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This paper will discuss the adverse effects of deficient cleanroom design practices on airborne particle counts and the rather curious correlation of particle count variations with external environmental pressure fluctuations. Data is also presented that demonstrates that APL building 23 cleanrooms ran well below ISO class 7 (FED class 10,000) during New Horizons and STEREO integration.
An ideal seeding device is proposed generating particles that exactly follow the flow out are still a major source of error, i.e., with a particle counting bias wherein the probability of measuring velocity is a function of velocity. The error in the measured mean can be as much as 25%. Many schemes have been put forward to correct for this error, but there is not universal agreement as to the acceptability of any one method. In particular it is sometimes difficult to know if the assumptions required in the analysis are fulfilled by any particular flow measurement system. To check various correction mechanisms in an ideal way and to gain some insight into how to correct with the fewest initial assumptions, a computer simulation is constructed to simulate laser anemometer measurements in a turbulent flow. That simulator and the results of its use are discussed.
The ER-2 condensation nuclei counter (CNC) has been modified to reduce the diffusive losses of particles within the instrument. These changes have been successful in improving the counting efficiency of small particles at low pressures. Two techniques for measuring the size distributions of particles with diameters less than 0.17 micrometers have been evaluated. Both of these methods, the differential mobility analyzer (DMA) and the diffusion battery, have fundamental problems that limit their usefulness for stratospheric applications. We cannot recommend either for this application. Newly developed, alternative methods for measuring small particles include inertial separation with a low-loss critical orifice and thin-plate impactor device. This technique is now used to collect particles in the multisample aerosol collector housed in the ER-2 CNC-2, and shows some promise for particle size measurements when coupled with a CNC as a counting device. The modified focused-cavity aerosol spectrometer (FCAS) can determine the size distribution of particles with ambient diameters as small as about 0.07 micrometers. Data from this instrument indicates the presence of a nuclei mode when CNC-2 indicates high concentrations of particles, but cannot resolve important parameters of the distribution.
There were two principal objectives of the cooperative agreement between NASA and the University of Denver. The first goal was to modify the design of the ER-2 condensation nuclei counter (CNC) so that the effective lower detection limit would be improved at high altitudes. This improvement was sought because, in the instrument used prior to 1993, diffusion losses prevented the smallest detectable particles from reaching the detection volume of the instrument during operation at low pressure. Therefore, in spite of the sensor's ability to detect particles as small as 0.008 microns in diameter, many of these particles were lost in transport to the sensing region and were not counted. Most of the particles emitted by aircraft are smaller than 0.1 micron in diameter. At the start date of this work, May 1990, continuous sizing techniques available on the ER-2 were only capable of detecting particles larger than 0.17 micron. Thus, the second objective of this work was to evaluate candidate sizing techniques in an effort to gain additional information concerning the size of particles emitted by aircraft.
Microscope-stage holder keeps filter pad flat to keep it in focus. Specimen holder is special vacuum chuck that applies suction through flat screen. Suction keeps filter pad flat against specimen holder while microscope stage moving to scan areas denoted by grid. In microscope system equipped with video camera, image-analyzing/particle-counting computer, and automatic focus, use of stage speeds count considerably by eliminating need to stop frequently for manual refocusing. Technician free to perform other tasks while computer controls translation of stage and takes count automatically.
