bluuebunny/crossref_metadata_2025 huggingface dataset:
Factors influencing charge transport at perovskite–charge transport layer interfaces: current strategies, challenges, and perspectives based on first-principles studies
Authors: Bhattacharya Labanya , Caspary Toroker Maytal
Published: May 2024

Charge transport at the interface between a perovskite absorbing layer and the charge transport layer (CTL) has a major role in determining perovskite solar cell device efficiency and long-term stability. Hence, a detailed operando characterization of the factors influencing charge transport at perovskite/CTL interfaces needs to be discussed. This perspective summarizes recent studies involving charge transport through perovskite and CTL interfaces. An overview is provided of the recent advances in the fundamental understanding of how these interfaces influence device performance. Based on recently reported articles, some of the crucial factors such as energy-level alignment, defects, and non-radiative recombination are identified. The identification is made from an atomistic point of view as these factors have a strong influence on charge transport at perovskite/CTL interfaces. Furthermore, we share our perspective on calculating said factors influencing interfacial charge transport from different approaches using density functional theory (DFT) and beyond.
Understanding the phase stability in a multi-principal-component AlCuFeMn alloy
Authors: Swarnakar Palash , Ghosh M , Mahato B , De Partha Sarathi , Roy Amritendu
Published: May 2024

Method(s) that can reliably predict phase evolution across thermodynamic parameter space, especially in complex systems, are of critical significance in academia as well as in the manufacturing industry. In the present work, the phase stability in an equimolar AlCuFeMn multi-principal-component alloy (MPCA) was predicted using complementary first-principles density functional theory calculations and ab initio molecular dynamics (AIMD) simulations. The temperature evolution of completely disordered, partially ordered, and completely ordered phases was examined based on the Gibbs free energy. Configurational, electronic, vibrational, and lattice mismatch entropies were considered to compute the Gibbs free energy of the competing phases. Additionally, elemental segregation was studied using AIMD. The predicted results at 300 K align well with room-temperature experimental observations using x-ray diffraction and scanning and transmission electron microscopy on a sample prepared using commercially available pure elements. The adopted method could help in predicting plausible phases in other MPCA systems with complex phase stability.
Enhanced performance of normally-OFF GaN HEMTs with stair-shaped p-GaN cap layer
Authors: Ye Yankai , Zhang Haochen , Xing Zhanyong , Yang Lei , Wang Hu , Zhang Mingshuo , Zuo Chengjie , Sun Haiding
Published: May 2024

The p-GaN-gated E-mode HEMTs (P-HEMTs) are being extensively studied for emerging power electronics. However, the devices still suffer from performance trade-off among threshold voltage (V
TH), output drain current (I
DS), and breakdown voltage (V
BD). Herein, we propose a P-HEMT with a stair-like p-GaN cap layer to boost their performance. The p-GaN cap layer is composed of four discrete p-GaN staircases with the decreased thickness to the right (Right-Stair P-HEMT) or to the left (Left-Stair P-HEMT). It is found that the RSP-HEMT simultaneously achieves the 1.3 times increased I
DS, 160 V enhanced V
BD, and improved V
TH stability against drain-induced barrier lowering effects, compared with the LSP-HEMT and the conventional BaSeline P-HEMT. These device merits should be attributed to the effective manipulation of the lateral electric field (E
F) under all bias conditions by the unique band structures enabled by the RSP configuration. Such E
F manipulation strategies offer us helpful guidance and insights to further propel the development of high-performance E-mode P-HEMTs.
An experimental study on low-temperature plasma tissue ablation and its thermal effect
Authors: Chen Liuxiao , Xie Lu , Wu Tong , Xu Qun , Liu Yangzhi , Xin Lin , Mao Lin , Song Chengli
Published: May 2024

Low-temperature plasma ablation has been recently used for minimally invasive surgeries. However, more research is still needed on its generation process during tissue ablation and the underlying mechanism of tissue thermal damage. In this paper, high-speed camera footage, voltage–current signal collection, temperature analysis, and histological analysis were used to investigate the dynamic process of plasma tissue ablation and its thermal effect of dual-needle electrodes immersed in normal saline, which were driven by a high-frequency DC power supply with an output voltage ranging from 220 V to 320 V and a squire wave of 100 kHz. Microbubbles occurred around the ground electrode and merged to form a vapor layer that could completely cover the ground electrode. Plasma capable of ablating tissue would occur in the vapor layer between the ground electrode and tissue. The effect of electrical parameters on plasma generation and its thermal effect are analyzed by statistical results. The experimental results indicated that the voltage applied to the electrodes significantly influenced both the generation and stability of plasma, as well as the heat generation and tissue damage around the electrodes. Furthermore, under the same voltage, the existence of biological tissue promotes the formation of a vapor layer around the electrode, thereby facilitating the generation and stability of plasma. Notably, the temperature rise around the ground electrode is much higher than that around the powered electrode. These results have direct application to the design of plasma tissue ablation systems, which could achieve tissue ablation effects with minimal thermal damage.
Characteristics of electric breakdown in repeated frequency pulse with microcavity effect
Authors: Zhang Tianliang , Wang Wenjing , He Feng
Published: May 2024

