In this study, the application of characteristic impedance in estimating specific energy and average fragment size of rocks was investigated during rock breakage at high strain rates. To achieve ...this, rock specimen was prepared in accordance with recommendations of the International Society for Rock Mechanics and broken at high strain rates using the split Hopkinson’s pressure bar system. Results reveal that although strain rate is well related to specific energy and average fragment size of broken rocks, the product of characteristic impedance and strain rate is more reliable for estimating the forementioned parameters. In addition, strain rate and dissipated energy generally increase at higher incident energies while the average fragment size of broken rocks reduces at higher strain rates. Based on these findings, more studies on indirect estimation of energy requirement for rock breakage to desired average fragment sizes is recommended from the product of characteristic impedance and strain rate.
Highlights
Rock classification and rate parameters are crucial for estimating breakage characteristics of rocks at high strain rates.
Novel application of the product of characteristic impedance and strain rate is proposed for estimating breakage characteristics of rocks at high strain rates.
The product of characteristic impedance and strain rate is more reliable for estimating specific energy and average fragment size from impulse rock breakage.
Voice communication using an air-conduction microphone in noisy environments suffers from the degradation of speech audibility. Bone-conduction microphones (BCM) are robust against ambient noises but ...suffer from limited effective bandwidth due to their sensing mechanism. Although existing audio super-resolution algorithms can recover the high-frequency loss to achieve high-fidelity audio, they require considerably more computational resources than is available in low-power hearable devices. This paper proposes the first-ever real-time on-chip speech audio super-resolution system for BCM. To accomplish this, we built and compared a series of lightweight audio super-resolution deep-learning models. Among all these models, ATS-UNet was the most cost-efficient because the proposed novel Audio Temporal Shift Module (ATSM) reduces the network's dimensionality while maintaining sufficient temporal features from speech audio. Then, we quantized and deployed the ATS-UNet to low-end ARM micro-controller units for a real-time embedded prototype. The evaluation results show that our system achieved real-time inference speed on Cortex-M7 and higher quality compared with the baseline audio super-resolution method. Finally, we conducted a user study with ten experts and ten amateur listeners to evaluate our method's effectiveness to human ears. Both groups perceived a significantly higher speech quality with our method when compared to the solutions with the original BCM or air-conduction microphone with cutting-edge noise-reduction algorithms.
Steady-state visual evoked potential (SSVEP) has become a powerful tool for Brain Computer Interface (BCI) because of its high signal-to-noise ratio, high information transmission rate, and minimal ...user training. At present, the edge information of each region cannot be identified in spatial coding based on SSVEP-BCI technology, and the user experience is poor. To solve this problem, this paper designed a new paradigm to explore the relationship between the fixation point position of continuous sliding and the correlation coefficient ratio in the dual-frequency case. Firstly, the standard sinusoidal signal was employed to simulate the Electroencephalogram (EEG) signal, which verified the reliability of characterizing the amplitude variation of test signal by correlation coefficient. Then, the relationship between the amplitude response of SSVEP and the distance between the fixation point and the stimulus in the horizontal direction was tested by Canonical Correlation Analysis (CCA) and Filter bank CCA (FBCCA). Finally, the experimental data were offline analyzed under the condition of continuous sliding of the fixation point. It is feasible and reasonable to detect the amplitude change of frequency component in SSVEP by utilizing the spatial coding method in this paper to improve the extraction accuracy of spatial information.
The sub‐nanometer‐diameter transitional‐metal chalcogenides (M6X6) molecular wires are ideal 1D quantum systems. The electronic properties of such system are very sensitive to the interface ...interaction and local imperfection. Here, the atomic structure and local electronic structure of van der Waals (vdW) stacking Mo6Te6 nanowires fabricated by using molecular beam epitaxy are reported. Atomic‐resolution scanning tunneling microscopy measurement shows that the vdW interface distance varies from 0.71 to 1.05 nm when Mo6Te6 wires stacked on graphite, MoTe2, and Mo6Te6 surfaces. Scanning tunneling spectroscopy confirmed the 1D quantum effect of van Hove singularity and Tomonaga–Luttinger liquid behavior at 77.8 K. Single Te vacancies and their effect to the local structure distortion are observed as well. These observations shed light on the local structure and quantum effects of the M6X6 nanowire materials, which may find applications in future electronic devices.