OSIRIS-REx is an asteroid sample return mission that delivered asteroid regolith from Bennu to Earth on 9/24/2023 [1]. Cleanroom monitoring of OSIRIS-REx Curation facilities has been ongoing since 2021 when construction of the OSIRIS-REx lab at Johnson Space Center (JSC) was completed [2]. The monitoring continues inside of the OSIRIS-REx lab in Houston. Monitoring was also conducted on a temporary cleanroom constructed inside a hangar at the Utah Test and Training Range (UTTR) to initially receive the Sample Return Capsule (SRC) upon its landing there. The following reports on cleanroom monitoring that has taken place in the months leading up to as well as after OSIRIS-REx return. Monitoring techniques used include particle counts, deployment of Si wafer witness plates (Balazs, Inc.) and Al foil witness plates, gas sampling (Balazs, Inc.) and microbiological monitoring. We collected particle counts at both the lab at JSC as well as the temporary cleanroom at UTTR. Particle counts were taken monthly from six locations in the lab at JSC. Particle counts were taken from seven locations at UTTR in July, August, and September. The UTTR cleanroom particle counts were taken daily in the five days leading to OSIRIS-REx return as well as consistently the day of return (every 2 minutes and 15 seconds 7:21 am- 6:27 pm) from one location inside the cleanroom. The particle counts at UTTR consistently stayed well within the ranges of its required ISO 7 equivalent classification (352,000 maximum particles/ m3 ≥ 0.5 μm). Most analysis showed that the particle counts were far below ISO 7 requirements (highest measured count was 61,484 particles/ m3 ≥ 0.5 um). but the elevated instances correlated to exterior hangar doors being open. Particle counts were reduced when keeping exterior hangar doors closed. The particle counts at JSC have stayed consistently within their ISO 5 equivalent classification (3,520 maximum particles/ m3 ≥ 0.5 um). In most instances, the counts are much better except in one instance where the count measured 13,381 particles/ m3 ≥ 0.5 um. The high spike in particle counts in the JSC lab correlated with the air handlers being shut down temporarily the previous day. The particle counts taken in the same location quickly reduced and measured 0 when taken a month later with the air handlers on. We deployed 8-inch semiconductor polished Si wafer witness plates for 24-hour periods inside of the OSIRIS-REx Curation lab at JSC (in July, August, September, and November 2023) and the cleanroom at UTTR (July and September 2023) to test for possible organic and inorganic contaminants. We also deployed these wafers inside of the OSIRIS-REx Touch-and-Go sample Acquisition Mechanism (TAGSAM) glovebox (where Bennu sample processing occurs) and desiccator (Bennu sample storage) at JSC in August 2023. These samples were all sent to Balazs for analysis via Thermal Desorption Gas Chromatography Mass Spectroscopy (TD-GC-MS) to quantify organic compounds and vapor phase decomposition inductively coupled plasma mass spectrometry (VPD-ICP-MS) to quantify inorganic contaminants. We collected air samples using an adsorbent tube connected to a pump for six hours (100 mL/minute) inside of both the JSC lab and the UTTR cleanroom. These samples were taken at JSC in July, August, September, November, and December and at UTTR in July and September. Additionally, a sample was taken just outside of the TAGSAM glovebox airlock door in July. These samples were sent to Balazs for analysis of volatile organics in air. Overall, the OSIRIS-REx lab at JSC and cleanroom at UTTR yielded very low organic and inorganic contaminants (similar results to Genesis lab at JSC which is ISO 4 equivalent) except for boron, which is attributed to the borosilicate glass in the fan filter units. We collected monthly surface and air samples inside the JSC lab to monitor potential microbial contamination. We report the recovery rate for each sampling event, which is defined as the number of samples exhibiting bacterial or fungal growth divided by the total number of samples collected. Since the lab was commissioned in 2021 the median recovery rate is 29%. This recovery rate is consistent with other ISO 5 equivalent labs used to curate astromaterials collections. Increases in recovery rate correspond to construction and/or extra activity in the lab. However, increases in recovery rate do not reliably correlate to increases in particle counts, which highlights the need for a dedicated microbial monitoring program for biologically sensitive collections. We sampled the temporary clean room at UTTR in July, August, and September of 2023 to monitor potential microbial contamination. The recovery rate decreased from 80% in August to 29% in September. However, in all instances, the diversity of bacteria and fungi was higher in the UTTR cleanroom than in the JSC lab. We routinely collected more than twenty different organisms from the UTTR cleanroom. In the JSC lab the median diversity is 2 organisms. Based on these results we hypothesize that microbes from UTTR could be transported back to JSC with the Bennu samples. To mitigate this risk, in September of 2023, we implemented additional cleaning procedures in the JSC lab to reduce the bioburden on surfaces that could come into direct contact with hardware used to process Bennu samples. Since adopting these additional cleaning measures, the median recovery rate has decreased to 14%. We did not observe an increase in fungal or bacterial diversity in the lab in the October sampling. We will continue to monitor this trend closely for the next several months. Supported by NASA under Award NNH09ZDA007O and Contract NNM10AA11C.