The electric breakdown characteristics in microcavity structure under repeated frequency pulse (RFP) were studied, and the physical mechanism was investigated quantitatively based on the full statistical distribution of breakdown time delay obtained in step rectangular pulse (SRP). Experimentally, microcavity heights of 300, 800, and 2000 μm were used. In RFP, the occurrence of breakdown becomes probabilistic when the time delay t
d and pulse width t
PW satisfy the condition t
s-min < t
PW < t
s-max. The breakdown probability increases with pulse width, and the probability distributions are roughly exponential and Gaussian at pulse frequencies of 3 and 1000 Hz, respectively. We found the results are attributed to the similar distributions of time delay in RFP and SRP with similar afterglow time and pulse voltage, and the equal distributions of breakdown probability (with pulse width) and cumulative probability of t
d in RFP. The microcavity effect will decrease the breakdown probability under given pulse width and voltage. Additionally, it is found that in RFP the increase of pulse width from 1 to 1000
μ
s will decrease the threshold voltages at 0% and 100% breakdown probabilities, and the threshold voltage difference will decrease simultaneously to around 0, which results in the transition of breakdown feature from probability to certainty. This phenomenon is due to that the reduction of pulse voltage will increase the time delay significantly and meanwhile the variation rate of time delay with pulse voltage Δt
d/ΔU
w decreases sharply. The microcavity effect will cause the increase of threshold breakdown voltages at a given pulse width and frequency. Finally, it is found that in RFP the breakdown voltage will decrease with the rise of pulse frequency from 10° to 104 Hz, which is consistent with the variation of time delay with afterglow time (from 10−1 to 103 ms) in the memory curve measured in SRP under similar afterglow time. Overall, the microcavity effect will enhance the adsorption of charged and excited species by dielectric walls during afterglow period and enlarge the time delay in the following pulse breakdown, and then influence the RFP breakdown characteristics.
Scaling and universality at ramped quench dynamical quantum phase transitions
Authors: Zamani Sara , Naji J , Jafari R , Langari A
Published: May 2024

The nonequilibrium dynamics of a periodically driven extended XY model, in the presence of linear time dependent magnetic field, is investigated using the notion of dynamical quantum phase transitions (DQPTs). Along the similar lines to the equilibrium phase transition, the main purpose of this work is to search fundamental concepts such as scaling and universality at the ramped quench DQPTs. We have shown that the critical points of the model, where the gap closing occurs, can be moved by tuning the driven frequency and consequently the presence of or absence of DQPTs can be flexibly controlled by adjusting the driven frequency. We have uncovered that, for a ramp across the single quantum critical point, the critical mode at which DQPTs occur is classified into three regions: the Kibble–Zurek (KZ) region, where the critical mode scales linearly with the square root of the sweep velocity, the pre-saturated (PS) region, and the saturated (S) region where the critical mode makes a plateau versus the sweep velocity. While for a ramp that crosses two critical points, the critical modes disclose just the KZ and PS regions. On the basis of numerical simulations, we find that the dynamical free energy scales linearly with time, as approaches to DQPT time, with the exponent

ν
=
1
±
0.01

for all sweep velocities and driven frequencies.
Theoretical study of the nonlinear magnon–phonon coupling in CoF2
Authors: Liu Shuang , Wang Qian , Long Meng-Qiu , Wang Yun-Peng
Published: May 2024

The coupling and interplay between magnon and phonon are important topics for spintronics and magnonics. In this work we studied the nonlinear magnon–phonon coupling in CoF2. First-principles calculations demonstrate that the antiferromagnetic resonance magnon drives a phonon with B1g character; the oscillating driving force has a frequency twice of that of the magnon. Comparing with similar materials indicates a strong correlation between the strength of nonlinear magnon–phonon coupling and the orbital magnetic moment of the magnetic ion. This work pave the way for theoretical study of nonlinear magnon–phonon coupling.
Spatio-temporal features based deep learning model for depression detection using two electrodes
Authors: Choudhary Shubham , Kumar Bajpai Manish , Kumari Bharti Kusum
Published: May 2024

Deep learning has made significant contributions to the medical field and has shown great potential in various applications. Its ability to process vast amounts of data and extraction of patterns has enabled breakthroughs in medical research, diagnosis and treatment. The application of deep learning plays a vital role in depression detection. Depression is a neurological disorder characterized by persistent feelings of sadness, hopelessness and a lack of interest. The prevalence of depression is a significant factor contributing to the rise in suicide cases on a global scale. The electroencephalogram (EEG) is a non-invasive technique used to detect depression. It records brain activity using multiple electrodes. The number of EEG electrodes used for measurement directly affects the instrumentation and measurement complexity of the experiment. The present manuscript proposes a deep learning model for depression detection, focusing on two electrodes named FP1 and FP2. The purpose of employing two electrodes is to enhance the system’s portability while reducing data acquisition time and system cost. EEG is spatio-temporal data and possesses inherent spatial and temporal features. The present manuscript proposes a methodology for extracting temporal and spatial features. The temporal feature extraction module extracts temporal features in the time domain and the spatial module extracts spatial features in the spatial domain. This manuscript presents a study on the applicability of two electrodes for depression detection. This research can enhance accessibility, user-friendliness and easier data collection and analysis. The proposed deep learning model is evaluated on two benchmark datasets. It achieves 93.41% classification accuracy, 92.54% precision, 93.23% recall, 93.06% F1 score and 97.80% area under the curve (AUC) for Hospital University Sains Malaysia dataset and for Multi-modal Open Dataset for Mental-disorder Analysis dataset it achieves 79.40% accuracy, 81.18% precision, 67.73% recall, 73.80% F1 score and 85.66% AUC.
Fractional differentiation-based variational level set model for noisy image segmentation without contour initialization
Authors: Zhong Zhengyang , Wang Bo , Hao Can , Wang Ying
Published: May 2024

