This paper presents the development of a normal adjustment cell(NAC) in aero-robotic drilling to improve the quality of vertical drilling, by using an intelligent double-eccentric disk normal ...adjustment mechanism(2-EDNA), a spherical plain bearing and a floating compress module with sensors. After the surface normal vector is calculated based on the laser sensors’ feedback,the 2-EDNA concept is conceived specifically to address the deviation of the spindle from the surface normal at the drilling point. Following the angle calculation, depending on the actual initial position, two precise eccentric disks(PEDs) with an identical eccentric radius are used to rotate with the appropriate angles using two high-resolution DC servomotors. The two PEDs will carry the spindle to coincide with the surface normal, keeping the vertex of the drill bit still to avoid repeated adjustment and position compensation. A series of experiments was conducted on an aeronautical drilling robot platform with a precise NAC. The effect of normal adjustment on bore diameter, drilling force, burr size, drilling heat, and tool wear was analyzed. The results validate that using the NAC in robotic drilling results in greatly improved vertical drilling quality and is attainable in terms of intelligence and accuracy.
Traditional physical-based models have generally been used to model the resistive-switching behavior of resistive-switching memory (RSM). Recently, vacancy-based conduction-filament (CF) growth ...models have been used to model device characteristics of a wide range of RSM devices. However, few have focused on learning the other-device-parameter values (e.g., low-resistance state, high-resistance state, set voltage, and reset voltage) to compute the compliance-current (CC) value that controls the size of CF, which can influence the behavior of RSM devices. Additionally, traditional CF growth models are typically physical-based models, which can show accuracy limitations. Machine learning holds the promise of modeling vacancy-based CF growth by learning other-device-parameter values to compute the CC value with excellent accuracy via examples, bypassing the need to solve traditional physical-based equations. Here, we sidestep the accuracy issues by directly learning the relationship between other-device-parameter values to compute the CC values via a data-driven approach with high accuracy for test devices and various device types using machine learning. We perform the first modeling with machine-learned device parameters on aluminum-nitride-based RSM devices and are able to compute the CC values for nitrogen-vacancy-based CF growth using only a few RSM device parameters. This model may now allow the computation of accurate RSM device parameters for realistic device modeling.
Resistive-switching memory (RSM) is one of the most promising candidates for next-generation edge computing devices due to its excellent device performance. Currently, a number of experimental and ...modeling studies have been reported to understand the conduction behaviors. However, a complete physical picture that can describe the conduction behavior is still missing. Here, we present a conduction model that not only fully accounts for the rich conduction behaviors of RSM devices by harnessing a combination of electronic and thermal considerations via electron mobility and trap-depth and with excellent accuracy but also provides critical insight for continued design, optimization, and application. A physical model that is able to describe both the conduction and switching behaviors using only a single set of expressions is achieved. The proposed model reveals the role of temperature, mobility of electrons, and depth of traps, and allows accurate prediction of various set and reset processes obtained by an entirely new set of general current-limiting parameters.
Orange light (593 nm, 5D0→7F1) and red light (613 nm, 5D0→7F2) are the two most important emission lines belonging to Eu3+ ions in high and low symmetries, respectively, making them important ...indicators for judging the nanoenvironment around Eu3+ ions. Therefore, obtaining significant red light emission in Eu3+ doped SnO2 nanocrystals requires anchoring Eu3+ ions onto lattice sites with low symmetries, which can be achieved through maximizing surface doping. To achieve this goal, we coated very thin Eu3+ doped SnO2 nanocrystal (10–20 nm) coatings on extremely dispersed SiO2 hollow spheres (500 nm in diameter) to investigate doping dependent luminescent properties. A significant increase in red emission was observed in such a system, accompanied by a significant attenuation of orange light, and the intensity of red emission increases with increasing Eu3+ concentration. When the concentration of Eu3+ exceeds 3 at%, the intensity of red light emission sharply decreases due to the quenching effect. For the optimal doped hollow sphere sample (3 at%), the asymmetry ratio (red/orange light integration intensity ratio) under indirect excitation is 5.58, which further rises to 11.3 under direct excitation, while the asymmetry ratio of SnO2 nanopowder with the same doping concentration is less than 0.2 under both excitation modes, indicating that the current structural design plays a significant role in the modulation of Eu3+ ion luminescence. Our research not only demonstrates an effective method to enhance the red light emission of Eu3+ doped SnO2 nanocrystals, but also provides a method for manipulating the polychromatic luminescence of such systems.
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•The extremely thin layer of Eu3+ doped SnO2 nanoparticles was successfully coated on highly-dispersed SiO2 hollow spheres.•SiO2@SnO2: Eu system achieves anchoring of Eu3+ ions at low symmetric sites by maximizing surface doping.•The design can adjust the intensity ratio of red/orange emission of Eu3+, achieving a significant enhancement of red light..•The current system demonstrates an effective method for enhancing the red light emission of Eu3+ doped SnO2 nanocrystals.
