<br /><br />TÉCNICAS  DE  ANÁLISE  ESPACIAL  APLICADAS À CARACTERIZAÇÃO DA POPULAÇÃO IDOSA PARA PLANEAR CUIDADOS DE ENFERMAGEM<br /> SPATIAL  ANALYSIS  TECHNIQUES  APPLIED  TO  THE CHARACTERIZATION OF ELDERLY POPULATION FOR THE PLANNING OF NURSING CARE<br

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.

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Characterization of Unfilled Tungsten Plugs on a 0.35μm CMOS Multilevel Metallization Process

ISTFA 1996: Conference Proceedings from the 22nd International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa1996p0141 ◽

1996 ◽

Author(s):

H. Sur ◽

S. Bothra ◽

Y. Strunk ◽

J. Hahn

Keyword(s):

Process Development ◽

Process Integration ◽

Wafer Level ◽

Electrical Failure ◽

Analysis Techniques ◽

Integration Approach ◽

Intermetal Dielectric ◽

Metallization Process ◽

Section Analysis

Abstract An investigation into metallization/interconnect failures during the process development phase of an advanced 0.35μm CMOS ASIC process is presented. The corresponding electrical failure signature was electrical shorting on SRAM test arrays and subsequently functional/Iddq failures on product-like test vehicles. Advanced wafer-level failure analysis techniques and equipment were used to isolate and identify the leakage source as shorting of metal lines due to tungsten (W) residue which was originating from unfilled vias. Further cross-section analysis revealed that the failing vias were all exposed to the intermetal dielectric spin-on glass (SOG) material used for filling the narrow spaces between metal lines. The outgassing of the SOG in the exposed regions of the via prior to and during the tungsten plug deposition is believed to be the cause of the unfilled vias. This analysis facilitated further process development in eliminating the failure mechanism and since then no failures of this nature have been observed. The process integration approach used to eliminate the failure is discussed.

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Connectivity characterization of the mouse basolateral amygdalar complex

Nature Communications ◽

10.1038/s41467-021-22915-5 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Houri Hintiryan ◽

Ian Bowman ◽

David L. Johnson ◽

Laura Korobkova ◽

Muye Zhu ◽

...

Keyword(s):

Granular Cell ◽

Cell Types ◽

Projection Neurons ◽

Cell Type ◽

Connectivity Map ◽

Analysis Techniques ◽

Domain Specific ◽

Cell Type Specific ◽

Unique Domain

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

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