Noisy image segmentation is a hot topic in image analysis. In this paper, we present a novel methodology for tackling this issue through the integration of fractional differentiation in the frequency domain with a variational level set model (VLSM), which eliminates user-selected initial contours by incorporating the convex energy function. Additionally, the fractional differentiation reduces noises while preserving more detail information. Experiments on synthetic and real noisy images demonstrate that our proposed model surpasses other denoising VLSMs in terms of noise reduction, segmentation accuracy, and efficiency.
DMOT-SLAM: visual SLAM in dynamic environments with moving object tracking
Authors: Wang Kesai , Yao Xifan , Ma Nanfeng , Ran Guangjun , Liu Min
Published: May 2024

Visual simultaneous localization and mapping (SLAM) in dynamic environments has received significant attention in recent years, and accurate segmentation of real dynamic objects is the key to enhancing the accuracy of pose estimation in such environments. In this study, we propose a visual SLAM approach based on ORB-SLAM3, namely dynamic multiple object tracking SLAM (DMOT-SLAM), which can accurately estimate the camera’s pose in dynamic environments while tracking the trajectories of moving objects. We introduce a spatial point correlation constraint and combine it with instance segmentation and epipolar constraint to identify dynamic objects. We integrate the proposed motion check method into DeepSort, an object tracking algorithm, to facilitate inter-frame tracking of dynamic objects. This integration not only enhances the stability of dynamic features detection but also enables the estimation of global motion trajectories for dynamic objects and the construction of object-level semi-dense semantic maps. We evaluate our approach on the public TUM, Bonn, and KITTI dataset, and the results show that our approach has a significant improvement over ORB-SLAM3 in dynamic scenes and performs better compared to other state-of-the-art SLAM approaches. Moreover, experiments in real-world scenarios further substantiate the effectiveness of our approach.
Mirror-assisted 360° panoramic 3D measurement system based on rotary laser profilometer
Authors: Yao Chuan-Wei , Han Yu-Chen , Zhou Peng , Wang Heng-Yu , Wang Yao , Lin Bin
Published: May 2024

The full surface digitization of real samples plays a crucial role in fields such as object recognition, industrial quality control, and reverse modeling. To achieve panoramic three-dimensional (3D) reconstruction of samples in complex scenes, we propose an advanced panoramic laser scanning system, consisting of a laser rotation scanning system and a pair of plane mirrors. With the assistance of mirrors, the projected line laser beam can illuminate the sample from full angles in a single scanning sequence, and the camera can capture the 3D information of the sample from several specific viewpoints. The scanning method of rotating allows us to achieve more efficient and larger-scale 3D scanning. After obtaining the sample’s 3D information from different viewpoints using the same calibration parameters, the sample’s full-surface 3D data in the global coordinate can be obtained using mirror reflections. We conducted precision and effectiveness tests on samples with different sizes, materials, shapes, and textures to demonstrate the ability of the proposed method to perform full-surface 3D reconstruction under different scenarios. The experimental results of accuracy evaluation demonstrate that the proposed system can achieve a measurement accuracy at the level of 100 μm. Additionally, the robust experimental results in different scenarios also indicate that the proposed panoramic laser scanning system is capable of accurately obtaining full-surface 3D data of various types of samples, providing a cost-effective, easy-to-use, efficient, high-resolution, and effective approach for achieving panoramic 3D reconstruction.
Nominal state determination and its effect on remaining useful life prediction
Authors: Mochammad Solichin , Kim Nam Ho , Noh Yoojeong
Published: May 2024

In machinery operation, a prolonged healthy or nominal state often lacks prognostic significance, causing challenges like data overload, biased predictions, and complex models. Moreover, many prediction methods utilize the complete history of monitoring data from the machine’s startup to its failure; however, prognostics mostly relies on data from the degradation stage. To address this, this study proposes a method to identify and exclude the prolonged period of the nominal state, thereby enhancing the prediction performance of remaining useful life (RUL). A health index (HI) is formulated by integrating acceleration signals from multiple time windows, with deviations computed as the disparity between the HI and its root mean squares. The identification of start and end times for the nominal state, determined by the intersection of consecutive deviation curves, leads to its exclusion from degradation behaviour modelling. The utilization of polynomial degradation trends from HI data after the nominal state’s end time, incorporating a positive slope constraint, aids in mitigating extrapolation uncertainty. The method’s efficiency is demonstrated in three defect cases, highlighting improved RUL predictions without the nominal state’s inclusion.
Underwater image enhancement via color correction and multi-feature image fusion
Authors: Ke Ke , Zhang Biyun , Zhang Chunmin , Yao Baoli , Guo Shiping , Tang Feng
Published: May 2024

