Characterization of In- and Near-Body Radio Frequency Transmission Loss for Biomedical Implants

2013 ◽  
Vol 3 (1) ◽  
pp. 112-119 ◽  
Author(s):  
Xianming Qing ◽  
Terence Shie Ping See ◽  
Zhi Ning Chen ◽  
Tat Meng Chiam ◽  
. Nasimuddin ◽  
...  
Author(s):  
Amy Poe ◽  
Steve Brockett ◽  
Tony Rubalcava

Abstract The intent of this work is to demonstrate the importance of charged device model (CDM) ESD testing and characterization by presenting a case study of a situation in which CDM testing proved invaluable in establishing the reliability of a GaAs radio frequency integrated circuit (RFIC). The problem originated when a sample of passing devices was retested to the final production test. Nine of the 200 sampled devices failed the retest, thus placing the reliability of all of the devices in question. The subsequent failure analysis indicated that the devices failed due to a short on one of two capacitors, bringing into question the reliability of the dielectric. Previous ESD characterization of the part had shown that a certain resistor was likely to fail at thresholds well below the level at which any capacitors were damaged. This paper will discuss the failure analysis techniques which were used and the testing performed to verify the failures were actually due to ESD, and not caused by weak capacitors.


2021 ◽  
pp. 004051752110238
Author(s):  
Oluwafemi P Akinmolayan ◽  
James M Manimala

Silica nanoparticle-impregnated Kevlar (SNK) fabric has better specific ballistic performance in comparison to its neat counterparts. For multifunctional structural applications using lightweight composites, combining this improved ballistic functionality with an acoustic functionality is desirable. In this study, acoustic characterization of neat and SNK samples is conducted using the normal-incidence impedance tube method. Both the absorption coefficient and transmission loss (TL) are measured in the 60–6000 Hz frequency range. The influence of parameters such as number of layers of neat or treated fabric, percentage by weight of nanoparticle addition, spacing between fabric layers, and residual porosity is examined. It is found that while absorption decreases with an increase in nanoparticle addition for frequencies above about 2500 Hz, increasing the number of layers shifts peak absorption to lower frequencies. By introducing an air-gap behind the fabric layer, dominant low-frequency (1000–3000 Hz) absorption peaks are obtained that correlate well with natural modes of mass-equivalent thin plates. Examining the influence of residual porosity by laminating the SNK samples reveals that it contributes to about 30–50% of the total absorption. Above about 1500 Hz, 3–5 dB of TL increase is obtained for SNK samples vis-à-vis the neat samples. TL is found to increase beyond that of the neat sample above a threshold frequency when an air-gap is introduced between two SNK layers. With an increase in the weight of nanoparticle addition, measured TL tends to be closer to mass law predictions. This study demonstrates that SNK fabric could provide improved acoustic performance in addition to its ballistic capabilities, making it suitable for multifunctional applications and could form the basis for the development of simplified models to predict the structural acoustic response of such nanoparticle–fabric composites.


2002 ◽  
Vol 92 (1) ◽  
pp. 310-319 ◽  
Author(s):  
David L. Young ◽  
Helio Moutinho ◽  
Yanfa Yan ◽  
Timothy J. Coutts

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
L. H. Gonsioroski ◽  
L. da Silva Mello

This paper presents the results of measurements of signal transmission loss at 2.5 GHz through 10 urban buildings. This allows the characterization of different types of buildings by effective attenuation constants and consideration of the contribution of the transmitted signal in microcell coverage predictions. Power delay profiles (PDPs) of the received signal were also measured and used to determine the time dispersion parameters of the channel, including the mean excess delay and the rms delay spread.


Sign in / Sign up

Export Citation Format

Share Document