Low Thermal Conductivity Materials Research Articles

Selection of phase change material for latent heat thermal energy storage using a hair-pin heat exchanger: Numerical Study

Abstract Phase change materials (PCMs) are promising for storing thermal energy as latent heat, addressing power shortages. Growing demand for concentrated solar power systems has spurred the development of latent thermal energy storage, offering steady temperature release and compact heat exchanger designs. This study explores melting and solidification in a hairpin-type heat exchanger (HEX) using three PCMs (RT 50, RT 27, and RT 35). A 3D model of the hairpin type heat exchanger (HEX) is drawn using Ansys-workbench. High-temperature fluid/Low-temperature fluid (HTF/LTF) with Stefan numbers (0.44, 0.35, and 0.23) flows through the inner pipe to charge the outer pipe's PCM. The Enthalpy-porosity model is used to study the melting and solidification of various PCMs, and the results were compared. Also, individual thermophysical properties that affect the heat transfer during the melting and solidification process have been discussed. It is observed that low thermal conductivity material with high latent heat is preferred for cold climates. In this study, RT 27 excels in cold climates due to extended solidification time, while RT 50 is effective in tropical regions due to its high melting points and lower latent heat.

GaInX3(X = S; Se; Te): ultra-low thermal conductivity and excellent thermoelectric performance

Abstract Seeking intrinsically low thermal conductivity materials is a viable strategy in the pursuit of high-performance thermoelectric materials. Here, by using first-principles calculations and semiclassical Boltzmann transport theory, we systemically investigate the carrier transport and thermoelectric properties of monolayer Janus GaInX3 (X = S; Se; Te). It is found that the lattice thermal conductivities can reach values as low as 3.07 Wm−1K−1, 1.16 Wm−1K−1 and 0.57 Wm−1K−1 for GaInS3, GaInSe3, and GaInTe3, respectively, at room temperature. These notably low thermal conductivity is attributed to strong acoustic-optical phonon coupling caused by the presence of low-frequency optical phonons in GaInX3 materials. Furthermore, by integrating the characteristics of electronic and thermal transport, the dimensionless figure of merit ZT can reach maximum values of 0.95, 2.37, and 3.00 for GaInS3, GaInSe3, and GaInTe3, respectively. Our results suggest monolayer Janus GaInX3 (X = S; Se; Te) are promising candidates for thermoelectric and heat management applications.

Enhancing the melting performance in latent heat storage systems with fin-foam combination at high temperatures: Configurational optimization and economic assessment

High-temperature latent heat thermal energy storage is restricted by the low thermal conductivity materials. To achieve rapid heat storage, a fin-foam synergistic heat transfer enhancement is proposed to break the marginal improvement of unilateral enhancement. The effect of different enhancement methods is explored by constructing 3D numerical models. The numerical result indicates the optimal fin-foam synergistic enhancement can effectively reduce the full melting time by 59.7%, compared with the smooth-foam unilateral enhancement. Further, the relationship between temperature uniformity and thermal performance has been refined. Internal fins achieve more efficient heat transfer from the tube center to the tube edge, accompanied by a 29.1% improvement in temperature uniformity of heat transfer fluid. A comprehensive index including the pump cost is established for economic assessment. The fin-foam synergistic enhancement has been proved to be the most cost-effective, achieving relatively high performance and avoiding excessive pressure drop.

Searching for low thermal conductivity materials for thermal barrier coatings: A theoretical approach

Searching for low thermal conductivity materials for thermal barrier coatings: A theoretical approach

High throughput screening of semiconductors with low lattice thermal transport induced by long-range interactions.

Semiconductors with long-range interactions (LRI) due to resonant bonding exhibit delocalized electronic states and low lattice thermal conductivity, contributing to the efficiency of heat-to-electricity conversion. Here, we build a descriptor for high-throughput screening of LRI materials from the second-order interaction force constants. We identify 75 semiconducting candidates from the binary compounds in the MatHub-3d database that contain LRI. By analyzing the bonding properties of LRI atoms, we classify LRI in materials into two categories: type I and type II. In the structural unit of type I LRI, the atoms have strong bond connections, while a weak bond exists between the two groups in the structural unit of type II LRI. We have identified atypical type I LRI formed by Sb-Sb and Mg-Mg pairs in the emerging thermoelectric material Mg3Sb2, resulting in the softening of TA1 phonons and large anharmonicity. For type II LRI, the LRI of Ge-Ge and Se-Se pairs in R3m-GeSe can cross different layers. Moreover, we observe a combination of type II LRI and rattling effect in BaSe2 to restrict thermal transport. This work is of great significance for understanding the relationship between LRI and thermal transport properties, and for designing new LRI-induced low lattice thermal conductivity materials.