The light attenuation underwater causes the actual underwater images to suffer from color cast, low contrast, and weak illumination. To address these issues, an effective fusion-based method is proposed, which realizes color correction (CC), brightness adjustment, contrast, and detail enhancement of underwater images. Concretely, we first design an adaptive CC method via dominant color channel judgment and lower color channel compensation. Then, we detect the brightness of each input image and propose a gamma correction function based on the gradient of the cumulative histogram to adjust the brightness of the low-light images. Subsequently, global histogram stretching and adaptive fractional differentiation techniques are employed to process the brightness-adjusted image, and then the global contrast-enhanced version and detail-enhanced version are generated respectively. To integrate the advantages of both versions, a channel fusion method based on the Lab color space is used to fuse the luminance and color of the two versions separately. The experimental results demonstrate the effectiveness of the proposed method in improving the color and illumination of underwater images, as well as enhancing the clarity of images. Moreover, the testing results on multiple datasets validate the excellent stability of this method.
FDS-MOMEDA: optimization-blind deconvolution in finite high-dimensional spaces for extracting pulse signal in rolling bearing fault diagnosis
Authors: Zhang Meng
Published: May 2024

Rolling bearing fault diagnosis is crucial for ensuring the safe and reliable operation of mechanical equipment. Detecting faults directly from measurement signals is challenging due to severe noise and interference. Blind deconvolution (BD), as a preferred method, effectively recovers periodic pulses from the measured vibration signals of faulty bearings. This study introduces a simulated annealing-based BD approach to enhance the pulse signal components reflecting faults in vibration signals measured on rolling bearings. This method iteratively searches for the optimal coordinates in a high-dimensional orthogonal optimization space, where the optimal coordinates reflect the combination of the inverse filter coefficients. Compared to the generalized spherical optimization space used in the ‘Optimization-Blind Deconvolution’ method in previous works, the proposed finite high-dimensional optimization space helps overcome the problem of inverse filter coefficient convergence, allowing for the design of inverse filters without limit of its shape. To better accommodate the cyclostationarity characteristics of bearing signal measured in reality, the proposed method employs a target vector that allows for uncertainty in pulse occurrence instants, thus overcomes challenges introduced by pseudo-periodic phenomena resulting from bearing slippage. Numerical simulations and experimental results on real bearing vibration signals confirm that the proposed method can design more flexible filters to enhance pulse-like patterns in signals, effectively utilize limited filter resources. Its capacity to tolerate inaccurate fault period estimates, high background noise, and pulse randomness enables it to effectively address vibration measurement signals in real-world scenarios.
Generalized nonlinear hybrid-norm parallel sparse filtering for bearing fault diagnosis under complex interference
Authors: Wang Jinrui , Jia Min , Zhang Zongzhen , Jiang Xingxing , Han Baokun , Bao Huaiqian
Published: May 2024

Considerable attention has been garnered by the bearing fault diagnostic method, founded on sparse feature learning, for its exceptional robustness and adaptability to noise. Being an effective sparse learning method, parallel sparse filtering (PSF) has found successful applications in intelligent fault diagnosis. However, influenced by mechanical structural collisions and complex transmission paths, the obtained bearing signals come with abnormal impacts and noise, resulting in a reduced reliability of the PSF. Additionally, PSF constrains features and samples with

l

1

/

2

norm, which is significantly disturbed by noise. To address these issues, generalized nonlinear hybrid-norm PSF (GNHNPSF) is proposed. Firstly, the Sigmoid nonlinear function is examined to suppress the amplitude of the anomalous shock. Subsequently, the hybrid-norm constraints, which involve the application of a

l

1

/

2

norm to the column features of the input signal and a

l

1

/

3

norm to the row features, can be employed to effectively extract distinctive information from the original data. The GNHNPSF is demonstrated to improve the accuracy of bearing fault diagnosis under complex interference, as evidenced by the results of simulation and experiments.
LiDAR-based SLAM pose estimation via GNSS graph optimization algorithm
Authors: He Wei , Li Rui , Liu Tianyue , Yu Yaoyao
Published: May 2024

LiDAR simultaneous localization and mapping (SLAM) is widely used in positioning and navigation. By illuminating a series of light spots on the surface of an object, orientation and pose information is obtained. However, improving the accuracy of the pose optimization algorithm without affecting the position information is difficult. Therefore, this study combines the graph optimization algorithm and the Global Navigation Satellite System (GNSS) to optimize the coordinates of the target object in the LiDAR SLAM pose. A GNSS pose estimation algorithm is proposed to show the relationship between positioning algorithms with and without GNSS pose optimization by analyzing the deviation of the distance, level, and height laser point cloud coordinates. The results show that with GNSS pose optimization, the deviations in distance, level, and height are 99% smaller than those without GNSS pose optimization. Furthermore, we demonstrate the effectiveness of the proposed graph optimization algorithm and GNSS optimization of LiDAR SLAM. Finally, this study highlights the directions for the application of wireless communication technology in the field of LiDAR SLAM.
Space-time image velocimetry in blurred scenes based on BSTI-DCGAN data augmentation
Authors: Hu Qiming , Jiang Dongjin , Zhang Guo , Zhang Ya , Wang Jianping
Published: May 2024

