Conventional Wave Research Articles

Application value of strain elastography and shear wave elastography in patients with type 2 diabetic peripheral neuropathy: a prospective observational study.

To evaluate the value of conventional ultrasound (US), strain elastography (SE), and shear wave elastography (SWE) in detecting diabetic peripheral neuropathy (DPN) of the tibial nerve (TN), and to establish a predictive model for the diagnosis of DPN. 32 healthy participants, 34 diabetic patients without DPN, and 36 diabetic patients with DPN were recruited for this study. The TN at the ankle and popliteal fossa were selected for examination. US was used to measure the cross-sectional area (CSA) and perimeter of the TN. Additionally, SE was employed to measure the strain ratio (SR) between the TN and the surrounding adipose tissue, and SWE was used to measure the Shear Wave Velocity (SWV) of the TN. The CSA, perimeter, SR and SWV of the TN at the ankle were significantly higher in the DPN group compared to both the Non-DPN group and control group (P < 0.05). Similarly, the TN at the popliteal fossa showed these differences. At the ankle, the CSA, perimeter, SR, and SWV of the TN in patients without DPN were significantly higher than those in the control group (P < 0.05). At the popliteal fossa, the SR and SWV of the TN in patients without DPN were significantly higher than those in the control group (P < 0.05). However, the CSA and perimeter of the TN in patients without DPN did not show a statistically significant difference compared to the control group. The area under the curve (AUC) for the diagnosis of DPN using SWE is significantly greater than that of SE and US. US, SE, and SWE could be used to diagnose DPN, and they also have good diagnostic value for sub-clinical DPN. Among these methods, SWE has demonstrated superior diagnostic efficacy. Compared to examining the TN in the popliteal fossa, the ankle level offers a better site for examination. For diabetic peripheral neuropathy, US, SE, and SWE are all promising diagnostic methods with high clinical utility.

Phase velocity of love waves as function of heterogeneity and void parameter

The present study looks at the Love wave propagating through an elastic layer containing empty pores situated above a heterogeneous elastic semi-infinite space. We have constructed separate formulations of equations of motion for both media under congruous boundary conditions. The separation of variables approach is used to build the phase velocity frequency relation in compact form using the Whittaker function. The resulting closed-form dispersion equation matches the conventional Love wave equation when heterogeneity has been removed. The propagation of Love waves is strongly influenced by a porous layer of limited thickness across an elastic semi-infinite space. Three wave fronts are demonstrated to have the potential to propagate. The equilibrated inertia and the variation in the void volume fraction are related to two wave fronts that are connected to the characteristics of the void pores. Numerical treatments are applied and graphically illustrated to implement these effects associated to Love waves’ phase velocity.

Multifluid Theory of Electrostatic Ion Cyclotron Waves in Partially Ionized Plasmas

Partially ionized plasmas universally exist in various astrophysical environments, such as the solar atmosphere and the E region of the ionosphere. In these contexts, the existence and propagation of waves in plasmas could be significantly influenced by effects of weakly ionized plasma (e.g., ion–neutral collisions). In this work, we investigate electrostatic ion cyclotron (EIC) waves in partially ionized plasmas based on the multifluid model with adiabatic electrons. Two distinct branches of EIC waves coexist in partially ionized plasmas: one branch is the conventional EIC waves; the other branch propagates around the “effective ion cyclotron frequency” which originates from self-consistent ion–neutral collisions. Furthermore, theoretical predictions in the new branch of EIC waves are qualitatively consistent with laboratory observations. In addition, a comparison between our theory and the previous work is also performed. This work can aid in understanding the acceleration and transverse heating of ions in partially ionized astrophysical plasmas where the ion–neutral collisions are frequent.

Field study on proactive pipe condition assessment using hydroacoustic noise

Condition assessment of water transmission pipelines is of important necessity for prioritizing rehabilitation and preventing catastrophic pipe failure. Hydraulic transient analysis has been investigated for three decades for this purpose and applied to many field studies. However, the significant pipe vibrations caused by the transient generation process and the limited energy and bandwidth of conventional discrete transient pressure waves (e.g., step and pulse waves) limit the accuracy and resolution of the analysis. This paper reports a pilot field study of noninvasive and nondestructive pipe condition assessment using small amplitude and persistent hydroacoustic noise instead of conventional large and discrete hydraulic transient waves. By opening a discharge valve installed at an existing access point, such as an air valve, on the field pipe, hydroacoustic noise was generated at the valve due to the turbulence of the discharge. The hydroacoustic noise was measured by pressure transducers at this access point as well as some other access points along the field pipe. A signal deconvolution process was then applied to the measured hydraulic pressures to transfer them to a compositional impulse response function (IRF), which is composed of IRFs of different pipe sections. A mathematical model was derived to interpret the anomaly-induced spikes on the deconvolution trace. A time-shifting process on the compositional IRFs was proposed to find the locations with pipe condition changes from a specific direction of the pipe. The field study has shown that small-amplitude persistent hydroacoustic noise can replace conventional large hydraulic transient waves for pipe condition assessment.

