Phase Pattern Research Articles

Comprehensive characterization of a microfluidic platform for DEP manipulation and bio-impedance detection using multi-sized polystyrene microbeads

Dielectrophoresis (DEP) manipulation combined with micro-electric impedance spectroscopy (µEIS) presents a sophisticated approach for cellular analysis and dielectric characterization. While conventional cell analysis techniques rely on complex labeling methods with inherent limitations, integrating DEP and µEIS offers non-invasive, label-free cellular characterization with enhanced sensitivity. This study presents an innovative dual-mode DEP platform incorporating both levitation (LEVDEP) and rotational (ROTDEP) forces, integrated with high-precision impedance measurement capabilities on one chip, enabling simultaneous Cell controlling and manipulation and dielectric signature extraction within a single microfluidic device. The fabricated and developed microfluidic platform demonstrated exceptional particle discrimination through the dual mode, with distinct responses for both particle populations. Under FlEV.DEP10.4μm 2.01 MHz showed a 63.4% magnitude increase, while FlEV.DEP24.9μm , particles exhibited a higher 81.2% increase at the same force, yielding a 2.48 × enhancement in discrimination ratio compared to no-DEP conditions. ROTDEP at 110 kHz induced even more pronounced differences, with FROT.DEP10.4μm showing a 120% magnitude increase (phase patterns: −24.501° to −34.363°) and FROT.DEP24.9μm µm particles demonstrating a 145% increase (phase patterns: −31.267° to −42.891°), achieving a 3.16 × discrimination ratio enhancement. The impedance spectrum revealed distinct frequency-dependent signatures, with ROTDEP showing superior mid-frequency discrimination (10.4 µm: 1.9370×104 Ω vs 24.9 µm: 2.0542×104 Ω at 110 kHz) and LEVDEP optimizing high-frequency characterization (10.4 µm: 1.6677×104 Ω vs 24.9 µm: 1.5849×104 Ω at 2.01 MHz). These signatures demonstrate the platform’s comprehensive particle characterization capabilities through complementary DEP forces. The dual-mode approach enhanced discrimination ratios by 2.48 × under Lev.force and 3.16 × under LEV.force at selected characteristic frequency range compared to NonDEPforce conditions. Comprehensive impedance analysis through frequency spectrum (10 kHz—2.01 MHz) revealed unique frequency-dependent cell signatures, ROT.force demonstrating superior mid-frequency discrimination (magnitude differences of 1.9370 × 104 Ω vs 2.0542 × 104 Ω at 110 kHz) and LEVDEP optimizing high-frequency characterization (1.6677 × 104 Ω vs 1.5849 × 104 Ω at 2.01 MHz). Impedance dielectric analysis conducted over the 10 kHz to 2.01 MHz frequency range demonstrated frequency-dependent characteristics for each selected cell population. ROTDEP enhanced the discrimination in the mid-frequency range (110 kHz), with 10.4 µm particles presenting impedance magnitudes of 1.9370 × 104 Ω, while 24.9 µm particles displayed 2.0542 × 104 Ω, yielding a distinct separation ratio of 1.06 × . In the high-frequency domain (2.01 MHz), LEVDEP optimized particle characterization revealed that 10.4 µm particles exhibited a resistance of 1.6677 × 104 Ω. In contrast, 24.9 µm particles showed a resistance of 1.5849 × 104 Ω, resulting in a separation ratio of 1.05 × . The dual-mode approach markedly improved discrimination capabilities, with LEVDEP demonstrating a 2.48 × enhancement and ROTDEP exhibiting a 3.16 × increase in separation ratios relative to no-DEP conditions. This proposed dual-force implementation exhibited notable efficacy in designated frequency ranges: ROTDEP excelled in mid-frequency discrimination, achieving magnitude differences of 11.72 × 103 Ω between particle populations, whereas LEVDEP optimized high-frequency characterization with differences of 8.28 × 103 Ω, facilitating comprehensive particle discrimination through complementary DEP forces. This study establishes a novel microfluidic platform integrating dual-mode DEP manipulation with high-sensitivity dielectric features impedance detection, achieving a 163.1% enhancement in signal-to-noise SNR ratio compared to the conventional impedance mode. The proposed system demonstrates exceptional particle discrimination capabilities, with LEVDEP achieving a 63.4% and 81.2% magnitude increase for 10.4 µm and 24.9 µm particles, respectively, at 2.01 MHz. In comparison, ROTDEP induced more pronounced increases of 120% and 145% at 110 kHz. The proposed system significantly improved discrimination ratios (2.48 × under LEVDEP and 3.16 × under ROTDEP) relative to no-DEP conditions, identifying clear phase behavior patterns for both particle populations. Impedance analysis over the 10 kHz to 2.01 MHz frequency range identified distinct frequency-dependent characteristics. ROTDEP exhibited enhanced mid-frequency discrimination, measuring 1.9370 × 104 Ω compared to 2.0542 × 104 Ω, while LEVDEP provided optimized high-frequency characterization, with values of 1.6677 × 104 Ω versus 1.5849 × 104 Ω. This system, which is label-free and non-invasive, facilitates cellular dielectric analysis with improved throughput and measurement precision. It provides substantial benefits for biological research, medical diagnostics, and drug analysis and development through its dual-force implementation and extensive impedance characterization capabilities.