Due to the limited sample quantity and the complex data collection process of the blurred space-time image (BSTI) dataset, the deep learning-based space-time image velocimetry (STIV) results in larger errors when applied to blurry videos. To enhance the measurement accuracy, we propose the use of STIV in blurred scenes based on BSTI-deep convolutional generative adversarial network (DCGAN) data augmentation. Firstly, BSTI-DCGAN is developed based on the DCGAN. This network utilizes a bilinear interpolation-convolution module for upsampling and integrates coordinated attention and multi-concatenation attention to enhance the resemblance between generated and real images. Next, further expanding the dataset by using artificially synthesized space-time images subsequently, all space-time images are transformed into spectrograms to create a training dataset for the classification network. Finally, the primary spectral direction is detected using the classification network. The experimental results indicate that our approach effectively augments the dataset and improves the accuracy of practical measurements. Under the condition of video blur, the relative errors of the average flow velocity and discharge are 3.92% and 2.72%, respectively.
Wasserstein local slow feature analysis and its application to process monitoring
Authors: Fu Yuanjian , Wu Zhichao , Luo Chaomin , Xu Xue
Published: May 2024

Complex industrial processes are commonly characterized by dynamics, which results from compensation of the closed-loop control and complex reflux during process operations. In this work, we propose a novel method termed the Wasserstein local slow feature analysis approach (WLSFA), used to monitor the dynamic process, which can learn slowly varying information to capture the trend of process variations and characterize dynamics. Specifically, Wasserstein graph embedding based on optimal transport is proposed to preserve the local geometrical structure of raw data so that the reduced-dimensionality representations can more faithfully reveal the underlying information of data, enhancing monitoring performance. Moreover, the

l
2

-norm orthogonal constraint is incorporated into the objective function to improve the generalization ability and alleviate the false alarm rate. Based on the WLSFA model, a contribution plot denoting reconstruction is developed to locate the fault variables, which is beneficial for regulating abnormal conditions toward normal levels. Finally, the efficiency of the proposed approach is illustrated by a benchmark process and application to a real-world fractionation process.
Numerical investigation on the convergence of self-consistent Schrödinger-Poisson equations in semiconductor device transport simulation
Authors: Zhu Junyan , Cao Jiang , Song Chen , Li Bo , Han Zhengsheng
Published: May 2024

Semiconductor devices at the nanoscale with low-dimensional materials as channels exhibit quantum transport characteristics, thereby their electrical simulation relies on the self-consistent solution of the Schrödinger-Poisson equations. While the non-equilibrium Green’s function (NEGF) method is widely used for solving this quantum many-body problem, its high computational cost and convergence challenges with the Poisson equation significantly limit its applicability. In this study, we investigate the stability of the NEGF method coupled with various forms of the Poisson equation, encompassing linear, analytical nonlinear, and numerical nonlinear forms Our focus lies on simulating carbon nanotube field-effect transistors (CNTFETs) under two distinct doping scenarios: electrostatic doping and ion implantation doping. The numerical experiments reveal that nonlinear formulas outperform linear counterpart. The numerical one demonstrates superior stability, particularly evident under high bias and ion implantation doping conditions. Additionally, we investigate different approaches for presolving potential, leveraging solutions from the Laplace equation and a piecewise guessing method tailored to each doping mode. These methods effectively reduce the number of iterations required for convergence.
Nano-enabled smart and functional materials toward human well-being and sustainable developments
Authors: Rajeev Ashna , Yin Lu , Kalambate Pramod K , Khabbaz Mahsa Barjini , Trinh Binh , Kamkar Milad , Mekonnen Tizazu H , Tang Shirley , Zhao Boxin
Published: May 2024

Fabrication and operation on increasingly smaller dimensions have been highly integrated with the development of smart and functional materials, which are key to many technological innovations to meet economic and societal needs. Along with researchers worldwide, the Waterloo Institute for Nanotechnology (WIN) has long realized the synergetic interplays between nanotechnology and functional materials and designated ‘Smart & Functional Materials’ as one of its four major research themes. Thus far, WIN researchers have utilized the properties of smart polymers, nanoparticles, and nanocomposites to develop active materials, membranes, films, adhesives, coatings, and devices with novel and improved properties and capabilities. In this review article, we aim to highlight some of the recent developments on the subject, including our own research and key research literature, in the context of the UN Sustainability development goals.
Terahertz communication: detection and signal processing
Authors: Lu Guanxuan , Wang Jiaqi , Zhou Rui , Xie Zhemiao , Yuan Yifei , Huang Lin , Yeow John T W
Published: May 2024

The development of 6 G networks has promoted related research based on terahertz communication. As submillimeter radiation, signal transportation via terahertz waves has several superior properties, including non-ionizing and easy penetration of non-metallic materials. This paper provides an overview of different terahertz detectors based on various mechanisms. Additionally, the detailed fabrication process, structural design, and the improvement strategies are summarized. Following that, it is essential and necessary to prevent the practical signal from noise, and methods such as wavelet transform, UM-MIMO and decoding have been introduced. This paper highlights the detection process of the terahertz wave system and signal processing after the collection of signal data.
Quantitative derivation of a two-phase porous media system from the one-velocity Baer–Nunziato and Kapila systems
Authors: Crin-Barat Timothée , Shou Ling-Yun , Tan Jin
Published: May 2024

