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Original instrumental setups embedded in industrial-type multi-diamond-wire sawing equipment are presented for in situ measurements of the apparent wire diameter, the vertical force applied to the wire web, and the wire-web bow during the cutting of crystalline silicon bricks into wafers. The proportionality relationship between the vertical force and the wire bow during the cut of a Czochralski silicon brick is, for the first time, experimentally observed as expected by the theoretical calculations. As a result, the in situ bow measurement is shown to provide a direct control of the cutting efficiency, which is inversely proportional to the vertical force. In addition, the wire-wear evolution during successive cuts is analyzed using the in situ measurement of the apparent wire diameter together with the in situ bow measurements for equivalent cutting conditions using several bow sensors distributed above the wire web. The three-dimensional plot of the cutting efficiency resulting from the bow measurement processing gives access to the distribution of the cutting efficiency along the wire web during the progress of the cut. Given the homogeneous properties of the silicon material used, the cutting efficiency proves to be a representative of the wire-wear. Moreover, the unique capability of the in situ bow measurement to provide a distribution of the measurements on the wire web during the cut allows studying the wire web behavior and the wire cutting efficiency distribution for different cutting conditions. Thanks to the innovative design of the instrumentation coupled with a data analysis based on a deep understanding of the involved physical phenomena, the in situ bow measurement is demonstrated to be a powerful tool to optimize the cutting process in terms of wafer quality and cost efficiency. Moreover, it can provide real-time information opening the door for tuning the parameters during the cutting process.In semiconductor device history, a trend is observed where narrowing and increasing the number of material layers improve device functionality, with diodes, transistors, thyristors, and superlattices following this trend. While superlattices promise unique functionality, they are not widely adopted due to a technology barrier, requiring advanced fabrication, such as molecular beam epitaxy and lattice-matched materials. Here, a method to design quantum devices using amorphous materials and physical vapor deposition is presented. It is shown that the multiplication gain M depends on the number of layers of the superlattice, N, as M = kN, with k as a factor indicating the efficiency of multiplication. This M is, however, a trade-off with transit time, which also depends on N. To demonstrate, photodetector devices are fabricated on Si, with the superlattice of Se and As2Se3, and characterized using current-voltage (I-V) and current-time (I-T) measurements. For superlattices with the total layer thicknesses of 200 nm and 2 μm, the results show that k200nm = 0.916 and k2μm = 0.384, respectively. The results confirm that the multiplication factor is related to the number of superlattice layers, showing the effectiveness of the design approach.Ultrafast science depends on different implementations of the well-known pump-probe method. Here, we provide a formal description of ultrafast disruptive probing, a method in which the probe pulse disrupts a transient species that may be a metastable ion or a transient state of matter. Disruptive probing has the advantage of allowing for simultaneous tracking of the yield of tens of different processes. Our presentation includes a numerical model and experimental data on multiple products resulting from the strong-field ionization of two different molecules, partially deuterated methanol and norbornene. The correlated enhancement and depletion signals between all the different fragmentation channels offer comprehensive information on photochemical reaction pathways. In combination with ion imaging and/or coincidence momentum imaging or as complementary to atom-specific probing or ultrafast diffraction methods, disruptive probing is a particularly powerful tool for the study of strong-field laser-matter interactions.This paper presents a hardware emulator of microelectromechanical systems (MEMS) vibratory gyroscopes that can be used for characterization and verification of control/interface electronics by means of hardware-in-the-loop testing, thus speeding up design cycles by decoupling these tasks from the often longer MEMS design and fabrication cycles. The easily re-configurable hardware emulator is completely synthesized on a field-programmable gate array board. The emulator is shown to successfully model the Coriolis effect along with the prominent error sources present in typical MEMS gyroscopes, namely, quadrature error, spring nonlinearity, and thermo-mechanical, electronic, and environmental noise. Preliminary experimental results characterizing the noise and nonlinearity models based on a prototype with user-controllable device parameters synthesized on the Xilinx Zynq®-7020 SoC (Digilent ZYBO Z7 board) are presented.We propose a variable-magnification full-field x-ray microscope using two Fresnel zone plates (FZPs). https://www.selleckchem.com/products/i-191.html By moving the positions of the two FZPs, the magnification can be continuously changed even if the sample and camera positions are fixed. It was demonstrated that the magnification can be changed in the range of 25-150× using a hard x-ray beam at 14.4 keV. Using the first FZP as a convex lens and the second FZP as a concave lens, high magnification can be achieved at a short camera length. Even under the condition of a camera length of about 7 m, a magnification higher than 300× was achieved, and a line and space pattern with a pitch of 40 nm was observed at 10 keV. By inserting a knife edge at an appropriate position in the optical system, a phase-contrast image can be easily obtained, which is useful for soft-tissue observation of biological samples.We