Design and thermal test of high-vacuum insulator for heat delivery pipes

Thermal piping insulation of implants is crucial for heat delivery, production, collection, or storage at high temperature values. It is currently obtained by enveloping low thermal conductivity materials such as rockwool, fiberglass, polyurethane, polystyrene, and aerogel. However, better performances can be reached by adopting vacuum technology. In this case, conductive losses are annihilated, and the radiative heat transfer mechanism represents the only loss mechanism. Here, we compare a high vacuum-based novel solution and the traditional insulation for heat delivery applications. We propose a high vacuum- based solution consisting of an evacuated gap that surrounds the hot pipe coated by a thin aluminium foil. Experimental results using this novel solution show a fivefold reduction of the thermal radiation losses compared to the traditional solutions when in the temperature range between 100 °C and 250 °C.

Extreme sensitivity of higher-order interatomic force constants and thermal conductivity to the energy surface roughness of exchange-correlation functionals

In this Letter, we report that the fourth-order interatomic force constants (4th-IFCs) are significantly sensitive to the energy surface roughness of exchange-correlation (XC) functionals in density functional theory calculations. This sensitivity, which is insignificant for the second- (2nd-) and third-order (3rd-) IFCs, varies for different functionals in different materials and can cause misprediction of thermal conductivity by several times of magnitude. As a result, when calculating the 4th-IFCs using the finite difference method, the atomic displacement needs to be taken large enough to overcome the energy surface roughness, in order to accurately predict phonon lifetime and thermal conductivity. We demonstrate this phenomenon on a benchmark material (Si), a high-thermal conductivity material (BAs), and a low thermal conductivity material (NaCl). For Si, we find that the LDA, PBE, and PBEsol XC functionals are all smooth to the 2nd- and 3rd-IFCs but all rough to the 4th-IFCs. This roughness can lead to a prediction of nearly one order of magnitude lower thermal conductivity. For BAs, all three functionals are smooth to the 2nd- and 3rd-IFCs, and only the PBEsol XC functional is rough for the 4th-IFCs, which leads to a 40% underestimation of thermal conductivity. For NaCl, all functionals are smooth to the 2nd- and 3rd-IFCs but rough to the 4th-IFCs, leading to a 70% underprediction of thermal conductivity at room temperature. With these observations, we provide general guidance on the calculation of 4th-IFCs for an accurate thermal conductivity prediction.

Package Design Thermal Optimization for Metal-Oxide Gas Sensors by Finite Element Modeling and Infra-Red Imaging Characterization.

We designed a 3D geometrical model of a metal-oxide gas sensor and its custom packaging and used it in finite element modeling (FEM) analysis for obtaining temperature and heat flux distribution. The 3D computer simulation, performed with GetDP software (version 3.5.0, 13 May 2022), accurately predicted the temperature distribution variation across the entire assembly. Knowing the temperature variation and the location of the hot spots allowed us to select the best electrical interconnect method and to choose the optimal materials combination and optimal geometry. The thermal modeling also confirmed the need to use a low thermal conductivity material to insulate the MOX sensor since the latter is heated to its operational temperature of 250 °C. For that purpose, we used the in-house formulated xerogel-epoxy composite of thermal conductivity of 0.108 W m-1 K-1, which is at least 30% less compared to the best-in-class among commercially available materials. Based on the 3D FEM outputs, we designed, assembled, and characterized a fully functional packaged MOX gas sensor in several configurations. We measured the temperature distribution on all parts of the MOX gas sensor assembly using a thermal imaging infrared (IR) microscope. The results of 3D FEM are in good agreement with the temperature distribution obtained by the non-contact IR thermal characterization.