We derive a novel two-phase flow system in porous media as a relaxation limit of compressible multi-fluid systems. Considering a one-velocity Baer–Nunziato system with friction forces, we first justify its pressure-relaxation limit toward a Kapila model in a uniform manner with respect to the time-relaxation parameter associated with the friction forces. Then, we show that the diffusely rescaled solutions of the damped Kapila system converge to the solutions of the new two-phase porous media system as the time-relaxation parameter tends to zero. In addition, we also prove the convergence of the Baer–Nunziato system to the same two-phase porous media system as both relaxation parameters tend to zero. For each relaxation limit, we exhibit sharp rates of convergence in a critical regularity setting. Our proof is based on an elaborate low-frequency and high-frequency analysis via the Littlewood–Paley decomposition and includes three main ingredients: a refined spectral analysis of the linearized problem to determine the frequency threshold explicitly in terms of the time-relaxation parameter, the introduction of an effective flux in the low-frequency region to overcome the loss of parameters due to the overdamping phenomenon, and renormalized energy estimates in the high-frequency region to cancel higher-order nonlinear terms. To justify the convergence rates, we discover several auxiliary unknowns allowing us to recover crucial

O

(
ε
)

bounds.
Spectral structure of Moran Sierpinski-type measure on

R

2
Authors: Cao Jian , Lu Jian-Feng , Zhang Min-Min
Published: May 2024

Let

M
n

=

diag

[
3

p
n

,
3

q
n

]

with

p
n

,

q
n

⩾
1

for all

n
⩾
1

and let

D
=

{
(
0
,
0

)
t

,
(
1
,
0

)
t

,
(
0
,
1

)
t

}

. One can generate a Borel probability measure

μ

{

M
n

}

,
D

=

δ

M
1

−
1

D

∗

δ

(

M
2

M
1

)

−
1

D

∗

δ

(

M
3

M
2

M
1

)

−
1

D

∗
⋯
.

Such measure

μ

{

M
n

}
,
D

is called a Moran Sierpinski-type measure. It is known Deng et al (Acta Math. Sin. submitted) that the associated Hilbert space

L
2

(

μ

{

M
n

}
,
D

)

has an exponential orthonormal basis. In this paper, we first characterize all the maximal exponential orthogonal sets for

L
2

(

μ

{

M
n

}
,
D

)

. For such a maximal orthogonal set, we then give some sufficient conditions to determine whether it is an orthonormal basis of

L
2

(

μ

{

M
n

}
,
D

)

or not.
The diffusive limit of Boltzmann equation in torus
Authors: Liu Zhengrong , Yu Hongjun
Published: May 2024

The Boltzmann equation of kinetic theory gives a statistical description of a gas of interacting particles. It is well known that the Boltzmann equation is related to the Euler and Navier–Stokes equations in the field of gas dynamics. In this paper we are concerned with the incompressible Navier–Stokes–Fourier limit of the Boltzmann equation. We prove the incompressible Navier–Stokes–Fourier limit globally in time and the time decay rate of the solution to the rescaled Boltzmann equation in a torus. For ɛ small, by using the truncated expansion and

L

x
,
v

2

–

L

x
,
v

∞

method, we prove such a limit for the general potentials

γ
∈
(
−
3
,
1
]

.
A landmark-supervised registration framework for multi-phase CT images with cross-distillation
Authors: Rao Fan , Lyu Tianling , Feng Zhan , Wu Yuanfeng , Ni Yangfan , Zhu Wentao
Published: May 2024

Objective. Multi-phase computed tomography (CT) has become a leading modality for identifying hepatic tumors. Nevertheless, the presence of misalignment in the images of different phases poses a challenge in accurately identifying and analyzing the patient’s anatomy. Conventional registration methods typically concentrate on either intensity-based features or landmark-based features in isolation, so imposing limitations on the accuracy of the registration process. Method. We establish a nonrigid cycle-registration network that leverages semi-supervised learning techniques, wherein a point distance term based on Euclidean distance between registered landmark points is introduced into the loss function. Additionally, a cross-distillation strategy is proposed in network training to further improve registration performance which incorporates response-based knowledge concerning the distances between feature points. Results. We conducted experiments using multi-centered liver CT datasets to evaluate the performance of the proposed method. The results demonstrate that our method outperforms baseline methods in terms of target registration error. Additionally, Dice scores of the warped tumor masks were calculated. Our method consistently achieved the highest scores among all the comparing methods. Specifically, it achieved scores of 82.9% and 82.5% in the hepatocellular carcinoma and the intrahepatic cholangiocarcinoma dataset, respectively. Significance. The superior registration performance indicates its potential to serve as an important tool in hepatic tumor identification and analysis.
Numerical characterization of capacitively coupled CF4 plasmas modulated by anion beam injection
Authors: Zhou Youyou , Xu Jingwen , Wang Yu , Wu Hao , Wang Hongyu , Jiang Wei , Zhang Ya
Published: May 2024

