Development and analysis of the Soil Water Infiltration Global database.

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (~76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type (~40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it

3D computational fluid dynamics simulation of carbon nanotube based microchannel on-chip cooler

Cooling of microsystem electronic device is of great importance, according to increased heat dissipation based on Moore\u27s law. Different solutions are proposed to overcome this issue. On-chip microchannel cooler implements micro-fabrication techniques to achieve large areas in small volume size by introducing micro channel CNT fins with smaller fin pitch. In this paper, a 3D model of this structure is simulated using computational fluid dynamics (CFD) in ANSYS\uae software, and effect of various parameters such as channel width and height is discussed to achieve an optimized cooling for this system

3D computational fluid dynamics simulation of carbon nanotube based microchannel on-chip cooler

Cooling of microsystem electronic device is of great importance, according to increased heat dissipation based on Moore\u27s law. Different solutions are proposed to overcome this issue. On-chip microchannel cooler implements micro-fabrication techniques to achieve large areas in small volume size by introducing micro channel CNT fins with smaller fin pitch. In this paper, a 3D model of this structure is simulated using computational fluid dynamics (CFD) in ANSYS\uae software, and effect of various parameters such as channel width and height is discussed to achieve an optimized cooling for this system

A complete carbon-nanotube-based on-chip cooling solution with very high heat dissipation capacity

Heat dissipation is one of the factors limiting the continuous miniaturization of electronics. In the study presented in this paper, we designed an ultra-thin heat sink using carbon nanotubes (CNTs) as micro cooling fins attached directly onto a chip. A metal-enhanced CNT transfer technique was utilized to improve the interface between the CNTs and the chip surface by minimizing the thermal contact resistance and promoting the mechanical strength of the microfins. In order to optimize the geometrical design of the CNT microfin structure, multi-scale modeling was performed. A molecular dynamics simulation (MDS) was carried out to investigate the interaction between water and CNTs at the nanoscale and a finite element method (FEM) modeling was executed to analyze the fluid field and temperature distribution at the macroscale. Experimental results show that water is much more efficient than air as a cooling medium due to its three orders-of-magnitude higher heat capacity. For a hotspot with a high power density of 5000 W cm(-2), the CNT microfins can cool down its temperature by more than 40 degrees C. The large heat dissipation capacity could make this cooling solution meet the thermal management requirement of the hottest electronic systems up to date

Microstructure and Mechanical Reliability Issues of TSV

The copper pumping problem exemplifies the complex reliability issues still to be resolved for TSV structures. From a materials science perspective the reliability issues presented by TSVs are linked to manufacturing processes and the resultant microstructure formed. Routine finite-element based reliability studies that treat the TSV filler as an isotropic and homogeneous material are not capable of providing a sufficiently thorough explanation of the observed copper extrusion/intrusion behavior. Rather, the material behavior and properties at multiple scales are required as the input data for effective reliability analysis of three- dimensional TSV stacked ICs. Such 3-D ICs also push the scale of materials to a limit where the anisotropy of material properties, recovery, recrystallization and time-dependent phase morphological evolution further complicate reliability issues. This chapter reviews both experimental and modeling approaches that address the microstructural and reliability issues of TSVs. Crystal plasticity based finite element analysis (FEA) and phase field crystal method with an inherently multiscale nature are identified as promising modeling techniques to enable atomistically-informed reliability analysis of TSVs