By combination of vacuum annealing and fast cooling of epitaxial MoTe2 ultrathin films, Mo6Te6 nanowires stacking on varying van der Waals surface are obtained. Through scanning tunneling microscopy measurement, local defects in forms of single Te vacancies or axial twist are observed. Moreover, the 1D electronic properties of pristine and defective Mo6Te6 nanowires are confirmed.
In river management, it is important to obtain ice velocity quickly and accurately during ice flood periods. However, traditional ice velocity monitoring methods require buoys, which are costly and ...inefficient to distribute. It was found that UAV remote sensing images combined with machine vision technology yielded obvious practical advantages in ice velocity monitoring. Current research has mainly monitored sea ice velocity through GPS or satellite remote sensing technology, with few reports available on river ice velocity monitoring. Moreover, traditional river ice velocity monitoring methods are subjective. To solve the problems of existing time-consuming and inaccurate ice velocity monitoring methods, a new ice velocity extraction method based on UAV remote sensing technology is proposed in this article. In this study, the Mohe River section in Heilongjiang Province was chosen as the research area. High-resolution orthoimages were obtained with a UAV during the ice flood period, and feature points in drift ice images were then extracted with the scale-invariant feature transform (SIFT) algorithm. Moreover, the extracted feature points were matched with the brute force (BF) algorithm. According to optimization results obtained with the random sample consensus (RANSAC) algorithm, the motion trajectories of these feature points were tracked, and an ice displacement rate field was finally established. The results indicated that the average ice velocities in the research area reached 2.00 and 0.74 m/s, and the maximum ice velocities on the right side of the river center were 2.65 and 1.04 m/s at 16:00 on 25 April 2021 and 8:00 on 26 April 2021, respectively. The ice velocity decreased from the river center toward the river banks. The proposed ice velocity monitoring technique and reported data in this study could provide an effective reference for the prediction of ice flood disasters.
Point-of-care testing (POCT) techniques based on microfluidic devices enabled rapid and accurate tests on-site, playing an increasingly important role in public health. As the critical component of ...capillary-driven microfluidic devices for POCT use, the capillary microfluidic valve could schedule multi-step biochemical operations, potentially being used for broader complex POCT tasks. However, owing to the reciprocal relationship between the capillary force and aperture in single-pore microchannels, it was challenging to achieve a high gating threshold and high operable liquid volume simultaneously with existing 2D capillary trigger valves. This paper proposed a 3D capillary-driven multi-microporous membrane-based trigger valve to address the issue. Taking advantage of the high gating threshold determined by micropores and the self-driven capillary channel, a 3D trigger valve composed of a microporous membrane for valving and a wedge-shaped capillary channel for flow pumping was implemented. Utilizing the capillary pinning effect of the multi-micropore membrane, the liquid above the membrane could be triggered by putting the drainage agent into the wedge-shaped capillary channel to wet the underside of the membrane, and it could also be cut off by taking away the agent. After theoretical analysis and performance characterizations, the 3D trigger valve performed a high gating threshold (above 1000 Pa) and high trigger efficiency with an operable liquid volume above 150 μL and a trigger-to-drain time below 6 s. Furthermore, the retention and trigger states of the valve could be switched for repeatable triggering for three cycles within 5 min. Finally, the microbead-based immunoreaction and live cell staining applications verified the valve's ability to perform multi-step operations. The above results showed that the proposed 3D trigger valve could be expected to play a part in wide-ranging POCT application scenarios.
The 2H‐MoTe2 is a well‐known layered 2D semiconductor that is considered as a promising material for next‐generation microelectronic and optoelectronic devices. Te‐deficiency‐induced defective ...structures, like Te vacancy and mirror twin boundary (MTB), would be generated at elevated temperatures. However, the temperature‐dependent evolution of such defects and their influence on the macroscopic electrical transport property of 2H‐MoTe2 is unclear. Herein, the semiconductor–metal transition phenomenon in 2H‐MoTe2−x mediated by the evolving disordered MTB network with increasing Te deficiency is reported on. The samples are grown by molecular beam epitaxy, while the Te deficiency is tuned by post‐growth flash annealing in ultra‐high vacuum. Low‐temperature scanning tunneling microscope investigation discloses the medium‐range disorder evolution of the MTB network incorporated in the 2H‐MoTe2, which eventually transforms to an ordered metallic Mo5Te8 metastable phase. The scanning tunneling spectroscopy shows rich in‐gap states localized at the MTBs, which provide a conducting channel in the semiconductor. The ultra‐high vacuum in situ transport measurement shows a gradual decrease of resistance of the sample upon flash annealing from 50 to 480 °C, confirming the influence of Te deficiency on the transport property, which would play an essential role in the device performance and durability.