How do red foxes (Vulpes vulpes) explore their environment? Characteristics of movement patterns in time and space

BackgroundMany animals must adapt their movements to different conditions encountered during different life phases, such as when exploring extraterritorial areas for dispersal, foraging or breeding. To better understand how animals move in different movement phases, we asked whether movement patterns differ between one way directed movements, such as during the transient phase of dispersal or two way exploratory-like movements such as during extraterritorial excursions or stationary movements.MethodsWe GPS collared red foxes in a rural area in southern Germany between 2020 and 2023. Using a random forest model, we analyzed different movement parameters, habitat features—for example landclasses and distances to linear structures—and time variables (season and time of day) within red fox exploratory, transient and stationary movement phases to characterize phase specific movement patterns and to investigate the influence of different variables on classifying the movement phases.ResultsAccording to the classification model, the movement patterns in the different phases were characterized most strongly by the variables persistence velocity, season, step length and distance to linear structures. In extraterritorial areas, red foxes either moved straight with high persistence velocity, close to anthropogenic linear structures during transient movements, or more tortuously containing a higher variance in turning angles and a decrease in persistence velocity during exploratory-like movements. Transient movements mainly took place during autumn, whereas exploratory-like movements were mainly conducted during winter and spring.ConclusionMovement patterns of red foxes differ between transient, exploratory and stationary phases, reflecting displacement, searching and resident movement strategies. Our results signify the importance of the combined effect of using movement, habitat and time variables together in analyzing movement phases. High movement variability may allow red foxes to navigate in extraterritorial areas efficiently and to adapt to different environmental and behavioral conditions.

Exploring the Thermodynamics and Dynamics of CO2 Using Rigid Models

Understanding the behavior of carbon dioxide (CO2) under varying thermodynamic conditions is essential for optimizing processes such as Carbon Capture and Storage (CCS) and supercritical fluid extraction. This study employs molecular dynamics (MD) simulations with the EPM2 and TraPPE-small force fields to examine CO2 phase behavior, structural characteristics, and transport properties across a temperature range of 228–500 K and pressures from 1 to 150 atm. Our findings indicate a good agreement between simulated and experimental liquid–vapor coexistence curves, validating the capability of both force fields to model CO2 accurately in a wide range of thermodynamical conditions. Radial distribution functions (RDFs) reveal distinct interaction patterns in liquid and supercritical phases, while mean squared displacement (MSD) analyses show diffusivity increasing from 5.2×10−9 m2/s at 300 K to 1.8×10−8 m2/s at 500 K. Additionally, response functions such as the heat capacity effectively capture phase transitions. These findings provide quantitative insights into CO2 phase behavior and transport properties, enhancing the predictive reliability of simulations for CCS and related industrial technologies. This work bridges gaps in the CO2 modeling literature and highlights the potential of MD simulations in advancing sustainable applications.

