Porosity, Specific Surface Area and Effective Thermal Conductivity of Anisotropic Open Cell Lattice Structures

2005 ◽  
Author(s):  
Kiran Balantrapu ◽  
Deepti Rao Sarde ◽  
Christopher M. Herald ◽  
Richard A. Wirtz
Keyword(s):  
Thermal Conductivity ◽  
Specific Surface ◽  
Effective Thermal Conductivity ◽  
Surface Area ◽  
Specific Surface Area ◽  
Structural Characteristics ◽  
Analytical Models ◽  
Lattice Structures ◽  
Open Cell ◽  
Thermally Conductive

Open-cell box-lattice structures consisting of mutually orthogonal thermally conductive cylindrical ligaments can be configured to have wide ranging porosity, a large specific surface area and effective thermal conductivity in a particular direction together with specified structural characteristics. Thermal and mechanical properties can be tuned (and anisotropy introduced) by specification of different filament diameter and pitch for the vertical and horizontal filaments. Analytical models for porosity, specific surface area and effective thermal conductivity of lattice structures having different ligament diameters and pitches (anisotropy) are developed. The models show that all three of these quantities are functions of three dimensionless lengths.   This paper was also originally published as part of the Proceedings of the ASME 2005 Heat Transfer Summer Conference.

In-Plane Effective Thermal Conductivity of Symmetric, Diamond-Weave Screen Laminates

2004 ◽  
Vol 127 (3) ◽  
pp. 353-356 ◽  
Author(s):  
Jun Xu ◽  
Richard A. Wirtz
Keyword(s):  
Thermal Conductivity ◽  
Specific Surface ◽  
Effective Thermal Conductivity ◽  
Surface Area ◽  
Specific Surface Area ◽  
Laboratory Experiments ◽  
Two Dimensional ◽  
Algebraic Models ◽  
Metal Fractions

Algebraic models of porosity, specific surface area, and in-plane effective thermal conductivity for stacked, two-dimensional symmetric diamond-weave screen laminations are developed and benchmarked with laboratory experiments. Diamond-weave laminations are found to have greater metal fractions and specific surface area than equivalent orthogonal-weaves. With the weave angle smaller than 90°, the structure also has a much higher effective thermal conductivity.

scholarly journals Nanocomposite Materials Based on Electrochemically Synthesized Graphene Polymers: Molecular Architecture Strategies for Sensor Applications

Chemosensors ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 149
Author(s):  
André Olean-Oliveira ◽  
Gilberto A. Oliveira Brito ◽  
Celso Xavier Cardoso ◽  
Marcos F. S. Teixeira
Keyword(s):  
Conducting Polymers ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Electrochemical Sensors ◽  
Structural Characteristics ◽  
Low Cost ◽  
Large Specific Surface Area ◽  
Molecular Architecture ◽  
Sensor Applications

The use of graphene and its derivatives in the development of electrochemical sensors has been growing in recent decades. Part of this success is due to the excellent characteristics of such materials, such as good electrical and mechanical properties and a large specific surface area. The formation of composites and nanocomposites with these two materials leads to better sensing performance compared to pure graphene and conductive polymers. The increased large specific surface area of the nanocomposites and the synergistic effect between graphene and conducting polymers is responsible for this interesting result. The most widely used methodologies for the synthesis of these materials are still based on chemical routes. However, electrochemical routes have emerged and are gaining space, affording advantages such as low cost and the promising possibility of modulation of the structural characteristics of composites. As a result, application in sensor devices can lead to increased sensitivity and decreased analysis cost. Thus, this review presents the main aspects for the construction of nanomaterials based on graphene oxide and conducting polymers, as well as the recent efforts made to apply this methodology in the development of sensors and biosensors.

scholarly journals Structure, specific surface area and thermal conductivity of the snowpack around Barrow, Alaska

2012 ◽  
Vol 117 (D14) ◽  
pp. n/a-n/a ◽  
Author(s):  
Florent Domine ◽  
Jean-Charles Gallet ◽  
Josué Bock ◽  
Samuel Morin
Keyword(s):  
Thermal Conductivity ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area

scholarly journals 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy

2012 ◽  
Vol 6 (5) ◽  
pp. 939-951 ◽  
Author(s):  
N. Calonne ◽  
C. Geindreau ◽  
F. Flin ◽  
S. Morin ◽  
B. Lesaffre ◽  
...  
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Three Dimensional ◽  
Analytical Models ◽  
Simple Relationship ◽  
Snow Density ◽  
Average Value ◽  
Wide Range ◽  
Snow Samples

Abstract. We used three-dimensional (3-D) images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K). This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. For several snow samples, a significant anisotropy of permeability was detected and is consistent with that observed for the effective thermal conductivity obtained from the same samples. The anisotropy coefficient, defined as the ratio of the vertical over the horizontal components of K, ranges from 0.74 for a sample of decomposing precipitation particles collected in the field to 1.66 for a depth hoar specimen. Because the permeability is related to a characteristic length, we introduced a dimensionless tensor K*=K/res2, where the equivalent sphere radius of ice grains (res) is computed from the specific surface area of snow (SSA) and the ice density (ρi) as follows: res=3/(SSA×ρi. We define K and K* as the average of the diagonal components of K and K*, respectively. The 35 values of K* were fitted to snow density (ρs) and provide the following regression: K = (3.0 ± 0.3) res2 exp((−0.0130 ± 0.0003)ρs). We noted that the anisotropy of permeability does not affect significantly the proposed equation. This regression curve was applied to several independent datasets from the literature and compared to other existing regression curves or analytical models. The results show that it is probably the best currently available simple relationship linking the average value of permeability, K, to snow density and specific surface area.