Drilling end-effector is a key unit in autonomous drilling robot. The perpendicularity of the hole has an important influence on the quality of airplane assembly. Aiming at the robot drilling ...perpendicularity, a micro-adjusting attitude mechanism and a surface normal measurement algorithm are proposed in this paper. In the mechanism, two rounded eccentric discs are used and the small one is embedded in the big one, which makes the drill’s point static when adjusting the drill’s attitude. Thus, removal of drill’s point position after adjusting the drill attitude can be avoided. Before the micro-adjusting progress, four non-coplanar points in space are used to determine a unique sphere. The normal at the drilling point is measured by four laser ranging sensors. The adjusting angles at which the motors should be rotated to adjust attitude can be calculated by using the deviation between the normal and the drill axis. Finally, the motors will drive the two eccentric discs to achieve micro-adjusting progress. Experiments on drilling robot system and the results demonstrate that the adjusting mechanism and the algorithm for surface normal measurement are effective with high accuracy and efficiency.
AbstractGreen’s functions for the continuous system of a beam with overhangs are constructed in this paper. Green’s functions for the corresponding mathematically transformed system are proven to be ...of oscillating kernels. The basic oscillating properties with respect to the natural frequencies and modes of the corresponding systems are revealed and proven. The number of the nodes of the flexural moment modes of the system is determined by analyzing its conjugated system. Furthermore, some qualitative properties of its displacement modes, rotational modes, moment modes, and shearing force modes are also obtained.
Celotno besedilo
Dostopno za:
DOBA, FGGLJ, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In this letter, we propose and experimentally demonstrate a high-speed true random number generator (TRNG) by exploiting the probabilistic delay time of threshold switching (TS) in a unified ...selector-resistive random access memory (RRAM). The device consists of dual functional layers (VO2/HfOx) and exhibits high endurance and fast switching speed, enabling a high bit generation rate (>28M/s). The switching parameters have been comprehensively investigated to obtain a stable and fine entropy. The generated bitstream successfully passes 12 National Institute of Standards and Technology (NIST) statistical tests without any postprocessing. The randomness and independence of the entropy source are justified by the autocorrelation test at a 95% confidence level, demonstrating great potential in high-performance hardware security and stochastic computing implementations.
Analytical solution of the free vibration of the isosceles right triangle membrane with several different boundary conditions was obtained. Some qualities of the solution were studied, especially, ...the completeness’s of the analytical solution were proved.
(GA) is a kind of red alga homologous to medicine and food and is distributed all over the world. Studies on GA are mainly focused on its polysaccharides, with little research on the ethanol extract. ...The ethanol extract of
(GAE) was subjected to a reverse-phase column to obtain 7 components. Among them, 100% methanol solution (GAM), enriched with phytene-1,2-diol, exhibited the strongest DPPH free radical scavenging activity (IC
= 0.17 mg mL
). Subsequently, high-fat male flies (HMFs) were used as a model to explore the antioxidant and anti-aging effects of GAM
. Studies showed that GAM can effectively prolong the lifespan of HMFs. When GAM concentrations were 0.2 and 1.0 mg mL
, the average lifespan of HMFs was increased by 28.7 and 40.7%, respectively, while the longest lifespan of HMFs was increased by 20.55% and 32.88%, respectively. Further research revealed that GAM can significantly downregulate the levels of malondialdehyde (MDA) and protein carbonyl (PCO), and can significantly upregulate the levels of catalase (CAT) and total superoxide dismutase (T-SOD). In addition, by analyzing differential metabolites, we found that GAM relieves aging caused by oxidative stress by regulating amino acid, lipid, sugar, and energy metabolism. The GAM group significantly regulated the levels of adenine, cholic acid, glutamate, L-proline, niacin, and stachyose which tend to recover to the levels of the normal diet male fly (NMF) group. In general, our research provides ideas for the high-value utilization of GA and provides a lead compound for the research and development of anti-aging food or medicine.
For memory and in-memory computing applications, the multi-level cell (MLC) capability is one of the most favorable characteristics of resistive random-access memory (RRAM). However, achieving stable ...MLCs typically demands a time-consuming programming strategy. This paper presents a novel programming algorithm, Adaptive Step Adjustment Programming (ASAP), implemented on 1Mb RRAM chips fabricated using commercial 40nm CMOS technology. Our experimental results showcase a remarkable improvement in 16-level MLC programming efficiency (up to 10x). Furthermore, the MLC retention characteristics exhibit remarkable stability even after 10 4 s thermal stress at 150°C.
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