Analyzing failure mechanisms and predicting step-like displacement: Rainfall and RWL dynamics in lock-unlock landslides

Lock-unlock landslides have thick sliding zones that store a lot of energy. This makes them start quickly, happen suddenly, and have serious consequences. Therefore, it becomes urgent to study the deformation and failure mechanisms of such landslides and develop rational predictive models. Taking the Jiuxianping landslide as an example, this study investigates the regularity of landslide displacement changes using multi-source data, focusing on the abrupt displacement patterns in the unlock phase. Furthermore, employing Transient Release and Inhalation Method tests combined with Geo-Studio’s SEEP/W and SIGMA/W modules for fluid–solid coupled simulation calculations, the evolution process of landslide failure mechanisms and deformation characteristics is analyzed and discussed. Lastly, utilizing data mining analysis of multi-source data, a hybrid optimized machine learning predictive model is established for model prediction comparison. The study reveals that: (1) The rise in infiltration line elevates pore water pressure, affecting the stability of the sliding zone, leading to “unlock effects” and step-like displacement deformation; (2) Simulation shows that YY208 is closer to the actual situation, located at the far bank position, while YY210 is greatly influenced by the “buoyancy effect”, resulting in a slowdown in deformation velocity; (3) After data preprocessing, overall actual displacement prediction performs better than simulation displacement prediction in terms of Mean Absolute Error, Mean Squared Error and Correlation Coefficient, but noise reduction processing can improve the periodic prediction effect of simulation displacement.

Vessels encapsulating tumor clusters contribute to the intratumor heterogeneity of HCC on Gd-EOB-DTPA-enhanced MRI.

Vessels encapsulating tumor clusters (VETC) pattern is tumor vasculature of HCC and is a predictor of prognosis and therapeutic efficacy. Recent radiological studies have demonstrated the predictability of VETC from preoperative images, but the mechanisms of image formation are not elucidated. This study aims to determine the relationship between VETC and intratumor heterogeneity in Gd-EOB-DTPA-enhanced magnetic resonance imaging (EOB-MRI) and to provide its pathological evidence. Radiologists visually classified preoperative arterial- and hepatobiliary-phase EOB-MRI images of 204 surgically resected HCCs into patterns based on heterogeneity and signal intensity; these classifications were validated using texture analysis. Single and multiplex immunohistochemistry for CD34, h-caldesmon, and OATP1B3 were performed to evaluate VETC, arterial vessel density (AVD), and OATP1B3 expression. Recurrence-free survival was assessed using the generalized Wilcoxon test. The contribution of clinicoradiological factors to the prediction of VETC was evaluated by random forest and least absolute shrinkage and selection operator regression. VETC was frequently found in tumors with arterial-phase heterogeneous hyper-enhancement patterns and in tumors with hepatobiliary-phase heterogeneous hyperintense/isointense patterns (HBP-Hetero). AVD and OATP1B3 expression positively correlated with signal intensity in the arterial and hepatobiliary phases, respectively. Intratumor spatial analysis revealed that AVD and OATP1B3 expression were lower in VETC regions than in tumor regions without VETC. Patients with HBP-Hetero tumors had shorter recurrence-free survival. Machine learning models highlighted the importance of serum PIVKA-II, tumor size, and enhancement pattern of arterial and hepatobiliary phase for VETC prediction. VETC is associated with local reductions of both AVD and OATP1B3 expression, likely contributing to heterogeneous enhancement patterns in EOB-MRI. Evaluation of the arterial and hepatobiliary phases of EOB-MRI would enhance the predictability of VETC.

Time-resolved transient optical and electron paramagnetic resonance spectroscopic studies of electron donor-acceptor thermally activated delayed fluorescence emitters based on naphthalimide-phenothiazine dyads.