VP-net: an end-to-end deep learning network for elastic wave velocity prediction in human skin in vivo using optical coherence elastography.

Acne vulgaris, one of the most common skin conditions, affects up to 85% of late adolescents, currently no universally accepted assessment system. The biomechanical properties of skin provide valuable information for the assessment and management of skin conditions. Wave-based optical coherence elastography (OCE) quantitatively assesses these properties of tissues by analyzing induced elastic wave velocities. However, velocity estimation methods require significant expertise and lengthy image processing times, limiting the clinical translation of OCE technology. Recent advances in machine learning offer promising solutions to simplify velocity estimation process. In this study, we proposed a novel end-to-end deep-learning model, named velocity prediction network (VP-Net), aiming to accurately predict elastic wave velocity from raw OCE data of in vivo healthy and abnormal human skin. A total of 16,424 raw phase slices from 1% to 5% agar-based tissue-mimicking phantoms, 28,270 slices from in vivo human skin sites including the palm, forearm, back of the hand from 16 participants, and 580 slices of facial closed comedones were acquired to train, validate, and test VP-Net. VP-Net demonstrated highly accurate velocity prediction performance compared to other deep-learning-based methods, as evidenced by small evaluation metrics. Furthermore, VP-Net exhibited low model complexity and parameter requirements, enabling end-to-end velocity prediction from a single raw phase slice in 1.32ms, enhancing processing speed by a factor of ∼100 compared to a conventional wave velocity estimation method. Additionally, we employed gradient-weighted class activation maps to showcase VP-Net's proficiency in discerning wave propagation patterns from raw phase slices. VP-Net predicted wave velocities that were consistent with the ground truth velocities in agar phantom, two age groups (20s and 30s) of multiple human skin sites and closed comedones datasets. This study indicates that VP-Net could rapidly and accurately predict elastic wave velocities related to biomechanical properties of in vivo healthy and abnormal skin, offering potential clinical applications in characterizing skin aging, as well as assessing and managing the treatment of acne vulgaris.

Combination of Different Sectional Elastography Techniques with Age to Optimize the Downgrading of Breast BI-RAIDS Class 4a Nodules.

This study aims to optimize the downgrading of BI-RADS class 4a nodules by combining various sectional elastography techniques with age. We performed conventional ultrasonography, strain elastography (SE), and shear wave elastography (SWE) on patients. Quantitative parameters recorded included age, cross-sectional and longitudinal area ratios (C-EI/B, L-EI/B), strain rate ratios (C-SR, L-SR), overall average elastic modulus values (C-Emean1, L-Emean1), five-point average elastic modulus values (C-Emean2, L-Emean2), and maximum elastic modulus values (C-Emax, L-Emax). Histopathological evaluations showed that out of 230 lesions, 45 were malignant, and 185 were benign. The sensitivity and specificity of conventional ultrasonography were 100% and 0%, respectively. In contrast, SE and SWE exhibited higher specificity but lower sensitivity. Crosssectional parameters (C-EI/B, C-SR, C-Emean1, C-Emean2, and C-Emax) outperformed their longitudinal counterparts, with C-SR and C-Emax showing the highest specificity (72.43% and 73.51%) and satisfactory sensitivity (80.00% and 88.89%). Combining age with C-SR and C-Emax significantly improved diagnostic efficiency, achieving a sensitivity of 97.78% and a specificity of 77.30%. Integrating age with C-SR and C-Emax effectively reduces unnecessary biopsies for most BI-RADS 4a benign lesions while maintaining a very low misdiagnosis rate.