In the study of electronegative CF4 capacitively coupled plasmas (CCP), plasma modulation is typically achieved by varying parameters such as pressure and voltage. In this work, the particle-in-cell/Monte Carlo (PIC/MC) method is used to simulate modulation of CF4 CCP with injection of anions (F−) ion beam (FB). The results demonstrate that FB injection effectively enhances the dissociation collision process between F− ions and neutral molecules, thus altering the densities of electrons and ions. An effective modulation of the characteristic parameters of the plasma of CF4 can be achieved by controlling the current and energy of FB. Particularly noteworthy is the transition of the heating mode from the DA mode to the dissociation mode as the FB current increases to 0.038 A (energy fixed at 10 keV) or when the FB energy exceeds 10 keV (current fixed on 0.038 A). This transition is attributed to the generation of a substantial number of electrons through dissociative collisions. This approach provides insight into the controlled modulation of plasma characteristics in CF4 CCP, offering potential applications in various plasma-based technologies.
Characteristics of laser induced plasma near a flat gas-liquid interface and its effect on the performance of laser induced breakdown spectroscopy (LIBS) detection
Authors: Xue Yuanyuan , Tian Ye , Li Jiamin , Sui Mingda , Pan Kezeng , Zhong Shilei
Published: May 2024

Moving the laser focus to the vicinity of the gas-liquid interface is the key point for many new enhanced and new methods to improve the quality of spectral signals in water Laser induced breakdown spectroscopy (LIBS) detection. Understanding the generation and evolution characteristics of the plasma induced by pulsed laser near the gas–liquid interface is of great significance for the establishment of evolution models and improvement of these new LIBS methods. In this paper, a set of slow horizontal flow auxiliary system is established to provide an ideal flat gas–liquid two-phase interface experimental condition. Experimental research on vertical incidence flat system was conducted using techniques such as time-resolved imaging, plasma characterization diagnosis, and spectral analysis. And the detection capabilities of the system were also tested. The characteristics and mechanisms of LIBS near the gas-liquid two-phase interface were investigated with the laser incident on the sample along the vertical direction. Simulation of the laser beam focusing process and observation of laser beam spot images show that the shift of plasma generation position relative to the focal point results from the refraction of the laser beam entering the solution from the air and the ‘interface effect’ of propagation on the vertical direction. Moreover, the plasma forms only the optical power density surpasses the breakdown threshold. In this work, plasma with smaller size, rounder shape, stronger radiation, higher temperature, and higher density can be produced when the focus position is in the liquid column 0.3 mm away from the upper interface. Simultaneously, for example, the Mg ion line at 285.213 nm, the obtained spectral intensity to signal-to-background ratio reaches the maximum value, and a better spectral signal can be obtained, which is 2–4 times of other positions, and the detection limits of the elements Na, Mg, and Ca also reach the lowest level, with 1.6–2.4 times of the detection limit of other focusing positions for Mg and 1.4–1.7 times for Ca, respectively.
Characterization of OH species in kHz air/H2O atmospheric pressure dielectric barrier discharges
Authors: Huang Cheng-Liang , Liao Tzu-Yi , He Yi-Ting , Lin Guan-Jung , Lai Wei-Hong , Chen Yi-Chi , Lin Kun-Mo
Published: May 2024

This work numerically studies densities and reaction mechanisms of OH species generated in atmospheric–pressure air dielectric barrier discharges with the model validated by experiments. The power consumption is measured, and the number of microdischarges (MDs) generated within a half period is captured by an intensified charge-coupled device (CCD) camera. The OH densities of cases with various H2O concentrations are measured using ultraviolet absorption spectroscopy. The numerical model integrating the 1.5D discharge fluid model and 3D background gas model (BGM) is adopted to predict the MD behavior and the generation of species related to OH generation. The simulated OH densities cover the range of 1.1 × 1019 and 1.6 × 1019 m−3 in the cases studied, agreeing with those measured. The simulated results show that most OH radicals are generated in MDs, while the reactive section contributes around 2% of the total OH generation. The detailed analysis shows that atomic oxygen (O(1D) and O) and O3 contribute most of the OH generation in the MDs. In contrast, the self-association reactions (i.e. 2OH + M → H2O2 + M and 2OH → O + H2O) and NO
x
species consume more than 64% of OH radicals generated in MDs. In the BGM, it is interesting to find that reactive species NO
x
play significant roles in both the OH generation and depletion in the reactive section. The distributions of species related to the OH species obtained by the BGM are presented to elucidate the detailed chemistry of OH species in the reactive section.
Comparing the mean inner potential of Zn-VI semiconductor nanowires using off-axis electron holography
Authors: Jose Anitha , Al-Turk Sarry , Ruda Harry E , Watkins Simon P , McCartney Martha R , Cordoba Cristina , Kavanagh Karen L
Published: May 2024

The mean inner potential (MIP), V
0, for a series of Zn group VI semiconductor nanostructures were measured experimentally using off-axis electron holography. Values for ZnS, ZnTe and ZnO were remeasured and new values were added for ZnSe and ZnSSe nanowires. We confirm that the MIP increases non-linearly with mass density beginning at 12.4 ± 0.2 V for the lowest density ZnS and slowly increasing with composition to 12.9 ± 0.2 V for ZnSe, more rapidly for ZnTe and with a significant increase to 14.8 ± 0.3 V for ZnO with the highest density. Published results from DFT calculations compared well to these measurements with similar trends apparent for other cation families such as the Ga-III-V.
Effect of distributed Bragg reflectors on optoelectronic characteristics of GaN-based flip-chip light-emitting diodes
Authors: Sun Yuechang , Shi Lang , Cui Yongjin , Tang Bin , Zhou Qianxi , Zhuang Jiaming , Zhou Shengjun
Published: May 2024