Experimental study of an innovative elastomer-based heat exchanger

This work aims to present the development stages of a serpentine heat exchanger, composed uniquely of a thin layer of a silicon-based organic elastomeric polymer, polydimethylsiloxane (PDMS). The novelty of this heat exchanger is that it allows the flowing liquid to wet the surface to be cooled directly, an innovation in relation to traditional exchangers, generally made up of tubes coupled to the heating surfaces. In order to evaluate its thermal performance, experimental flow tests compared two PDMS serpentines with a hydraulic diameter of around 5.0 mm with a traditional tubular copper serpentine. The heat exchanger made of PDMS was coupled to a steel plate that simulated the rear side of a photovoltaic thermal solar panel (PVT). In addition, different geometries were tested. Although PDMS is considered a material of low thermal conductivity, the experimental results showed a greater cooling capacity when compared to the traditional heat exchanger reducing the surface's temperature by an average of 17%. Though the experimental results presented here were obtained for a specific case, the innovation can be used for thermal control of central process units (CPUs), smartphones, tablets, video games, and other mechanical and electronic devices with high cooling requirements.

Effectiveness of coolant on sustainable drilling and hole quality of titanium alloy

The present research investigated the effects of input parameters such as feed rate, cutting speed and coolant type on sustainability and hole quality during the drilling of Ti-6Al-4V alloy. Several output parameters such as surface roughness, burr height, chip thickness ratio, thrust force, torque and peak power consumption were measured and analysed. Higher cutting speeds (2000 r/min) and lower feed rates (0.04 mm/rev) are recommended to be used to reduce drilling torque (0.77 Nm), thrust force (695 N) and power consumption (0.07 kW). However, it should be noted that increasing cutting speed (2000 r/min) can increase tool tip temperature which is detrimental, particularly for low thermal conductivity materials such as titanium alloys. In addition to that, the effect of tool wear also cannot be negated, as increased tool wear generates more heat in the cutting zone which was not effectively removed due to the poor thermal conductivity of titanium. Liquid nitrogen and chilled air had the greatest influence on temperature reduction at the cutting zone, however, its poor penetration and lubrication properties diminished hole quality. Minimum quantity lubrication conditions proved to strike a balance between good hole quality and enhancing sustainable machining by lowering torque, force and power consumption.

Investigation of Analog/RF and linearity performance with self-heating effect in nanosheet FET

In vertically stacked gate-all-around Nanosheet FET (NSFET), the channels/sheets are wrapped by a low thermal conductivity material, which hinders the active heat flow path and, thus, raises reliability concerns. Therefore, the role of temperature, i.e., ambient condition and self-heating effect (SHE), become prime objectives that must be adequately addressed. In this work, through extensive TCAD simulations, we analyzed the DC/Analog/RF/Linearity characteristics of an NSFET, considering the cumulative effect of ambient temperature and SHE. Using well-calibrated TCAD models, we investigated: (i) the variation in device characteristics with and without considering SHE; (ii) the impact of SHE and ambient temperature on Analog/RF and Linearity characteristics using well-defined figure-of-merits (FoMs); (iii) the device optimization, i.e., the significance of the varying number of sheets (Nsheet) with considering SHE for optimal performance; (iv) the impact of varying temperature over the voltage gain of an NSFET-based common source (CS) amplifier considering SHE. The temperature variation (including SHE) significantly affects the ON current (e.g., reduced by 9.4%), resulting in the modulation in transconductance (gm). Therefore, the designed CS amplifier's gain is also altered by temperature variation (e.g., ranging from 250 K to 400 K). Hence, the proposed analysis is worth exploring to acquire the design guidelines for optimal and reliable DC/Analog/RF/Linearity characteristics of a Nanosheet transistor under various temperature conditions.

Screening outstanding mechanical properties and low lattice thermal conductivity using global attention graph neural network

Mechanical and thermal properties of materials are extremely important for various engineering and scientific fields such as energy conversion and energy storage. However, the characterization of these properties via high throughput screening at the quantum level, although highly accurate, is inefficient and very time- and resource-consuming. In contrast, prediction at the classical level is highly efficient but less accurate. We deploy scalable global attention graph neural network for accurate prediction of mechanical properties which bridge the gap between the accuracy at the quantum level and efficiency at the classical level. Using 10,158 elastic constants as training data, we trained the models on 5 mechanical properties, namely bulk modulus, shear modulus, Young's modulus, Poisson's ratio, and hardness. With the trained model, we predicted 775,947 data in search of materials with ultrahigh hardness. We further verify the recommended ultrahigh hardness materials by high precision first principles calculations, and we finally identify 20 structures with extreme hardness close to diamond, the hardest material in nature. Among those, two super hard materials are completely new and have not been reported in literature so far. We further recommend potential materials from bulk modulus prediction to search low lattice thermal conductivity, and we verify the thermal conductivity of 338 structures with first principles. Our results demonstrate that one can find materials with extreme mechanical properties recommended by graph neural network and low thermal conductivity material from bulk modulus prediction with minimal first principles calculations of the structures (only 0.04%) in the large-scale materials pool.