The photophysics of naphthalimide (NI)-phenothiazine (PTZ) dyads were investigated as electron donor-acceptor (D-A) thermally activated delayed fluorescence (TADF) emitters. Femtosecond transient absorption (fs-TA) spectra show that the photophysical processes in non-polar solvents are in singlet localized state (1LE, τ = 0.8 ps) → Franck-Condon singlet charge separation state (1CS, τ = 7.8 ps) → 1CS state (τ = 2.2 ns) → triplet state (3LE, τ = 16 μs). The 3LE state is formed via the spin-orbit charge transfer-intersystem crossing (SOCT-ISC) mechanism rather than the spin-orbit (SO)-ISC mechanism. In a polar solvent, the CS state has a much lower energy than the 3LE state; thus, the 3LE state is absent from the photophysical processes and no TADF was observed. Moreover, we found that the delayed fluorescence lifetime is related to the low-lying triplet state (3LE or 3CS states). When the 3CS state is the low-lying triplet state, the TADF lifetime is shorter than that of the 3LE state as the low-lying triplet state. In the time-resolved electron paramagnetic resonance (TREPR) spectra, both 3LE (zero field splitting parameter D = 2250 MHz, E = -150 MHz) and 3CS (D = 430 MHz, E = 0 MHz) states were observed. It is noteworthy that the electron spin polarization (ESP) phase pattern of the 3CS state was inverted at longer delay times as a consequence of the selective transition between the 3LE and 3CS states and a faster decay of one sublevel of the 3CS state. These results are strong and direct experimental evidence for the spin-vibronic coupling mechanism of TADF.

Contactless defects detection using modulated photoluminescence technique: model for a single Shockley-Read-Hall trap in a semiconductor thin layer

Studying defects in semiconductors is, in practice, a very important topic for opto-electronic applications. It involves advanced characterization tools able to quantify and qualify the defect densities present in the materials. In the present article we focus on the use of a contactless frequency domain technique: modulated photoluminescence (MPL), and show its potential to detect defects. MPL has been used for the measurement of differential lifetime for several decades in silicon wafers. By extending it to low lifetime/highly defective materials we discovered its potential to become a defect spectroscopy method, measuring time constants close to the ones governing impedance spectroscopy measurements. Proofs of concept and an analytical model for doped materials have been presented already. Here, we reformulate the analytical model more explicitly and check its applicability by extensive numerical simulations for the case of a low illumination for a thin layer with a single defect. We present a parametric numerical study simulating the response of a single Shockley-Read-Hall center, showing the appearance of so-called V-Shapes in the MPL phase patterns as predicted by the analytical model, and valid beyond small-signal approximation. We discuss the difference between these two approaches and extend the analytical model and numerical investigations to intrinsic materials.

Rapid stochastic spatial light modulator calibration and pixel crosstalk optimization

Holographic light potentials generated by phase-modulating liquid-crystal spatial light modulators (SLMs) are widely used in quantum technology applications. Accurate calibration of the wavefront and intensity profile of the laser beam at the SLM display is key to the high fidelity of holographic potentials. Here, we present a new calibration technique that is faster than previous methods while maintaining the same level of accuracy. By employing stochastic optimization and random speckle intensity patterns, we calibrate a digital twin that accurately models the experimental setup. This approach allows us to measure the wavefront at the SLM to within λ/170 in ~ 5 minutes using only 10 SLM phase patterns, a significant speedup over state-of-the-art techniques. Additionally, our digital twin models pixel crosstalk on the liquid-crystal SLM, enabling rapid calibration of model parameters and reducing the error in light potentials by a factor of ~ 5 without losing efficiency. Our fast calibration technique will simplify the implementation of high-fidelity light potentials in, for example, quantum-gas microscopes and neutral-atom tweezer arrays where high-NA objectives and thermal lensing can deform the wavefront significantly. Applications in the field of holographic displays that require high image fidelity will benefit from the novel pixel crosstalk calibration, especially for displays with a large field of view and increased SLM diffraction angles.

