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Research Papers

Identification and Characterization of Particulate Contaminants Found at a Data Center Using Airside Economization

[+] Author and Article Information
Jimil M. Shah

Department of Mechanical and
Aerospace Engineering,
University of Texas at Arlington,
Arlington, TX 76019
e-mail: jimil.shah@mavs.uta.edu

Abel Misrak, Dereje Agonafer

Department of Mechanical and
Aerospace Engineering,
University of Texas at Arlington,
Arlington, TX 76019

Mike Kaler

Mestex,
A Division of Mestek, Inc.,
4830 Transport Drive,
Dallas, TX 75247

1Corresponding author.

Contributed by the Electronic and Photonic Packaging Division of ASME for publication in the JOURNAL OF ELECTRONIC PACKAGING. Manuscript received November 1, 2018; final manuscript received March 14, 2019; published online May 8, 2019. Assoc. Editor: Wei Li.

J. Electron. Packag 141(3), 031003 (May 08, 2019) (10 pages) Paper No: EP-18-1103; doi: 10.1115/1.4043481 History: Received November 01, 2018; Revised March 14, 2019

Contamination due to the use of airside economizer has become a major issue that cost companies revenue. This issue will continue to rise as server components become smaller, densely packed, and as companies move into more polluted environments. Contaminants with small particles less than 10 μm are not noticeable; yet, these particles are most likely to get to areas where they can cause damage. Dust from different sources and suspended in air settles on surfaces of electrical components. The dust mainly contains two components: salts and metallic particles. The salts may be neutral or corrosive and the nature of the salt depends on the deliquescent humidity. For metallic particles, surveys are performed in various data centers in order to determine the limits in terms of weight per unit area and particle size distribution. It is necessary to first identify those contaminants that directly affect the information technology (IT) equipment in the data center. In this research, a real-world data center utilizing airside economization in an ANSI/ISA classified G2 environment was chosen for the study. Servers were removed and qualitative study of cumulative corrosion damage was carried out. The particulate contaminants were collected from different locations of a server and material characterization was performed using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), and Fourier transform infrared spectroscopy (FTIR). The analysis from these results helps to explain the impact of the contaminants on IT equipment reliability.

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References

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Figures

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Fig. 1

Airflow Pattern inside the IT pod

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Fig. 2

Psychrometric chart regions based on A1 allowable region

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Fig. 3

Lodged dust at the different locations of the test server

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Fig. 4

Hitachi S-3000N variable pressure SEM with a thermionic source (W gun)

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Fig. 5

Hitachi S-4800 II FE SEM with cold field emission source

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Fig. 6

CrC 100 sputtering system used for coating the nonconductive samples with silver

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Fig. 7

Sample holder with the silver-coated sample

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Fig. 8

Thermo Nicolet 6700 FTIR spectrometer

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Fig. 9

(a) Back Scatter images in COMPO mode at ×10k and (b) SE images ×500

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Fig. 10

(a) SE images at ×8k (left) and ×20k (right) at 11.2 mm working distance (WD), (b) SE images at ×200k (left) and ×220k (right) at 11.2 mm WD, (c) SE images at ×200k (left) and ×350k (right) at 5 mm WD, and (d) SE image at ×500k at 5 mm WD

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Fig. 11

The size of the different contaminants measured using analysis tool on matlab

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Fig. 12

(a) Result obtained from the spectral analysis showing the location of the various elements identified in one location of the sample, (b) result of the spectrum analysis of one location of the sample, and (c) result of quantitative analysis of one location of the sample

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Fig. 13

Average weight of elements identified in the contaminant sample in percentage

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Fig. 14

(a) Absorbance data collected using FTIR, (b) transmission data collected using FTIR, and (c) result obtained after performing the search in the FTIR database

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