Research on New Solid Waste Heat Insulation Material for Deep Mining

The global demand for mineral resources has led to the gradual transformation of the mining industry from the traditional shallow, small-scale mining mode to the high-intensity mining of deep underground mines. Due to the high stress, high temperature, high permeability, and easy disturbance of deep mines, new challenges have been brought to the mining of materials. Some scholars have improved the thermal insulation performance of concrete by adding low thermal conductivity materials such as ceramsite, shell, and natural fiber to traditional shotcrete, but there are still high costs, insufficient support strength, and unsatisfactory thermal insulation effects. Given the background related to the fact that it is still not possible to fully recycle the large amount of solid waste generated by mining activities, this paper, with traditional shotcrete as its basis, uses coal fly ash to replace part of the cement and tailings to replace part of the sand and gravel aggregate. In addition, it adds basalt fiber to reduce thermal conductivity and restore strength. An orthogonal experiment of three factors and three levels was designed to explore a new type of solid waste-based thermal insulation support shotcrete material. Through the testing and analysis of the mechanical and thermal properties of the specimens, it was concluded that the optimal ratio of the materials was 45% fly ash, 50% tailings, and 25% basalt fiber (the percentage of the total mass of fly ash and cement). The compressive strength of the specimens after curing for 28 days could reach 16.26 MPa, and the thermal conductivity and apparent density were 0.228561 W/(m·k) and 1544.00 kg/m3, respectively. By using COMSOL Multiphysics multi-physics coupling software to analyze the coupling of the stress field and temperature field, it was concluded that the optimum thickness of the thermal insulation layer of this material was 150 mm. The field application in a mine in Shandong Province proved that it met the effects of thermal insulation (the ability to isolate heat conduction) and support. The successful trial of this material provides a new idea for the solving of the problem of heat damage and solid waste utilization in deep mines, which has a certain practical significance.

Simultaneous measurement of normal spectral emissivity and temperature of materials with low thermal conductivity

This study develops a measurement system and a method for measuring the normal spectral emissivity and temperature of low thermal conductivity materials at high temperatures. A self-design heating device using a synergistic heating treatment including a high-power laser and a radiation heating cavity is introduced, and a Fourier transform infrared spectrometer is utilized to measure the radiation signal of sample. Based on the temperature hypothesis model, which considers normal spectral emissivity keeps constant within small temperature difference less than 10.0 K, a method is proposed for realizing the inversion of normal spectral emissivity and temperature with the multispectral radiation signal. A genetic algorithm-based technique with big mutations is used to estimate the normal spectral emissivity and temperature of sample at high temperatures. The variation of blackbody radiation signals with the blackbody radiance is analyzed to verify the linearity for the detector of FTIR spectrometer. The apparent normal spectral emissivity of an alumina ceramic fiber is determined in the spectral range of 2.5–25.0 μm at 673–1273 K. Furthermore, the uniformity of temperature distribution on the sample surface and inside the sample is numerically evaluated. The standard uncertainty in the experiment at 1273 K is less than 4.0 % in the investigated bands.

Numerical Study on the Thermal Insulation of Smart Windows Embedded with Low Thermal Conductivity Materials to Improve the Energy Efficiency of Buildings

The building industry accounts for almost 40% of the world's energy consumption. To reduce the global heat transfer coefficient, sustainable buildings should use highly insulated enclosures. As the building envelope serves as a barrier between the exterior and interior of the building, integration of passive solar design principles in its construction, such as smart windows with low thermal conductivity materials are essential. Smart windows may assist to reduce energy consumption by minimizing heat gain by the building, which able reduce the cooling loads while maintaining the thermal comfort for the building users. This study features smart double-glazed windows filled with low thermal conductive materials which are argon and aerogel to improve window insulation in pursuit of energy efficiency improvement. A numerical model is developed in ANSYS Workbench to evaluate thermal insulation performance of argon-filled and aerogel-filled windows by measuring the indoor surface temperature of the building at three critical times of the day. Newton's Law of Cooling is used to compute the empirical value of the heat transfer across the window to compare and validate the numerical data. This study shows that argon-filled and aerogel-filled window able to reduce the heat transfer across the building up 21% and 59% respectively. Aerogel is proven to resist more heat transfer as compared to argon