Numerical Modelling of Myocardial Infarction in Multivessel Coronary Lesion. II. Patterns of Formation of Large-Scale Damages and Structures

In this work, the basic mechanisms of myocardial infarction development during its inflammatory phase have been studied using mathematical modelling methods. Complex scenarios associated with multivessel lesions of the coronary bed and variability in baseline indicators of the innate immune system state have been considered. Special attention is paid to methodological issues related to the analysis of the effectiveness of the algorithm for approximate solutions of nonlinear initial-boundary value problems and setting up computational experiments under conditions close to the conditions of laboratory experiments in the field of interest. A numerical analysis was performed of several of the most common variants in laboratory practice of the formation of a large lesion in the left ventricle of the mouse heart, caused by the spatiotemporal heterogeneity of the properties of the environment, the immune reaction and ischemic myocardial damage, including recurrent infarction. The main attention is on the following aspects: – analysis of the mechanism of formation of large-scale infarct damages with an extensive core covering almost the entire infarct focus, or with a relatively small core, and assessment of the role of inflammation in these processes; – analysis of current scenarios of structure formation and the role of nonlinear dynamic structures of demarcation inflammation in the formation of a large but highly structured focus. The obtained data allow us to conclude that there is sufficient conservatism during infarction, evidenced by the basic patterns of the inflammatory phase revealed during modeling. The variability of heart attack scenarios manifests itself as a «memory»-effect about the initial data. We observe the «memory»-effect only at a biologically significant time interval, but we also note a general tendency to switch to the usual scenario of inflammation in large-focal infarction, which eliminates the peculiarities of the initial and individual conditions. The role of inflammation has been investigated in the context of a wave process in which spatial localization and the interaction of density and concentration waves can determine the main features of myocardial damage. In particular, within the framework of the adopted mathematical model, the conditions under which the formation of local zones with a relatively low or, conversely, high level of damage is possible have been described. In our work, we have established a significant interdependence between the formation of quasi-stationary structures and the intensity of the immune response. The high probability of developing severe or even terminal myocardial infarction may be due to the high level of immune system factors, in particular, monocytes-macrophages or cytokines in the reinfarction heart.

The Evolution and Performance Response of Industrial Land Use Development in China’s Development Zone: The Case of Suzhou Industrial Park

Development zones are crucial spatial carriers driving economic growth and industrial upgrading, playing a key role in China’s development. After years of expansion, these zones face significant challenges in industrial land development and performance enhancement. This paper takes Suzhou Industrial Park (SIP) as a case, which is a model of Sino–Singaporean government cooperation. Using Landsat 4–5 TM data, socioeconomic data, and industrial land use data, spatial analysis and statistical modeling were employed to examine the evolution and phased patterns of industrial land use in SIP from 1994 to 2022. A performance evaluation system encompassing economic benefits, innovation-driven growth, development intensity, green development, and social security was developed to assess land use performance and its responses to spatial transformations. The results reveal that industrial land in SIP experienced a significant change in the intensity of land expansion from 1.031 to 0.352 during 1994–2022, and the peak circle density expanded from 3 km to 15 km. The mean value of the comprehensive performance score during 2017–2022 was 42.18, with the highest economic efficiency (40.54) and a lower innovation capacity (16.98). The development of industrial land in SIP presents the stage characteristics of monocentric polarization, polycentricity, and spatial diffusion toward a generalized development zone, showing significant path dependence, and the difference in the land use performance of different industrial types is obvious. In the future, the optimization and redevelopment of the stock of land should be strengthened to promote the optimization of the spatial layout of technology-intensive industries and the technological upgrading of labor-intensive industries, as well as achieving sustainable economic growth through innovation-driven, green development and enclave economy collaboration. This study provides a reference for the industrial layout and high-quality sustainable development of development zones.

Liquid-crystal-based diffractive optical elements with high Pancharatnam-Berry phase accuracy for holographic displays fabricated using an optimized liquid crystal on silicon device

A rapid and accurate photoalignment technique was proposed for the fabrication of liquid crystal Pancharatnam-Berry phase diffractive optical elements (LC PB-DOEs). The in-plane orientation of LCs was precisely manipulated through the polarized illumination of an optimized liquid crystal on silicon (LCOS) device. LCOS and thereafter spatial light modulator (SLM) can generate polarization patterns at pixel level at will. The quality of such alignment was improved significantly by minimizing the phase flicker of the phase-only LCOS SLM. This was confirmed by the increase of the measured quality of the holographic images reconstructed using our DOE in terms of structural similarity (SSIM) and peak signal-to-noise ratio (PSNR) at 30% and 5%, respectively. Furthermore, a bi-focal LC PB-lens was fabricated and used as a high quality Fourier lens in holographic display to validate the usefulness of such LC PB-DOEs. This work illustrated a ubiquitous approach of fabricating different types of lightweight and thin form factor DOEs of random phase patterns at pixel level with low cost and high throughput.

