind-speed and wind-temperature in real time. The working concept presented here is also applicable to other single energy sources containing multiple energy forms, such as falling raindrops and sunlight, which can lift energy utilization and conversion efficiency and alleviate the energy crisis.

Preparing hybrid microstructures on flexible substrates is a crucial approach to achieving highly sensitive flexible pressure sensors. However, the preparation of hybrid microstructures on soft materials often faces complex, time-consuming, and costly problems, which hampers the advancement of highly sensitive flexible sensors. Herein, based on a 3D-printing template and a household microwave oven, a simple, green, and one-step microwave irradiation process using glucose porogen is applied to develop a flexible pressure sensor with a volcano-sponge-like porous dome structure based on porous polydimethylsiloxane (PDMS). Due to the easily deformable porous dome on the porous PDMS substrate, the flexible pressure sensor showcases exceptional sensitivity of 611.85 kPa–1in 0–1 and 50.31 kPa–1over a wide range of 20–80 kPa. Additionally, the sensor takes only 43 ms to respond, 123 ms to recover, and presents excellent stability (>1100 cycles). In application testing, the sensor effectively captures pulse signals, speech signals, tactile signals from a mechanical gripper, and gesture signals, demonstrating its potential applications in medical diagnosis and robotics. In conclusion, the microwave irradiation method based on template and glucose porogen provides a new way for the simple, low-cost, and green preparation of porous-surface hybrid microstructures on polymers and high-performance flexible pressure sensors.

Laser-directed energy deposition (L-DED) utilizes a high-power laser and coaxial powder feed to rapidly fabricate high-quality components with intricate structures. However, the complex interaction between the powder stream and laser beam is not yet fully understood. Particularly, the morphological evolution of the droplets after powder melting is closely related to the quality of component formation. In this study, the dynamical mechanism of the aggregation and evolution of molten powder after laser–powder interaction was investigated. The Ti6Al4V powder flow was observed at various laser powers using a high-speed camera. Imaging of the molten droplets at approximately 50,000 frames·s−1was conducted, depicting the aggregation of molten powder into droplets of different sizes and shapes, mainly consisting of spherical and ribbon droplets, after laser–powder interaction. A transient numerical model was established with consideration of the mutual influence of gravity, recoil pressure, and surface tension, depicting the temporal evolution of the temperature field and droplet morphology. The simulation results indicated that the balance between the surface tension, gravity, and recoil pressure determined the morphological evolution of the molten droplets. When spherical and ribbon droplets fell into the molten pool, the maximum velocities within the pool increased by 24 % and 69 %, respectively. This phenomenon reduced the stability of the molten pool to a certain extent and affected the print quality of the part. This study deepens our comprehension of the dynamic mechanisms of Ti6Al4V alloy powder melting evolution, providing invaluable insights for optimizing L-DED processes.

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Drug delivery with customized combinations of drugs, controllable drug dosage, and on-demand release kinetics is critical for personalized medicine. In this study, inspired by successive opening of layered structures and compartmentalized structures in plants, we designed a multiple compartmentalized capsular structure for controlled drug delivery. The structure was designed as a series of compartments, defined by the gradient thickness of their external walls and internal divisions. Based on the careful choice and optimization of bioinks composed of gelatin, starch, and alginate, the capsular structures were successfully manufactured by fused deposition modeling three-dimensional (3D) printing. The capsules showed fusion and firm contact between printed layers, forming complete structures without significant defects on the external walls and internal joints. Internal cavities with different volumes were achieved for different drug loading as designed. In vitro swelling demonstrated a successive dissolving and opening of external walls of different capsule compartments, allowing successive drug pulses from the capsules, resulting in the sustained release for about 410 min. The drug release was significantly prolonged compared to a single burst release from a traditional capsular design. The bioinspired design and manufacture of multiple compartmentalized capsules enable customized drug release in a controllable fashion with combinations of different drugs, drug doses, and release kinetics, and have potential for use in personalized medicine.

Selective laser melting (SLM) is an additive manufacturing technology that has an extensively applied foreground and practical value in many fields. Despite its powerful manufacturing ability, defects are prone to occur and therefore a more reliable and repeatable manufacture process is in high demand. During the SLM process, the melt pool signature is the key to understanding the dynamic process status, with which it is possible to predict process failure and give guidance to real-time feedback control. In this paper, a novel method to capture melt pool signature using a U-Net-based convolutional neural network is described. A lightweight architecture was used to reduce the inference time, and an improved loss function with penalty maps was applied to better remove interferences. The model performance was evaluated by comparing both the processing time and accuracy with two conventional image segmentation algorithms, including the threshold segmentation method and the active contour method. Mean intersection over union (MIoU) was chosen as the segmentation metric. Unlike traditional algorithms, U-Net successfully eliminated the interferences, and reached the highest MIoU (0.9806) at a relatively low computational cost of 37 ms on average. The collected information from the melt pool area in various scenarios was analyzed, and its potential to indicate the problem of melt pool overheating was investigated.