Analyses of non-aqueous reactive polymer insulation layer in high geothermal tunnel

The scenario of geothermal tunnel is commonly observed around the world, and increases with the new constructions in the long and deep tunnels, for example in China. Tunnel insulation is generally divided into active and passive insulation. In passive insulation, it is an effective way to set low thermal conductivity materials as the thermal insulation layer as the choice of insulation material mainly depends on the thermal conductivity. Polymer is a kind of material with good geothermal performance, but there are relatively few studies. In this context, the transient plane source (TPS) method was used to measure the thermal conductivity of the developed polymer. Then, the temperature field of the high geothermal tunnel insulated by the non-aqueous reactive polymer layer was simulated. With the parametric analysis results, the suggestions for the tunnel layers were proposed accordingly. It revealed that the thermal conductivity of polymer first increases and then decreases with temperature. There are two rising sections (-40–10 °C and 20–90 °C), one flat section (10–20 °C) and one descending section (>90 °C). It is observed the thermal conductivity of polymer increases with increase of the density of insulation layer and the density, and the thermal conductivity decreases when exposed to high temperatures. The temperature of the surrounding rocks increases with increase of the thermal conductivity and the thickness of polymer. Finally, a more economical thickness (5 cm) was proposed. Based on the parametric study, a thermal insulation layer with thermal conductivity less than 0.045 W/(m K), thickness of 5 cm and a density less than 0.12 g/cm 3 is suggested for practice. • The non-aqueous reactive polymer can be applied in high geothermal tunnel with good insulation performance. • The parameters (i.e., thermal conductivity, thickness and density) on the tunnel temperature field have been analyzed. • Reasonable parameters for polymer insulation layer in practice were suggested for tunnel engineering. • When the thermal conductivity is lower than 0.045 W/(m·K), the heat insulation effect is the most significant. • When thickness is about 5 cm, the polymer layer shows best heat insulation performance.

Low thermal conductivity substrate accelerates droplet evaporation in transition boiling regime: An abnormal Leidenfrost phenomenon

We investigate droplet evaporation on heater surface with different thermal conductivities. The complete droplet evaporation curves are obtained using the phase change lattice Boltzmann model, including four regimes of film evaporation, nucleate boiling, transition and Leidenfrost. Three thermal conductivities of substrate heater (λs) are paid attention. We found that higher λs does not always accelerate droplet evaporation. In the regimes excluding transition regime and Leidenfrost regime, higher λs increases droplet evaporation rate. However, in transition regime, lower λs enhances droplet evaporation, explained by that lower λs triggers second contact of droplet and heater and decreases vapor film thickness underneath droplet. Detailed droplet characteristic features including droplet spreading diameter, projected diameter of suspended drop, and vapor thickness in transition boiling regime are investigated in detail. The droplet oscillation in vertical direction during transition boiling for low thermal conductivity heater is found numerically for the first time. We conclude that low thermal conductivity material is benefit for heat transfer improvement due to the triggering of second contact (TSC) between droplet and solid surface.

Extremely strong four-phonon scattering and ultra-low lattice thermal conductivity due to quartic anharmonicity in fluoride perovskites XHgF3 (X = K, Rb)

Using high-throughput first-principles calculations, combined with self-consistent phonon theory and Boltzmann transport equations, the lattice thermal transport properties of fluoride perovskites XHgF3 (X = K, Rb) with strong anharmonicity are investigated. After considering the quartic anharmonic renormalization, the imaginary frequency in the phonon spectrum disappears and the low-lying modes soften, resulting in a low group velocity of the acoustic phonons. The strong quartic anharmonicity also causes extremely strong four-phonon scattering, which is even greater than three-phonon scattering in the low frequency phonon mode. The results show that the lattice thermal conductivity κL of XHgF3 (X = K, Rb) is ultra-low and the temperature dependence is unusually weak. The κL of KHgF3 at 300 K is only 0.18 Wm−1K−1, which is one-fifth of the classical low thermal conductivity material, quartz glass. Our study points the way to addressing the thermal transport properties of materials with strong anharmonicity and demonstrates that XHgF3 (X = K, Rb) can not only serve as a good thermal insulation material but also has potential applications in the thermoelectric field.