Electron transport property evolution is observed in 2H‐MoTe2 with Te‐deficiency defects. The atomic‐scale scanning tunneling microscope characterization reveals the evolution of disordered mirror twin boundary. The in situ transport measurement confirms the resistance declined by two orders of magnitude in the sample with increasing Te deficiency created by flash annealing.
Abstract Simultaneously achieving high sensitivity and detection speed with traditional solid-state biosensors is usually limited since the target molecules must passively diffuse to the sensor ...surface before they can be detected. Microfluidic techniques have been applied to shorten the diffusion time by continuously moving molecules through the biosensing regions. However, the binding efficiencies of the biomolecules are still limited by the inherent laminar flow inside microscale channels. In this study, focused traveling surface acoustic waves were directed into an acoustic microfluidic chip, which could continuously enrich the target molecules into a constriction zone for immediate detection of the immune reactions, thus significantly improving the detection sensitivity and speed. To demonstrate the enhancement of biosensing, we first developed an acoustic microfluidic chip integrated with a focused interdigital transducer; this transducer had the ability to capture more than 91% of passed microbeads. Subsequently, polystyrene microbeads were pre-captured with human IgG molecules at different concentrations and loaded for detection on the chip. As representative results, ~0.63, 2.62, 11.78, and 19.75 seconds were needed to accumulate significant numbers of microbeads pre-captured with human IgG molecules at concentrations of 100, 10, 1, and 0.1 ng/mL (~0.7 pM), respectively; this process was faster than the other methods at the hour level and more sensitive than the other methods at the nanomolar level. Our results indicated that the proposed method could significantly improve both the sensitivity and speed, revealing the importance of selective enrichment strategies for rapid biosensing of rare molecules.
Real-time transformation was important for the practical implementation of impedance flow cytometry. The major obstacle was the time-consuming step of translating raw data to cellular intrinsic ...electrical properties (e.g., specific membrane capacitance C
and cytoplasm conductivity σ
). Although optimization strategies such as neural network-aided strategies were recently reported to provide an impressive boost to the translation process, simultaneously achieving high speed, accuracy, and generalization capability is still challenging. To this end, we proposed a fast parallel physical fitting solver that could characterize single cells' C
and σ
within 0.62 ms/cell without any data preacquisition or pretraining requirements. We achieved the 27000-fold acceleration without loss of accuracy compared with the traditional solver. Based on the solver, we implemented physics-informed real-time impedance flow cytometry (piRT-IFC), which was able to characterize up to 100,902 cells' C
and σ
within 50 min in a real-time manner. Compared to the fully connected neural network (FCNN) predictor, the proposed real-time solver showed comparable processing speed but higher accuracy. Furthermore, we used a neutrophil degranulation cell model to represent tasks to test unfamiliar samples without data for pretraining. After being treated with cytochalasin B and N-Formyl-Met-Leu-Phe, HL-60 cells underwent dynamic degranulation processes, and we characterized cell's C
and σ
using piRT-IFC. Compared to the results from our solver, accuracy loss was observed in the results predicted by the FCNN, revealing the advantages of high speed, accuracy, and generalizability of the proposed piRT-IFC.
Achieving passive microparticle filtration with micropore membranes is challenging due to the capillary pinning effect of the membranes. Inspired by the teapot effect that occurs when liquid (tea) is ...poured from a teapot spout, we proposed a tap-triggered self-wetting strategy and utilized the method with a 3D sieve to filter rare cells. First, a 3D-printed polymer tap-trigger microstructure was implemented. As a result, the 3 µm micropore membrane gating threshold (the pressure needed to open the micropores) was lowered from above 3000 to 80 Pa by the tap-trigger microstructure that facilated the liquid leakage and spreading to self-wet more membrane area in a positive feedback loop. Then, we implemented a 3D cone-shaped cell sieve with tap-trigger microstructures. Driven by gravity, the sieve performed at a high throughput above 20 mL/min (DPBS), while the micropore size and porosity were 3 µm and 14.1%, respectively. We further filtered leukocytes from whole blood samples with the proposed new 3D sieve, and the method was compared with the traditional method of leukocyte isolation by chemically removing red blood cells. The device exhibited comparable leukocyte purity but a higher platelet removal rate and lower leukocyte simulation level, facilitating downstream single-cell analysis. The key results indicated that the tap-triggered self-wetting strategy could significantly improve the performance of passive microparticle filtration.