Modeling Rayleigh wave in viscoelastic media with constant Q model using fractional time derivatives

The propagation of seismic waves within the near-surface weathering layers, characterized by their low-quality factors (Q), is often accompanied by strong attenuation and dispersion phenomena. Among these, the Rayleigh wave, with its sensitivity to dispersion, has proven to be a powerful tool for near-surface exploration. We propose a novel approach for simulating Rayleigh wave propagation in such low-Q media. Our method uses the time-domain fractional wave equation with memory effect, based on Kjartansson's constant-Q (CQ) model, for accurate characterization of the propagation process. To solve numerically the wave equation with the fractional derivatives, we employ a finite-difference method combined with the auxiliary differential equation-perfectly matched layer (ADE-PML) and the acoustic-elastic boundary approach (AEA). The algorithm's high computational accuracy is verified through comparison with the conventional integer-order wave equation based on the nearly constant-Q (NCQ) models in strong attenuation media. The research in this paper deepens our understanding of the propagation characteristics of Rayleigh waves in strongly weathering layers. This new method strongly supports those seismic imaging and inversion methods depending on seismic modeling, including the reverse time migration and the full waveform inversion of the internal structure of low-Q media.

Advancements and Future Prospects in Ocean Wave Energy Harvesting Technology Based on Micro-Energy Technology.

Marine wave energy exhibits significant potential as a renewable resource due to its substantial energy storage capacity and high energy density. However, conventional wave power generation technologies often suffer from drawbacks such as high maintenance costs, cumbersome structures, and suboptimal conversion efficiencies, thereby limiting their potential. The wave power generation technologies based on micro-energy technology have emerged as promising new approaches in recent years, owing to their inherent advantages of cost-effectiveness, simplistic structure, and ease of manufacturing. This paper provides a comprehensive overview of the current research status in wave energy harvesting through micro-energy technologies, including detailed descriptions of piezoelectric nanogenerators, electromagnetic generators, triboelectric nanogenerators, dielectric elastomer generators, hydrovoltaic generators, and hybrid nanogenerators. Finally, we provide a comprehensive overview of the prevailing issues and challenges associated with these technologies, while also offering insights into the future development trajectory of wave energy harvesting technology.

Dual-type heterogeneous interface design enables customized tuning of dielectric parameters of multifunctional, lightweight, flexible absorbers for broadband electromagnetic wave absorption

With the boom in 5 G technology comes widespread concern about electromagnetic (EM) interference and the safe use of electronics. Conventional electromagnetic wave (EMW) absorbing materials in the form of coatings are often inflexible and poorly adapted to different EM environments. Diversified application scenarios require EMW absorbing materials with a wide absorption band and multifunctional properties. Herein, the frequency dispersion (FD) requirements of the EM parameters of the broadband absorber in different frequency bands are determined by EM simulation. Based on the dominant role of interface polarization on FD, we designed different types of heterogeneous interfaces to meet the needs of strong FD in the low-frequency band and weak FD in the high-frequency band. Through the optimized design of heterogeneous interfaces, CC@ZnO/ZnS composites exhibit excellent EMW absorption performance, achieving flexible, ultrathin (2.1 mm), ultralight (10 wt%), and broadband (7.02 GHz), which is superior to EMW absorbing materials of similar compositions. In addition, the composites have good piezoelectric/inverse piezoelectric properties, which can convert EM energy into mechanical energy while absorbing EMW, thus realizing applications in multifunctional fields such as sensors, controllers and energy converters. More noteworthy is the sample's highly efficient thermal insulation, flame retardant and anti-frosting properties, demonstrating important advantages for service in harsh environments. Therefore, CC@ZnO/ZnS composites not only have good practical application characteristics while realizing broadband absorption, but also are expected to achieve multifunctional applications in different fields.

Identification and Application of Wave Field Characteristics of Channel Waves in Extra-Thick Coal Seams

Channel wave seismic activity often occurs with thin and medium-thick coal seams being the main target layer. To address the problem of channel wave applicability detection in extremely thick coal seams, the propagation and identification characteristics of channel waves remain the focus of research. Therefore, this paper takes the in-seam wave exploration of a 27 m extremely thick coal seam as an example and uses the staggered mesh finite difference method to construct a three-dimensional medium model for numerical simulation. An analysis of the physical parameters of coal and rock, along with the dispersion characteristics of channel waves in extra-thick coal seams, is utilized, through the Zoeppritz equation and the total reflection propagation method, to calculate the imaging. We found the following: (1) The dispersion areas and weak dispersion areas along the detection direction are extremely thick coal seams. (2) There are apparent channel waves in extra-thick coal seams, with a waveform similar to body waves; the length of the wave train is shorter than that of the conventional channel wave, and the arrival time can be estimated accurately. The amplitude of the apparent channel wave is affected by the degree of dispersion, with lower attenuation and higher resolution. The characteristic of total reflection in extremely thick coal seams is that the incident angle is equal to the critical angle, and the dispersion characteristics are weak. (3) The channel waves with weak dispersion characteristics in extra-thick coal seams are mainly Love-type waves.