Coarse-grained simulation to study the thermal conductivity of crystalline polyethylene

<p indent="0mm">As one of the most used polymer material, polyethylene (PE) has excellent mechanical and processing properties. However, the low thermal conductivity limits the application of polyethylene in field of electronic devices, which needs good thermal conductivity for heat management. However, recent studies report excellent thermal conductivity for PE fibres. It should be very interesting to check if it is possible to convert PE from low thermal conductivity materials to high ones. In this study, in order to make a deep understand on thermal conductivity of PE material, a coarse-grained model of crystalline PE was constructed, and molecular dynamics simulation methods were used to explore the effect of crystallization on the intrinsic thermal conductivity of PE. First, Boltzmann inversion method was applied to build the coarse-grained model of PE, which is suitable to mimic physical behaviours of PE material with varied crystalline degrees. The simulation data such as the bond distribution function, angular distribution function, and radial distribution function of the coarse-grained model are found consistent with those from all-atom model. Furthermore, various physical data calculated from coarse-grained model are compared with those from reported experimental studies, such as glass transition temperature, thermal expansion coefficient, mean square radius of gyration, diffusion coefficient and thermal conductivity. All above physical data of coarse-grained model fit well with those from literatures. It means our coarse-grained model is readily to mimic PE materials, especially in field of thermal properties. For example, the curve of thermal conductivities of a single PE chain varied along with chain length calculated from our coarse-grained model lies between results from previous theoretic predictions. Second, the coarse-grained PE model with various crystalline degree and same crystalline degree of varied crystalline particles sizes are systematically investigated. We paid much attention on effect of stretching on thermal conductivity of PE models, because stretching is an efficient way to alter alignment state of PE chains. The results show that thermal conductivity of the PE model increases along with the increasing of crystalline degree. During stretching, the PE models with higher crystalline degree are easily reconfigured to align chains along the stretching direction, which is the thermal transporting direction, that in turn causes an obviously increasing for thermal conductivity. At the same crystalline degree, PE model with larger crystalline particle size is easier to form a high thermal conductivity system under stretching comparing with those with small crystalline particle sizes. Order parameters represent alignment of PE chains are calculated to analysize this observation. To conclude, the coarse-grained PE model established in this paper can be used to study the thermal conductivity of complex crystalline systems. The physical properties calculated from coarse-grained PE model are found to fit well with experimental and theoretic data of PE materials. Our simulation explores the dependence of thermal conductivity on crystalline state of PE material, and provides a theoretical basis for designing and manufacturing the intrinsic high thermal conductivity polymer materials. The coarse-grained model is thought to be able to explore mechanical properties of crystalline PE materials in the future.

Effect of yttria on thermal transport and vibrational modes in yttria-stabilized hafnia

Low thermal conductivity plays an essential role in application relevant to thermal energy conversion and management. In this paper, we utilize molecular dynamics to investigate the thermal transport and lattice variation modes in yttria-stabilized hafnia, which only contains binary oxides of Y2O3 and HfO2. It is found that the thermal conductivity κ of yttria-stabilized hafnia decreases significantly with the increase of doping ratio of Y2O3, and then reaches a limiting value (∼2.1 W m−1K−1), because of the strong phonon scattering of oxygen vacancies. Importantly, a glass-like thermal conductivity κ is achieved in yttria-stabilized hafnia samples when the content of Y2O3 exceeds 15 mol%. By decomposing the phonon vibrational modes, we find that most of the heat is transported by diffusive modes. As a result, the κ exhibits a glass-like feature in yttria-stabilized hafnia samples with high content of Y2O3. Notably, the κ of yttria-stabilized hafnia is much lower than those of classical functional ceramics materials. The insight into the κ in yttria-stabilized hafnia system is beneficial for understanding and reducing the κ of materials through defect engineering. Despite its simple composition, yttria-stabilized hafnia with different doping ratios demonstrates unexpected high scattering rate of phonon vibration density states, which is confirmed by the diffused wavevector-frequency dispersion. Eigenvector periodicity and phonon participation ratio of phonon have been visualized to capture the distribution of phonon modes in yttria-stabilized hafnia with various dopant. This work investigates into the details of phonon vibrational modes in yttria-stabilized hafnia, which would be valuable for conducting experiments to acquire low thermal conductivity materials in laboratory.