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Laser-based powder bed fusion (L-PBF) is an additive manufacturing (AM) technology that uses a high-energy–density laser to scan through a powder bed and completely melts the metal powder. The environment inside the printer chamber, including the flow field of the shielding gas and the spatter particles induced by laser–powder interactions, is essential for product quality. For the first time, this work built a full-size model of printer chamber, and numerically investigated the interaction between the shielding argon flow and the laser induced spatter particles with considering laser temperature. A full-size geometric model of a commercial L-PBF printer with a Gaussian heat source was constructed, as well as a movable particle-release source model for particle injection. The distribution of the argon flow field, the temperature field, and the trajectory and deposition of spatter particles, particularly above the workbench during the L-PBF process were quantitatively analyzed. The results show that the gas flow within 30 mm above the workbench is uniform, and in the upper region of the printer chamber, the flow field is disorderly. The laser can only induce high temperature and upward gas flow in a small region close to the workbench (the height less than 1.6 mm), and the laser induced velocity disturbance in rest regions of the L-PBF printer is negligible. Particles injected towards the outlet (ID4) are mostly blown into the outlet, and in the other four injection directions, more than 90% of spatter particles are deposited inside the printer chamber, especially more than 50% deposited on the workbench. Increasing the laser power (from 100 to 200 W) has little effect on particle deposition on the workbench. Results will be helpful for improving the L-PBF product quality.

Monolayer cubic boron (B) nitride (N) terminated diamond (111) surfaces are proposed and investigated using density functional theory. The carbon (C)–N–B-terminated diamond (111) surface with a monolayer coverage of hydrogen and the C–N–B-terminated diamond (111) surface with a monolayer coverage of fluorine [named C–N–B–F-terminated (111) surface] have positive electron affinities (PEAs) with no inter-band gap states and nearly perfect alignment of nitrogen vacancy (NV). Thus, they could potentially be applied in NV-based quantum sensors. The C–B–N-terminated diamond (111) surface with a monolayer coverage of hydrogen [named C–B–N–H-terminated (111) surface], which has negative EAs (NEAs) and an adsorption energy of −3.51 eV, could potentially be employed in electron emission devices. Specifically, C–N–B–F- and C–B–N–H-terminated diamond (111) surfaces have the largest PEA (4.48 eV) and NEA (−4.00 eV), respectively, of any reported diamond surfaces. We also propose a formalism to construct multiple dipole structures on diamond surfaces to yield extremely large EAs.

Lipophagy is a lysosomal lipolytic pathway that complements the actions of cytosolic neutral lipases. Chaperon-mediated autophagy (CMA) triggers lipid droplets (LDs) breakdown, to initiate lipolysis via either cytosolic lipases or macroautophagy. SIRT3, a mitochondrial NAD+-dependent deacetylase, regulates the acetylation status and activity of many substrates involving in energy metabolism. However, the role of SIRT3 in regulating lipophagy is controversial. The current study showed that SIRT3 expression was decreased and the macroautophagy flux was blocked in the primary hepatocytes from high-fat diet fed mice and P/O (palmitic acid and oleic acid mixture) treated AML12 mouse hepatocytes, compared with the corresponding controls. SIRT3 overexpression promoted macroautophagy in LDs from P/O-treated hepatocytes through activating AMP-activated protein kinase (AMPK) and unc-51-like kinase 1, to boost LDs digestion. Gain of SIRT3 expression stimulated the formation of lysosome-associated membrane protein 2A (LAMP-2A)-heat shock cognate 71 kDa protein (HSC70)-perilipin-2 (PLN2) complex, to promote CMA process and reduce the stability of LDs in hepatocytes. Moreover, SIRT3 reduced the expression of stearoyl-CoA desaturase 1, to suppress lipogenesis. In addition, SIRT3 overexpression promoted LDs dispersion on detyrosinated microtubules, and directly deacetylated long-chain acyl-CoA dehydrogenase to enhance mitochondrial energetics. Taken together, SIRT3 ameliorates lipotoxicity in hepatocytes, which might be a potential target for the treatment of nonalcoholic fatty liver disease.

Corrections are presented for the above named paper.

Cancer is one of the most challenging diseases in the world. Recently, iron oxide nanoparticles (IONPs) are emerging materials with rapid development and high application value, and have shown great potential on tumor therapy due to their unique magnetic and biocompatible properties. However, some data hint us that IONPs were toxic to normal cells and vital organs. Thus, more data on biosafety evaluation is urgently needed. In this study, we compared the effects of silicon-coated IONPs (Si-IONPs) on two cell types: the tumor cells (Hela) and the normal cells (HEK293T, as 293 T for short), compared differences of protein composition, allocation and physical characteristics between these two cells. The major findings of our study pointed out that 293 T cells death occurred more significant than that of Hela cells after Si-IONPs treatment, and the rate and content of endocytosis of Si-IONPs in 293 T cells was more prominent than in Hela cells. Our results also showed Si-IONPs significant promoted the production of reactive oxygen species and disturbed pathways related to oxidative stress, iron homeostasis, apoptosis and ferroptosis in both two types of cells, however, Hela cells recovered from these disturbances more easily than 293 T. In conclusion, compared with Hela cells, IONPs are more likely to induce 293 T cells death and Hela cells have their own unique mechanisms to defense invaders, reminding scientists that future in vivo and in vitro studies of nanoparticles need to be cautious, and more safety data are needed for further clinical treatment.