Retraction Note: A multi-scale and rotation-invariant phase pattern (MRIPP) and a stack of restricted boltzmann machine (RBM) with preprocessing for facial expression classification

Retraction Note: A multi-scale and rotation-invariant phase pattern (MRIPP) and a stack of restricted boltzmann machine (RBM) with preprocessing for facial expression classification

Flatness constraints in the estimation of GNSS satellite antenna phase center offsets and variations

Accurate information on satellite antenna phase center offsets (PCOs) and phase variations (PVs) is indispensable for high-precision geodetic applications. In the absence of consistent pre-flight calibrations, satellite antenna PCOs and PVs of global navigation satellite systems are commonly estimated based on observations from a global network, constraining the scale to a given reference frame. As part of this estimation, flatness and zero-mean conditions need to be applied to unambiguously separate PCOs, PVs, and constant phase ambiguities. Within this study, we analytically investigate the impact of different boresight-angle-dependent weighting functions for PV minimization, and we compare antenna models generated with different observation-based weighting schemes with those based on uniform weighting. For the case of the GPS IIR/-M and III satellites, systematic differences of 10 mm in the PVs and 65 cm in the corresponding PCOs are identified. In addition, new antenna models for the different blocks of BeiDou-3 satellites in medium Earth orbit are derived using different processing schemes. As a drawback of traditional approaches estimating PCOs and PVs consecutively in distinct steps, it is shown that different, albeit self-consistent, PCO/PV pairs may result depending on whether PCOs or PVs are estimated first. This apparent discrepancy can be attributed to potentially inconsistent weighting functions in the individual processing steps. Use of a single-step process is therefore proposed, in which a dedicated constraint for PCO-PV separation is applied in the solution of the normal equations. Finally, the impact of neglecting phase patterns in precise point positioning applications is investigated. In addition to an overall increase of the position scatter, the occurrence of systematic height biases is illustrated. While observation-based weighting in the pattern estimation can help to avoid such biases, the possible benefit depends critically on the specific elevation-dependent weighting applied in the user’s positioning model. As such, the practical advantage of such antenna models would remain limited, and uniform weighting is recommended as a lean and transparent approach for the pattern estimation of satellite antenna models from observations.

EXACT SOLUTIONS OF NONLINEAR FRACTIONAL CAHN–ALLEN EQUATION ARIES IN DIFFERENT NONLINEAR PHYSICAL PHENOMENON USING UNIFIED TECHNIQUE

The nonlinear fractional Cahn–Allen (NFCA) equation provides insight into phase modifications and pattern elaboration in natural structures, clarifying how various states of matter have changed throughout time. By using a unified technique, this study aims to present novel, precise solutions to the NFCA problem. This method has led to the discovery of a broad spectrum of soliton solutions, ranging from dark compactons and dark solitons to periodic kink behaviors, rough wave behaviors, and periodic patterns featuring peaked crests and troughs. It has also unveiled anti-kink periodic behaviors, periodic wave behaviors, bright-dark single solitons, periodic patterns displaying anti-peaked crests and anti-troughs, bright solitons, and compound soliton phenomena. Notably, these accomplishments have been made possible through the utilization of Maple software. These findings are important for fractional nonlinear dynamical models (FNLDMs). In order to clarify many dynamic behaviors that solutions of the NFCA equation display in other scientific fields, such as quantum mechanics, mathematical biology, and plasma physics, contour plots and 3D surface representations of these exact solutions are also featured. Through our investigation using the unified technique, we have unveiled a plethora of novel discoveries. Employing this method has revealed a total of 54 fresh findings. In contrast, Javeed et al. [S. Javeed, S. Saif and D. Baleanu, New exact solutions of fractional Cahn–Allen equation and fractional DSW system, Adv. Differential Equations 2018 (2018) 459] applied the first integral technique, resulting in only eight outcomes. Upon comparing their results with ours, our approach has yielded an additional four out of six innovative results. As far as we are aware, the application of our technique to the NFCA equation has not been previously documented. We anticipate that future research will expand this methodology to include other FNLDMs.