Table S1, putative gene knockout targets in P. putida KT2440 to enhance vesiculation; Table S2, protein sequence identity of OmpA from E. coli K12 to P. putida KT2440 genes; Table S3, strains utilized in this study and corresponding construction details; Table S4, oligonucleotides utilized in this study; Table S5, plasmids utilized in this study; Table S6, sequences for mNeonGreen, tags, and codon-optimized genes; Figure S1, particle count per gCDW for KT2440 and knockout strains corresponding to data presented in Figure 1B; Figure S2, OD600 measurements of extracted MVs from KT2440 and knockout strains; Figure S3, particle count per gCDW for WT, ΔPP_4669, and ΔPP_1502; Figure S4, particle count per gCDW for KT2440 and knockout strains corresponding to data presented in Figure 3C; Figure S5, sizes of MVs corresponding to particle counts in Figure S4; Figure S6, particle count per gCDW for KT2440 grown on 20 mM glucose alone or 20 mM glucose plus 12.5 mM p-coumarate and 12.5 mM ferulate; Figure S7 and Figure S8, principal component analysis of the cellular fractions; Figure S9, heatmap of outer membrane proteins with differential abundance; and Figure S10, mNeonGreen (mNG) fluorescence signal for the cellular fraction and the extracellular fraction
A data base describing the properties of the exhaust cloud produced by the launch of the STS has been developed based on data from a series of ground and aircraft based measurements made during the launches of STS 2, 3, and 4. Aircraft observations were performed during the STS-3 launch with a NOAA WP-3D Orion hurricane research aircraft which contained instrumentation for cloud condensation nucleus and ice nucleus counting, Aitken particle counting, and pH determination. Ground observations were conducted at 50 different sites, as well as in the direct exhaust from the solid rocket booster flame trench at all three launches. The data is analyzed in order to determine any possible adverse impacts of the exhaust products on human health and/or the environment. Analyses of the exhaust cloud measurements indicate that in the case of the ground cloud where plenty of large water drops are present and considerable scavenging and fallout of aerosol takes place, possible adverse impacts of the remaining aerosols (CCN and IN) on natural precipitation processes which may occur in the launch area hours after the launch are remote. However, it is determined that under certain atmospheric conditions there could be short term adverse effects on visibility.
A machine vision system, similar to systems used in microbiological laboratories to count cultured microbes, has been proposed for quantifying the cleanliness of nominally precisely cleaned hardware by counting residual contaminant particles. The system would include a microscope equipped with an electronic camera and circuitry to digitize the camera output, a personal computer programmed with machine-vision and interface software, and digital storage media. A filter pad, through which had been aspirated solvent from rinsing the hardware in question, would be placed on the microscope stage. A high-resolution image of the filter pad would be recorded. The computer would analyze the image and present a histogram of sizes of particles on the filter. On the basis of the histogram and a measure of the desired level of cleanliness, the hardware would be accepted or rejected. If the hardware were accepted, the image would be saved, along with other information, as a quality record. If the hardware were rejected, the histogram and ancillary information would be recorded for analysis of trends. The software would perceive particles that are too large or too numerous to meet a specified particle-distribution profile. Anomalous particles or fibrous material would be flagged for inspection.
Computer image processing techniques have been applied to particle counting and sizing in electron microscope images. Distributions of particle sizes were computed for several images and compared to manually computed distributions. The results of these experiments indicate that automatic particle counting within a reasonable error and computer processing time is feasible. The significance of the results is that the tedious task of manually counting a large number of particles can be eliminated while still providing the scientist with accurate results.
During KOSI (comet simulation) experiments, mineral-ice mixtures are observed in simulated space conditions. Emission of ice-/dust particles from the sample surface is observed by means of different devices. The particle trajectories are recorded with a video system. In the following analysis we extracted the parameters: particle count rate, spatial distribution of starting points on the sample surface, and elevation angle and particle velocity at distances up to 5 cm from the sample surface. Different kinds of detectors are mounted on a frame in front of the sample to register the emitted particles and to collect their dust residues. By means of these instruments the particle count rates, the particle sizes and the composition of the particles can be correlated. The results are related to the gas flux density and the temperature on the sample surface during the insolation period. The particle emission is interpreted in terms of phenomena on the sample surface, e.g., formation of a dust mantle.
