Physical Behavior and Sampling of Airborne Particles

2018 ◽  
pp. 7-26
Author(s):  
D. Hochrainer
Keyword(s):  
Airborne Particles ◽  
Physical Behavior

Identifying groups of airborne particles by ordination

1994 ◽  
Vol 52 ◽  
pp. 856-857
Author(s):  
M. Shlepr ◽  
C. M. Vicroy
Keyword(s):  
Elemental Analysis ◽  
Energy Dispersive Spectroscopy ◽  
Manufacturing Process ◽  
Spatial Representation ◽  
Airborne Particles ◽  
Common Source ◽  
Data Set ◽  
Microelectronics Industry ◽  
Induced Changes ◽  
Source Materials

The microelectronics industry is heavily tasked with minimizing contaminates at all steps of the manufacturing process. Particles are generated by physical and/or chemical fragmentation from a mothersource. The tools and macrovolumes of chemicals used for processing, the environment surrounding the process, and the circuits themselves are all potential particle sources. A first step in eliminating these contaminants is to identify their source. Elemental analysis of the particles often proves useful toward this goal, and energy dispersive spectroscopy (EDS) is a commonly used technique. However, the large variety of source materials and process induced changes in the particles often make it difficult to discern if the particles are from a common source.Ordination is commonly used in ecology to understand community relationships. This technique usespair-wise measures of similarity. Separation of the data set is based on discrimination functions. Theend product is a spatial representation of the data with the distance between points equaling the degree of dissimilarity.

RESEARCH: Dry Heat Processing of Single-Use Respirators and Surgical Masks

2020 ◽  
Vol 54 (6) ◽  
pp. 410-416
Author(s):  
Joyce M. Hansen ◽  
Scott Weiss ◽  
Terra A. Kremer ◽  
Myrelis Aguilar ◽  
Gerald McDonnell
Keyword(s):  
Microbial Contamination ◽  
Healthcare Providers ◽  
High Volume ◽  
Airborne Particles ◽  
Heat Processing ◽  
Protective Equipment ◽  
Healthcare Facilities ◽  
Dry Heat ◽  
Surgical Masks ◽  
Single Use

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2, has challenged healthcare providers in maintaining the supply of critical personal protective equipment, including single-use respirators and surgical masks. Single-use respirators and surgical masks can reduce risks from the inhalation of airborne particles and microbial contamination. The recent high-volume demand for single-use respirators and surgical masks has resulted in many healthcare facilities considering processing to address critical shortages. The dry heat process of 80°C (176°F) for two hours (120 min) has been confirmed to be an appropriate method for single-use respirator and surgical mask processing.

Nanomechanical Characterization in the FIB

2005 ◽  
Author(s):  
Thomas M. Moore
Keyword(s):  
Focused Ion Beam ◽  
Ion Beam ◽  
Materials Characterization ◽  
Depth Of Focus ◽  
Ion Milling ◽  
Nano Technology ◽  
Physical Behavior ◽  
Nanomechanical Testing ◽  
Load Cells ◽  
Scanning Electron

Abstract The availability of the focused ion beam (FIB) microscope with its excellent imaging resolution, depth of focus and ion milling capability has made it an appealing platform for materials characterization at the sub-micron, or "nano" level. This article focuses on nanomechanical characterization in the FIB, which is an extension of the FIB capabilities into the realm of nano-technology. It presents examples that demonstrate the power and flexibility of nanomechanical testing in the FIB or scanning electron microscope with a probe shaft that includes a built-in strain gauge. Loads that range from grams to micrograms are achievable. Calibration is limited only by the availability of calibrated load cells in the smallest load ranges. Deflections in the range of a few nanometers range can be accurately applied. Simultaneous electrical, mechanical, and visual data can be combined to provide a revealing study of physical behavior of complex and dynamic nanostructures.

LEARNING NAIVE PHYSICS BY VISUAL OBSERVATION: USING QUALITATIVE SPATIAL REPRESENTATIONS AND PROBABILISTIC REASONING

2001 ◽  
Vol 01 (03) ◽  
pp. 273-285 ◽  
Author(s):  
PAUL A. BOXER
Keyword(s):  
Bayesian Network ◽  
Probabilistic Reasoning ◽  
Autonomous Robots ◽  
Visual Observation ◽  
Spatial Representations ◽  
Physical Behavior ◽  
Naive Physics ◽  
Action At A Distance ◽  
General Physical ◽  
Test Scenarios

Autonomous robots are unsuccessful at operating in complex, unconstrained environments. They lack the ability to learn about the physical behavior of different objects through the use of vision. We combine Bayesian networks and qualitative spatial representation to learn general physical behavior by visual observation. We input training scenarios that allow the system to observe and learn normal physical behavior. The position and velocity of the visible objects are represented as qualitative states. Transitions between these states over time are entered as evidence into a Bayesian network. The network provides probabilities of future transitions to produce predictions of future physical behavior. We use test scenarios to determine how well the approach discriminates between normal and abnormal physical behavior and actively predicts future behavior. We examine the ability of the system to learn three naive physical concepts, "no action at a distance", "solidity" and "movement on continuous paths". We conclude that the combination of qualitative spatial representations and Bayesian network techniques is capable of learning these three rules of naive physics.

Human-Cell Mutagens in Respirable Airborne Particles in the Northeastern United States. 1. Mutagenicity of Fractionated Samples

2004 ◽  
Vol 38 (3) ◽  
pp. 682-689 ◽  
Author(s):  
Daniel U. Pedersen ◽  
John L. Durant ◽  
Bruce W. Penman ◽  
Charles L. Crespi ◽  
Harold F. Hemond ◽  
...  
Keyword(s):  
United States ◽  
Human Cell ◽  
Airborne Particles ◽  
Northeastern United States
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