Subclinical left ventricular structural and functional alterations in children with obesity: is body mass or insulin resistance the main issue?

Obesity is an independent risk factor for cardiovascular diseases. The study aims to assess the left ventricular structure and functions in children with obesity. This study included 29 patients with metabolic syndrome, 31 patients with obesity without metabolic syndrome, and 30 healthy children of similar age and gender. Demographic, anthropometric, and biochemical findings and left ventricular structure and functions evaluated by conventional pulsed wave Doppler and tissue Doppler echocardiography were compared. The left ventricular mass index and relative wall thickness were significantly higher in children with obesity compared to controls. The mean left ventricular mass index of children with metabolic syndrome was also higher than for those without it. Most children with obesity had normal left ventricular geometry; concentric hypertrophy (27.6%) was more common in children with metabolic syndrome, and eccentric hypertrophy (25.7%) was more common in those without. The early to late diastolic mitral annular velocity ratios obtained with conventional pulsed wave Doppler echocardiography and tissue Doppler echocardiography (E/A and Em/Am, respectively) were lower in children with obesity than controls. In addition, the ratio obtained by tissue Doppler echocardiography was lower in children with metabolic syndrome than without. The homeostatic model assessment of insulin resistance, systolic blood pressure, and body mass index has been identified as independent factors for left ventricular structures and functions. Obesity causes subclinical left ventricular hypertrophy and diastolic dysfunction. Additional metabolic syndrome-related risks lead to further deterioration of cardiac morphology and functions.

Acoustofluidic Diversity Achieved by Multiple Modes of Acoustic Waves Generated on Piezoelectric-Film-Coated Aluminum Sheets.

Excitation of multiple acoustic wave modes on a single chip is beneficial to implement diversified acoustofluidic functions. Conventional acoustic wave devices made of bulk LiNbO3 substrates generally generate few acoustic wave modes once the crystal-cut and electrode pattern are defined, limiting the realization of acoustofluidic diversity. In this paper, we demonstrated diversity of acoustofluidic behaviors using multiple modes of acoustic waves generated on piezoelectric-thin-film-coated aluminum sheets. Multiple acoustic wave modes were excited by varying the ratios between IDT pitch/wavelength and substrate thickness. Through systematic investigation of fluidic actuation behaviors and performances using these acoustic wave modes, we demonstrated fluidic actuation diversities using various acoustic wave modes and showed that the Rayleigh mode, pseudo-Rayleigh mode, and A0 mode of Lamb wave generally have better fluidic actuation performance than those of Sezawa mode and higher-order modes of Lamb wave, providing guidance for high-performance acoustofluidic actuation platform design. Additionally, we demonstrated diversified particle patterning functions, either on two sides of acoustic wave device or on a glass sheet by coupling acoustic waves into the glass using the gel. The pattern formation mechanisms were investigated through finite element simulations of acoustic pressure fields under different experimental configurations.

The added value of shear wave elastography when combined to conventional ultrasonography and fine-needle aspiration cytology in detection of malignant thyroid nodule

BackgroundThis study aims to evaluate the effectiveness of ultrasound criteria, TI-RADS score, and elastography in distinguishing benign thyroid nodules from malignant ones, as a substitute for invasive diagnostic procedures. Although the minority of thyroid nodules is malignant, invasive diagnostic procedures are often necessary.MethodsIn this prospective study, a total of 104 thyroid nodules were assessed using fine-needle aspiration cytology. The euthyroid state of the patients was ensured. Conventional ultrasound and shear wave elastography (SWE) were performed by a single experienced operator. Final postoperative histopathologic findings were compared to conventional ultrasound and elastography findings.ResultsSWE elasticity indices (EIs) were found to be significantly higher in malignant nodules than benign ones (p < 0.05). Combined results of both TI-RADS and SWE increased the sensitivity of detection of malignant nodules.ConclusionCombined SWE and TI-RADS could enhance the diagnostic accuracy in differentiating thyroid nodules by leveraging their complementary strengths.