(Invited) Energy Intelligent Computing Devices Based on 2D Materials

Despite the long and crucial role of traditional solid-state physics for current silicon-based technologies, next generation neuromorphic, non-volatile memory, and energy devices that are key components in the era of the internet of things (IOT) require novel working principles with quantum physics emerging in low-dimensional materials1-4. The main research direction for the future devices is to realize ‘ultralow device operation energy’, ‘ultrahigh device operation speed’, and ‘large-scale device integration (up to 1015)’, which calls for exploring diverse quantum phenomena in low dimensional device components5,6. In this talk, I will present some of our recent efforts1-7 to establish new device physics for energy intelligent devices, which could be a milestone for the promising future devices. In particular, dynamic convolution neural network, phase transition and other intriguing quantum physics in two-dimensional (2D) materials will be discussed along with logic device, neuromorphic computing, and energy device applications. Reference H. Yang et al. Graphene Barristor, a Triode Device with a Gate-Controlled Schottky Barrier, Science 336, 1140 (2012)S. Cho et al. Phase Patterning for Ohmic Homojunction Contact in MoTe2. Science 349, 625 (2015)D. H. Keum et al. Bandgap opening in few-layered monoclinic MoTe2. Nature Physics 11, 482 (2015)H. Yang et al. Structural and quantum-state phase transition in van der Waals layered materials. Nature Physics 13, 931 (2017)L. Sun et al. Self-selective van der Waals heterostructures for large-scale memory array. Nature Communications 10, 3161 (2019)S. Zheng et al. Resonant tunneling spectroscopy to probe the giant Stark effect in atomically-thin materials. Advanced Materials 32, 1906942 (2020)L. Sun et al. In-sensor Reservoir Computing for Language Learning via Two-dimensional Memristor. Science Advances 7, eabg1455 (2021)

Data and Model Synergy-Driven Rolling Bearings Remaining Useful Life Prediction Approach Based on Deep Neural Network and Wiener Process

Abstract Various remaining useful life (RUL) prediction methods, encompassing model-based, data-driven, and hybrid methods, have been developed and successfully applied to prognostics and health management for diverse rolling bearing. Hybrid methods that integrate the merits of model-based and data-driven methods have garnered significant attention. However, the effective integration of the two methods to address the randomness in rolling bearing full life cycle processes remains a significant challenge. To overcome the challenge, this paper proposes a data and model synergy-driven RUL prediction framework that includes two data and model synergy strategies. First, a convolutional stacked bidirectional long short-term memory network with temporal attention mechanism is established to construct Health Index (HI). The RUL prediction is achieved based on HI and polynomial model. Second, a three-phase degradation model based on the Wiener process is developed by considering the evolutionary pattern of different degradation phases. Then, two synergy strategies are designed. Strategy 1: HI is adopted as the observation value for online updating of physics degradation model parameters under Bayesian framework, and the RUL prediction results are obtained from the physics degradation model. Strategy 2: The RUL prediction results from the data-driven and physics-based model are weighted linearly combined to improve the overall prediction accuracy. The effectiveness of the proposed model is verified using two bearing full life cycle datasets. The results indicate that the proposed approach can accommodate both short-term and long-term RUL predictions, outperforming state-of-the-art single models.

Generating High‐Fidelity Structured Light Fields Through an Ultrathin Multimode Fiber Using Phase Retrieval

AbstractLight transmission through a multimode fiber (MMF) has gained major importance for imaging and manipulation. The majority of phase retrieval algorithms used for a MMF implicitly assume light propagation to be described by a unitary operation, yet the transmission matrix of a multimode fiber is inherently non‐unitary. It is demonstrated that this erroneous assumption can impede the performance of many commonly used MMF phase retrieval algorithms and demonstrate that the weighted Yang–Gu algorithm outperforms other phase retrieval algorithms in this scenario. Once accounted for, the non‐unitary property of the transmission matrix can be leveraged to generate intricate intensity and phase patterns at the output of the fiber, and shape specific output fields. This is experimentally demonstrated by generating Laguerre–Gaussian beams that carry orbital angular momentum, and by forming images in planes offset from the distal end of the fiber facet.