This paper describes particle evolution measurements taken in the Particulate Aerosol Laboratory (PAL). The PAL consists of a burner capable of burning jet fuel that exhausts into an altitude chamber that can simulate temperature and pressure conditions up to 13,700 m. After presenting results from initial temperature distributions inside the chamber, particle count data measured in the altitude chamber are shown. Initial particle count data show that the sampling system can have a significant effect on the measured particle distribution: both the value of particle number concentration and the shape of the radial distribution of the particle number concentration depend on whether the measurement probe is heated or unheated.
Lead-acid batteries (LABs) play a pivotal role in the energy storage sector with applications spanning from starting-lighting-ignition batteries to grid energy storage. Passivation of lead negative electrodes by PbSO 4 particles is a fundamental mechanism limiting the performance of LAB. In this regard, an electrochemical model is developed that simulates the nucleation and growth (N&G) dynamics of PbSO 4 particles on a flat lead electrode, responsible for its passivation. The model considers the electrochemical reactions between lead electrode and sulfuric acid, N&G of PbSO 4 particles, passivation of the lead surface, and the ternary transport of PbSO 4 (aq), bisulfate, and protons in H 2 SO 4 electrolyte. The model is validated with a dataset of cyclic voltammetry (CV) responses collected at several scan rates and H 2 SO 4 concentrations. The model shows remarkable qualitative and quantitative agreement with the experimental data including CV peak features, discharge capacity, and particle size. The model was employed to explore key N&G quantities, such as supersaturation, nucleation rate, particle count, growth rate, particle size, and surface coverage, and to examine how their interactions influence electrode utilization. Parametric studies were also conducted to evaluate how scan rates and acid concentrations influence the previously mentioned N&G quantities and, subsequently, the utilization of the electrode.
Introduction: A scientist with experience as a sample science analyst, provider of flight hardware for multiple missions, and senior engineer in an ISO 2000-rated manufacturing plant has described the timeline of key participants in any PI-led sample return mission, the breadth of the organizations involved [1,2], and, of interest to this meeting, choosing the types of data to preserve and issues of future data accessibility. This work broadens that perspective by giving similar lessons from Genesis sample curation point-of-view. Curation participation regarding data gathering was part of the mission review process from the beginning. Genesis’ story illustrates outcome of several choices about types of data to record and preserve. Precision analysis of solar wind atoms captured in pure, ultraclean substrates is the driving science goal; therefore, detailed documentation was captured from all mission and curation phases and from investigator laboratories because these processes affect the final analytical results [3]. Pre-flight: Design and fabrication of the spacecraft. Like many modern small sample return missions, Genesis was a tightly managed team integrated across science, engineering and curation. Communication across the team was excellent, and, for the most part, the hands-on engineering technicians understood the impacts of “small choices” they routinely make, and the eyes-on oversight of manufacturing processes by scientists was mindful of details. The payload was designed by the Jet Propulsion Laboratory and the spacecraft by Lockheed Martin. Solar wind collectors and instruments were fabricated by multiple vendors and laboratories. The main portion of the payload was assembled at JSC. Fabrication procedures and contamination-control data (with witness coupons) were stored primarily at JSC. The original composition, dimensions and configuration of components, results of thermal testing, etc. are still needed for interpretation of analytical data. At times, these must be estimated from secondary information acquired pre-flight. Moreover, some files (e.g., original 3-D models and early Powerpoint) cannot be opened using software. Archived curation data includes 2-D drawings, material usage lists, QA documentation and analyses of consumables used during fabrication. Important chemical information still resides in archived hardware, paints and lubricants, material coupons, cleaning coupons, environmental witness plates and reference materials from manufacturing facilities. Purity and cleanliness of collector substrates. Semi-conductor vendors provided surface cleanliness data and some purity data. Purity for specific elements of interest was verified by science team members in their laboratories [4]. Curation archived procurement and shipping records, analysis reports, and non-proprietary fabrication data. A physical archive of flight collector reference materials is maintained for future use so additional data can be collected as analytical techniques improve. These are of increased value due to the hard landing upon