An efficient ultrasonic wavenumber-domain plane wave imaging method towards the inspection of curved structures

Ultrasonic phased array testing is commonly employed for inspecting curved structures. Conventional plane wave imaging techniques, based on delay-and-sum in the time-domain, offer high image quality and inspection accuracy but suffer from low frame rates due to their high computational complexity. In this work, an efficient wavenumber-domain imaging method that combines non-stationary wavefield extrapolation and f-k migration is proposed for curved structure inspection. Special emission focal laws are designed to generate a sequence of steered plane waves through the curved interface. The raw data is then extrapolated to the top boundary of the region of interest, followed by f-k migration to reconstruct images with high time efficiency. Simulation and experimental evaluations demonstrate a time reduction by a factor of up to 32.24 compared to conventional time-domain plane wave image reconstruction with equivalent image quality, highlighting its potential for monitoring flaws in real-time.

Shear wave velocity prediction for fractured limestone reservoirs based on artificial neural network

AbstractShear wave velocity is an essential parameter in reservoir characterization and evaluation, fluid identification and prestack inversion. However, conventional data‐driven or model‐driven shear wave velocity prediction methods exhibit several limitations, such as lack of training data sets, poor model generalization and weak model robustness. In this study, a model‐ and data‐driven approach is presented to facilitate the solution of these problems. We develop a theoretical rock physics model for fractured limestone reservoirs and then use the model to generate synthetic data that incorporates geological and geophysical knowledge. The synthetic data with random noise is utilized as the training data set for the artificial neural network, and a well‐trained shear wave velocity prediction model, random noise shear wave velocity prediction neural network, is established by parameter tuning, which fits the synthetic data with noise well. The neural network is applied directly to the real field area. Compared with conventional shear wave prediction methods, such as empirical formulas and the improved Xu–White model, the prediction results show that the random noise shear wave velocity prediction neural network has better prediction performance and generalization. Furthermore, the prediction results demonstrate the efficacy of the proposed approach, and the approach has the potential to perform shear wave velocity prediction in real areas where training data sets are unavailable.

1-Norm waveform analysis for MR elastography-based quantification of inhomogeneity: Effects of the freeze-thaw cycle and Alzheimer's disease

BackgroundDespite its success in the mechanical characterization of biological tissues, magnetic resonance elastography (MRE) uses ill-posed wave inversions to estimate tissue stiffness. 1-Norm has been recently introduced as a mathematical measure for the scattering of mechanical waves due to inhomogeneities based on an analysis of the delineated contours of wave displacement. PurposeTo investigate 1-Norm as an MRE-based quantitative biomarker of mechanical inhomogeneities arising from microscopic structural tissue alterations caused by the freeze-thaw cycle (FTC) or Alzheimer's disease (AD). MethodsIn this proof-of-concept study, we prospectively investigated excised porcine kidney (n = 6), liver (n = 6), and muscle (n = 6) before vs. after the FTC at 500–2000 Hz and excised murine brain of healthy controls (n = 3) vs. 5xFAD species with AD (n = 3) at 1200–1800 Hz using 0.5 T tabletop MRE. 1-Norm analysis was compared with conventional wave inversion. ResultsWhile the FTC reduced both stiffness and inhomogeneity in kidney, liver, and muscle tissue, AD led to lower brain stiffness but more pronounced mechanical inhomogeneity. ConclusionOur preliminary results show that 1-Norm is sensitive to tissue mechanical inhomogeneity due to FTC and AD without relying on ill-posed wave inversion techniques. 1-Norm has the potential to be used as an MRE-based diagnostic biomarker independent of stiffness to characterize abnormal conditions that involve changes in tissue mechanical inhomogeneity.

Fully ab-initio all-electron calculation of dark matter-electron scattering in crystals with evaluation of systematic uncertainties

We calculate target-material responses for dark matter–electron scattering at the all-electron level using atom-centered Gaussian basis sets. The all-electron effects enhance the material response at high momentum transfers from dark matter to electrons, q≳O(10αme), compared to calculations using conventional plane wave methods, including those used in ; this enhances the expected event rates at energy transfers E≳10 eV, especially when scattering through heavy mediators. We carefully test a range of systematic uncertainties in the theory calculation, including those arising from the choice of basis set, exchange-correlation functional, number of unit cells in the Bloch sum, k-mesh, and neglect of scatters with very high momentum transfers. We provide state-of-the-art crystal form factors, focusing on silicon and germanium. Our code and results are made publicly available as a new tool, called (“”). Published by the American Physical Society 2024