Distributed Bragg reflectors have been widely utilized in GaN-based flip-chip light-emitting diodes (FCLEDs) owing to their excellent reflection performance. Recently, wide reflected angle DBR (WRA-DBR) has been suggested to enhance the optical characteristics of GaN-based FCLEDs by incorporating multiple sub-DBRs with varying central wavelengths. However, the reflectivity of WRA-DBR decreases at large incident angle from 425 nm to 550 nm, which restricts further optical performance improvement of FCLEDs. Here, we demonstrate a quintuple-stack DBR comprised of five sub-DBRs. The quintuple-stack DBR possesses a high reflectivity (>97.5%) for incident angles below 50° within the blue and green light wavelength ranges. Compared to WRA-DBR, quintuple-stack DBR exhibits a higher reflectivity in wavelength range of 425 nm to 550 nm and thinner multilayer thicknesses. Furthermore, stronger electric field intensities exist in the top facet and sidewalls of FCLED with quintuple-stack DBR, revealing that quintuple-stack DBR is beneficial for enhancing the light extraction efficiency. As a result, the light output power of FCLED with quintuple-stack DBR is ∼3% higher than that of FCLED with WRA-DBR at 750 mA.
Enhancing light absorption of deep ultraviolet photodiodes through intelligent algorithm-guided design of resonant nano-optical structures
Authors: Zhu Yifan , Lu Huimin , Wang Jianping , Feng Liya , Ma Jianhua , Yu Tongjun , Li Junze
Published: May 2024

The surface of the deep ultraviolet (DUV) photodiodes requires an enhanced light absorption to improve wall-plug efficiency. The resonant Mie scatterer has a high optical mode density with a high refractive index all-dielectric resonant structure, which causes strong light coupling and improves forward scattering, providing a new perspective for efficient light absorption on the surface of the DUV photodiodes. In this work, a method is proposed for the design of nano-optical structures that is capable of supporting forward light scattering across the resonant bandwidth. This is achieved by utilizing intelligent algorithms in conjunction with Maxwell’s equations. The results show that the average light absorption coefficient of the optimized optical structure is improved to more than 96% with angle-independent and polarization-independent characteristics. Based on intelligent algorithms, a reverse design approach can be employed to maximize this effect, thereby offering novel avenues for enhancing the wall-plug efficiency of the DUV photodiodes.
Rotating coupling of chiral identical twins in multimodal Kresling metamaterials for achieving ultra-high energy absorption
Authors: Yang Haiying , Shu Dong-Wei , Lu Haibao , Tao Ran
Published: May 2024

Origami structures have been widely applied for various engineering applications due to their extraordinary mechanical properties. However, the relationship between in-plane rotating coupling and energy absorption of these Origami structures is seldom studied previously. The study proposes a design strategy that utilizes identical-twin rotation (i.e. simultaneous rotation with the same chirality) and fraternal-twin rotation (i.e. simultaneous rotation with the opposite chirality) of Kresling metamaterials to achieve multimodal rotation coupling and enhanced energy absorption. Deformation mode and energy absorption properties of 3D-printed Kresling metamaterials have been studied using both quasi-static compression tests and finite element analysis. Furthermore, effects of polygon units and their connections to 2D and 3D arrangements, which generate 4 × 4 arrays and 2 × 2 × 2 arrays, have been investigated to identify the optimized structures for achieving ultra-high energy absorption of chiral Kresling metamaterials. Results showed that rotating coupling of chiral identical twins in multimodal Kresling metamaterials possesses diverse deformation patterns and ultra-high energy absorption. This study provides a novel strategy to optimize structural designs and mechanical properties of the Kresling metamaterials.
Characterization of partially accessible anisotropic spin chains in the presence of anti-symmetric exchange
Authors: Cavazzoni Simone , Adani Marco , Bordone Paolo , Paris Matteo G A
Published: May 2024

We address quantum characterization of anisotropic spin chains in the presence of anti-symmetric exchange, and investigate whether the Hamiltonian parameters of the chain may be estimated with precision approaching the ultimate limit imposed by quantum mechanics. At variance with previous approaches, we focus on the information that may be extracted by measuring only two neighboring spins rather than a global observable on the entire chain. We evaluate the Fisher information (FI) of a two-spin magnetization measure, and the corresponding quantum Fisher information (QFI), for all the relevant parameters, i.e. the spin coupling, the anisotropy, and the Dzyaloshinskii–Moriya (DM) parameter. Our results show that the reduced system made of two neighboring spins may be indeed exploited as a probe to characterize global properties of the entire system. In particular, we find that the ratio between the FI and the QFI is close to unit for a large range of the coupling values. The DM coupling is beneficial for coupling estimation, since it leads to the presence of additional bumps and peaks in the FI and QFI, which are not present in a model that neglects exchange interaction and may be exploited to increase the robustness of the overall estimation procedure. Finally, we address the multiparameter estimation problem, and show that the model is compatible but sloppy, i.e. both the Uhlmann curvature and the determinant of the QFI matrix vanish. Physically, this means that the state of the system actually depends only on a reduced numbers of combinations of parameters, and not on all of them separately.