demonstrate the potential of using digital stereo micro-photogrammetry for the analysis and modeling of the habit and sectoral structure of real high-pressure high-temperature single-crystal diamonds. A prototype scanning system with a resolution of 5 μm has been implemented based on a digital single-lens reflex camera, making it possible to create highly accurate reproductions of crystal shapes with a minimum size of 4 mm. This method makes it possible to monitor the effect of actual conditions on the physical processes of crystal growth, which is a useful advance for the development of active device elements based on semiconductor diamonds.With the development of remote cardiac healthcare, wearable devices for electrocardiogram (ECG) monitoring are stringent requirements to cope with this rapid growth of demands. Due to the advantages of no-contact ECG measuring methods in safety, convenience, and comfortableness, it is more suitable for wearable long-term ECG monitoring than the conventional Ag/AgCl electrodes. The capacitance coupling printed circuit board (PCB) electrode with ultra-high input impedance proposed in this paper can realize non-contact ECG measurement through a multi-layer insulating medium. Then, an eight-channel ECG signal processing circuit is also designed and fabricated. In addition, the following important performance properties of the non-contact ECG measuring system, such as the input impedance, the phase-frequency characteristic, the amplitude-frequency characteristic, the coupling coefficient, and the input short-circuit input noise, were all experimentally measured. The synchronous comparison between the Ag/AgCl electrode and the PCB electrode was also conducted to verify the accuracy of the non-contact measuring method. Finally, the influence of the lead positions, coupling medium parameters, and the body motion states was also experimentally studied. The results demonstrate that the proposed non-contact ECG measuring method based on capacitance coupling PCB electrodes can effectively collect the main components of ECG signals and cardiac rhythm in various situations.In order to overcome the many shortcomings of traditional hot-wire thermal conductivity sensor design, a new design method was proposed in which a graphene-composite carbon nanotube mixed carbon material was used as a thermal conductivity sensor carrier instead of nano-alumina particles. Taking advantage of the large specific surface area and high thermal conductivity of graphene, as well as the characteristics of a large number of gas transport channels modified by carbon nanotubes, a high-efficiency gas heat exchange medium is made. In order to improve the consistency of the product, electrochemical preparation of an aluminum oxide film material is used to make the chip substrate of the thermal conductivity sensor by MEMS process technology, and the heating sensitive electrode of the sensor is made by a thick film process. Experiments show that the sensor prepared by this method has high sensitivity and zero point stability and has greatly improved the detection accuracy and response time. The sensitivity of the sensor to hydrogen detection increases to 3.287 mV/1%H2, and the response time is shorter than 5.4 s. The research results have good application prospects.In a tokamak, disruption is defined as losing control over a confined plasma resulting in sudden extinction of the plasma current. Machine learning offers potent solutions to classify plasma discharges into disruptive and non-disruptive classes. Evolving experimental programs reduce the performance of machine learning models, and also, the need for labeling the huge volume of data incurs more labor cost and time. This paper proposes a data-driven based machine learning technique that employs an active learning approach for labeling and classification of plasma discharges. The designed model uses 117 normally terminated shots and 70 disruptive shots with 14 labeled diagnostic signals. The stacking classifier is built over three base learners logistic regression, reduced error pruning tree, and categorial boost algorithm, and the logistic regression technique is used at the meta-learner. An active learning approach is proposed for labeling the unlabeled dataset using a modified uncertainty sampling technique with minimal queries. The proposed model queries the unlabeled data to an oracle based on a selection strategy with uncertainty sampling using entropy metrics. The new labeled data and the class probabilities of the base classifiers are channeled to the final predictor for classifying the plasma discharge. The proposed model achieves an accuracy of 98.75% in classifying the disruptive vs non-disruptive discharges, with a minimally trained dataset, and also, it is free from aging of predictors.New approaches for lifetime determination using data from recoil distance Doppler-shift experiments are presented based on the fundamental properties of the functions describing the time evolution of the population of excited nuclear states. To some extent, one of them represents a contraction of the well-known Differential decay-curve method (DDCM) by using the most reliable data point [the maximum of the ni(t) function describing the population of level i in time] and a purely numerical procedure avoiding any fitting of decay curves. The combination with the standard DDCM analysis is promising for improving the reliability and the precision of the results for the lifetimes obtained. The novel part of the approach consists of using a chain of equations at the consecutive maxima of the ni(t) functions, which allow us to precisely determine the ratio of the lifetimes of two consecutive levels and, in the case where one of these lifetimes is known, to determine the unknown one. In addition, a simple integral derivation of the lifetime is presented involving the peak areas measured at different distances, and an application of the first moments (expectation values and centroids in time) of the ni(t) functions for determining lifetimes is also demonstrated to be useful.