Full Dispersion‐Spectrum Inversion of Surface Waves

AbstractNowadays, the most successful applications of full‐waveform inversion (FWI) involve marine seismic data under acoustic approximations. Elastic FWI of land seismic data is still challenging in theory and practice. Here, we propose a full dispersion spectrum inversion method and apply it to seismic data acquired in West Antarctica. Inspired by the conventional surface wave dispersion curve inversion method, we propose to invert the surface wave dispersion spectrum instead of the complicated waveforms. We compare the frequency‐velocity, frequency‐slowness, and frequency‐wavenumber spectra in terms of their ability to resolve dispersion modes and the feasibility of their adjoint updates and conclude that the frequency‐slowness spectrum is the best for our inversion objectives. We test four objective functions, subtraction, zero‐lag crosscorrelation, optimal transport, and the local‐crosscorrelation to quantify the spectrum mismatch and provide the corresponding adjoint source. We then theoretically analyze the convexity of the proposed objective functions and examine their convergence behavior using numerical examples. We also compare the proposed method with the classic FWI method and the traditional surface wave dispersion curve inversion method and discuss the strengths and weaknesses of each method. This technique is employed to evaluate the shallow velocity structures beneath a seismic array stationed in West Antarctica. Our proposed inversion scheme is also useful for more general applications such as imaging the shallow subsurface of the critical zones, like geothermal reservoirs, and CO2 storage sites.

Burst sine wave electroporation (B-SWE) for expansive blood-brain barrier disruption and controlled non-thermal tissue ablation for neurological disease.

The blood-brain barrier (BBB) limits the efficacy of treatments for malignant brain tumors, necessitating innovative approaches to breach the barrier. This study introduces burst sine wave electroporation (B-SWE) as a strategic modality for controlled BBB disruption without extensive tissue ablation and compares it against conventional pulsed square wave electroporation-based technologies such as high-frequency irreversible electroporation (H-FIRE). Using an in vivo rodent model, B-SWE and H-FIRE effects on BBB disruption, tissue ablation, and neuromuscular contractions are compared. Equivalent waveforms were designed for direct comparison between the two pulsing schemes, revealing that B-SWE induces larger BBB disruption volumes while minimizing tissue ablation. While B-SWE exhibited heightened neuromuscular contractions when compared to equivalent H-FIRE waveforms, an additional low-dose B-SWE group demonstrated that a reduced potential can achieve similar levels of BBB disruption while minimizing neuromuscular contractions. Repair kinetics indicated faster closure post B-SWE-induced BBB disruption when compared to equivalent H-FIRE protocols, emphasizing B-SWE's transient and controllable nature. Additionally, finite element modeling illustrated the potential for extensive BBB disruption while reducing ablation using B-SWE. B-SWE presents a promising avenue for tailored BBB disruption with minimal tissue ablation, offering a nuanced approach for glioblastoma treatment and beyond.

Modulating charge density wave states in 1T-TaS[formula omitted] by self-intercalation: A DFT study

Complicated charge density wave (CDW) phases transitions in the transition-metal dichalcogenide (TMDs) 1T-TaS2 have attracted wide research interest owing to the accompanied complex electronic structure transition which has not been fully understood. Inspired by a recent experimental work (Zhao et al. (2020), reported the successful preparation of Ta atom self-intercalated 2H-TaS2), we employed first-principles methods to investigate Ta atom self-intercalated 1T-TaS2, exploring effects of self-intercalation on electronic structure, magnetism, and stability ofthe charge density wave (CDW) phase in 1T-TaS2. Our first-principle calculation shows that the intercalation of Ta atom into the van der Waals gap of 1T-TaS2 induce the phase transition from 1T phase to CDW phase, and the positions of intercalated Ta atom determine the distribution of David-star clusters. Accompanied by the structural phase transition, the Ta intercalated 1T-TaS2 also undergoes an electronic structure phase transition from non-magnetic metal to half-metal which is also different from conventional charge density wave’s insulating state. When appropriate holes are doped to the intercalation system, the CDW David-star cluster is gradually destroyed and eventually returns to its original 1T phase. Our studies enrich the phase diagram of TaS2 and highlight the effective manipulation of the CDW states via self-intercalation. This type of materials may have very promising applications in future electronic devices.