scholarly journals Effect of the electrolysis regime on the structural characteristics of honeycomb-like electrodes

2013 ◽  
Vol 32 (1) ◽  
pp. 79
Author(s):  
Nebojsa D. Nikolic ◽  
Goran Branković ◽  
Miomir G. Pavlović
Keyword(s):  
Surface Morphology ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Structural Characteristics ◽  
Hole Size ◽  
Porous Structures ◽  
Wall Width ◽  
Copper Electrodes ◽  
Hydrogen Bubbles

The effect of different current regimes of electrolysis on the micro- and nanostructural characteristics of open porous structures was examined by the analysis of honeycomb-like copper electrodes obtained by constant galvanostatic (DC) electrodeposition and by regimes of pulsating (PC) and reversing (RC) current. An increase in the number of holes formed by detached hydrogen bubbles, the decrease in wall width between holes and changes in surface morphology around holes from cauliflower-like agglomerates of copper grains to dendrites were observed in the following order: the DC, PC and RC regime. The hole size formed in the RC regime was smaller than the hole size formed in the DC and PC regimes. Analysis of the obtained structural characteristics showed that the specific surface area of the honeycomb-like electrodes was increased by the application of the PC and RC regimes in relation to the DC regime.

scholarly journals Thermal conductivity of polyvinylpolymethylsiloxane aerogels with high specific surface area

RSC Advances ◽  
2019 ◽  
Vol 9 (14) ◽  
pp. 7833-7841 ◽  
Author(s):  
Lukai Wang ◽  
Junzong Feng ◽  
Yonggang Jiang ◽  
Liangjun Li ◽  
Jian Feng
Keyword(s):  
Mechanical Properties ◽  
Thermal Conductivity ◽  
Energy Storage ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Heat Insulation ◽  
High Specific Surface Area

The traditional SiO2 aerogels are difficult to apply in the fields of energy storage and heat insulation due to their poor mechanical properties.

scholarly journals 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy

2012 ◽  
Vol 6 (2) ◽  
pp. 1157-1180 ◽  
Author(s):  
N. Calonne ◽  
C. Geindreau ◽  
F. Flin ◽  
S. Morin ◽  
B. Lesaffre ◽  
...  
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Three Dimensional ◽  
Analytical Models ◽  
Wide Range ◽  
Sphere Radius ◽  
Snow Microstructure ◽  
Microstructural Anisotropy ◽  
Good Agreement

Abstract. We used three-dimensional (3-D) images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K). This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. Because the permeability is related to a characteristic length, we introduced a dimensionless tensor K*=K/ res2, where the equivalent sphere radius of ice grains (res) is computed from the specific surface area of snow (SSA) and the ice density (ρi) as follows: res=3/(SSA x ρi). Values of K*, the average of vertical and horizontal components of K*, were plotted vs. snow density (ρs) and compared to analytical models and data from the literature, showing generally a good agreement. The 35 values of K* were fitted to ρs and provide the following regression: K*=2.94 x exp(–0.013 ρs), with a correlation coefficient of 0.985. This indicates that permeability, if assumed isotropic, can be reasonably determined from SSA and ρs, which are both easily measurable in the field. However, the anisotropy coefficient of K, induced by the snow microstructure, ranges from 0.74 to 1.66 for the samples considered. This behavior is consistent with that of the effective thermal conductivity obtained in a previous work.

scholarly journals Meteorological, snow and soil data (2013–2019) from a herb tundra permafrost site at Bylot Island, Canadian high Arctic, for driving and testing snow and land surface models

2021 ◽  
Author(s):  
Florent Domine ◽  
Georg Lackner ◽  
Denis Sarrazin ◽  
Mathilde Poirier ◽  
Maria Belke-Brea
Keyword(s):  
Thermal Conductivity ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
High Arctic ◽  
Specific Humidity ◽  
The Arctic ◽  
Canadian High Arctic ◽  
Validation Data ◽  
Bylot Island

Abstract. Seasonal snow covers Arctic lands 6 to 10 months of the year and is therefore an essential element of the Arctic geosphere and biosphere. Yet, even the most sophisticated snow physics models are not able to simulate fundamental physical properties of Arctic snowpacks such as density, thermal conductivity and specific surface area. The development of improved snow models is in progress but testing requires detailed driving and validation data for high Arctic herb tundra sites, which are presently not available. We present 6 years of such data for an ice-wedge polygonal site in the Canadian high Arctic, in Qarlikturvik valley on Bylot Island at 73.15 °N. The site is on herb tundra with no erect vegetation and thick permafrost. Detailed soil properties are provided. Driving data are comprised of air temperature, air relative and specific humidity, wind speed, short wave and long wave downwelling radiation, atmospheric pressure and precipitation. Validation data include time series of snow depth, shortwave upwelling radiation, surface temperature, snow temperature profiles, soil temperature and water content profiles at five depths, snow thermal conductivity at three heights and soil thermal conductivity at 10 cm depth. Field campaigns in mid-May for 5 of the 6 years of interest provided spatially-averaged snow depths and vertical profiles of snow density and specific surface area in the polygon of interest and at other spots in the valley. Data are available at https://doi.org/10.5885/45693CE-02685A5200DD4C38 (Domine et al., 2021). Data files will be updated as more years of data become available.

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