Effects of nano-modification on the microstrfuctural evolution and mechanical properties of AA7075/AA6061 aluminum alloy joints fabrica ted by laser-MIG hybrid welding technique

In this study, a rigorous comparative analysis is conducted to assess the implications of 7075 welding wire and 7075 welding wire fortified with 1.0 wt% of TiC nanoparticles on the microstructural characteristics, distribution patterns of secondary phases, grain refinement, and mechanical properties of AA7075/AA6061 dissimilar aluminum alloy joints produced via laser-MIG hybrid welding. The experimental results show that: The introduction of TiC nanoparticles prompts a transformation in the weld microstructure, transitioning from coarse dendritic morphologies to finer equiaxed dendritic structures. The grain size and the strengthening phases have both undergone a process of refinement. Notably, a marked increase in high-angle grain boundaries (HAGBs) and a concomitant decrease in low-angle grain boundaries (LAGBs) are observed in the nano-modified weld. Nano-modification yields substantial improvements in the mechanical properties of the welded joint. Specifically, the softening width of the AA6061 heat-affected zone (HAZ) is reduced by approximately half (from 8 mm to 4 mm), while the minimum microhardness of the joint has been increased from 34.1 Hv to 62.4 Hv. Moreover, the average ultimate tensile strength (UTS) of the joint has been enhanced from 95.7 MPa to 208.9 MPa, while the average yield strength (YS) has been increased from 57.1 MPa to 155.1 MPa.

Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research.

Muscle synergy analysis based on machine learning has significantly advanced our understanding of the mechanisms underlying the central nervous system motor control of gait and has identified abnormal gait synergies in stroke patients through various analytical approaches. However, discrepancies in experimental conditions and computational methods have limited the clinical application of these findings. This review seeks to integrate the results of existing studies on the features of muscle synergies in stroke-related gait abnormalities and provide clinical and research insights into gait rehabilitation. A systematic search of Web of Science, PubMed, and Scopus was conducted, yielding 10 full-text articles for inclusion. By comprehensively reviewing the consistencies and differences in the study outcomes, we emphasize the need to segment the gait cycle into specific phases (e.g., weight acceptance, push-off, foot clearance, and leg deceleration) during the treatment process of gait rehabilitation and to develop rehabilitation protocols aimed at restoring normal synergy patterns in each gait phase and fractionating reduced synergies. Future research should focus on validating these protocols to improve clinical outcomes and introducing indicators to assess abnormalities in the temporal features of muscle synergies.

Design and experimental evaluation of a non-contact ultrasonic motor using acoustic phase holography

Abstract Non-contact ultrasonic motors address certain limitations of conventional ultrasonic motors. However, they continue to have intricate designs and electronics. Acoustic holography has emerged as a technique for its flexibility and dynamicity in manipulating acoustic phase and amplitude patterns in the nearfield, offering a reduction in mentioned complexities. Therefore, this technique may find utility in the development of non-contact ultrasonic motors. This paper discusses a novel design for non-contact rotary ultrasonic motor using acoustic holography. Acoustic holographic technique modulates the acoustic phase to create a phase gradient, resulting in a rotary flow that drives the rotor in the interface of aqueous media and air. The motor’s performance is influenced by factors such as the acoustic pressure amplitude, the number of 0 to 2 π pitches, and the rotor’s geometry. An empirical study using the Response Surface Method (RSM) identified an optimal number of pitches for maximum rotational speed at a constant voltage. The motor torque was measured by calculating the drag forces applied to the rotor blades. It was found that the minimum output torque occurs when the stator phase pitches match the rotor blades. The ideal motor performance is achieved with eight rotor blades and six phase pitches. The motor’s top speed reached 40 rpm, and the output torque varied around 0.1 μN.m, depending on the phase pitches and rotor blades. In summary, the research highlights the potential of acoustic holography in designing a non-contact ultrasonic motor, with specific configurations yielding optimal speed and torque.