re-entry. Cleaning and cleanliness assessments of flight hardware. Cleaning of the science canister payload was performed at JSC in a dedicated ISO 4 cleanroom using ultrapure water (UPW). The cleanliness of this UPW was monitored throughout processing. The archive for the clean lab also includes airborne particle counts, airborne molecular and inorganic contamination measurements as well as cleanroom construction material coupons and witness coupons. Hardware cleanliness was assessed by particle counts in rinse water batches. This information is recorded in batch cleaning forms and logbooks, and are, perhaps, of decreased value due to the hard landing. Post-flight: Curation-generated data. The curation handling history of each Genesis sample is documented in a typical astromaterials sample database which captures sample location, physical description and characterization data. Samples have a “shelf life”. Crucial to the preservation of samples is ongoing documentation of the sample environment, initially under curatorial control but is now a separate facility function with requires coordination. PI-generated data. Data on sample characterization and cleaning techniques continues to be generated by sample users [5]. These are often captured in LPSC abstracts, but these “engineering” results often are not publishable as stand-alone papers. We are actively looking for ways to make this information more accessible to users. Ion implants into samples have aided science return and can be shared among investigators. These (and similar) materials should be added to the curatorial collection with appropriate process and characterization data generated externally. Summary: Complete data archives for returned astromaterial samples must be broad in types and formats, and inclusive of environmental monitoring.
The accuracy of Young's fringe method for reducing velocity field data is compromized by a spatially incoherent background field which originates in the random locations of the seeding particles. The probability density function for the spatial frequency cutoff of this background is derived as a function of the particle count, the distribution governing the power in each frequency interval is derived, and conditions are found under which the Van Cittert-Zernike theorem applies. The background field resembles the far field of a partially coherent source in the high particle count limit, but departs significantly at low and moderate counts.
The James Webb Space Telescope (JWST) launched from the Centre Spatial Guyanais (CSG) in December 2021. JWST’s requirements permitted processing in International Organization for Standardization (ISO) Class 7 or better facilities, but CSG was only equipped with ISO Class 8 facilities. To temporarily upgrade the air cleanliness in the Payload Processing Facility, Fueling Hall, and Final Assembly Building Encapsulation Hall, NASA provided two portable High Efficiency Particulate Air (HEPA) and carbon filter walls that were used in each location. The walls were comprised of stacks of two modules high and arranged in push-push configurations as shown to be most effective via Computational Fluid Dynamics simulations of expected floor layouts in each facility. After delivery to NASA’s Goddard Space Flight Center in 2020, the walls underwent initial verification measurements inside a cleanroom and validation testing in an uncontrolled area to quantify their improvement of air cleanliness and particle and molecular fallout. Validation testing showed improvements of 83-99% for airborne particle counts, 79-91% for particle fallout, and 50-90% for molecular fallout. The particle improvements were applied to the contamination budget analysis that tracked current and predicted future cleanliness against End-of-Life requirements for JWST’s critical surfaces. At CSG, the walls successfully maintained an ISO Class 7 environment or better within their envelope in each location, despite their presence in ISO Class 8 facilities with dense integration operations.
The James Webb Space Telescope (JWST) launched from the Centre Spatial Guyanais (CSG) in December 2021. JWST’s requirements permitted processing in International Organization for Standardization (ISO) Class 7 or better facilities, but CSG was only equipped with ISO Class 8 facilities. To temporarily upgrade the air cleanliness in the Payload Processing Facility, Fueling Hall, and Final Assembly Building Encapsulation Hall, NASA provided two portable High Efficiency Particulate Air (HEPA) and carbon filter walls that were used in each location. The walls were comprised of stacks of two modules high and arranged in push-push configurations as shown to be most effective via Computational Fluid Dynamics simulations of expected floor layouts in each facility. After delivery to NASA’s Goddard Space Flight Center in 2020, the walls underwent initial verification measurements inside a cleanroom and validation testing in an uncontrolled area to quantify their improvement of air cleanliness and particle and molecular fallout. Validation testing showed improvements of 83-99% for airborne particle counts, 79-91% for particle fallout, and 50-90% for molecular fallout. The particle improvements were applied to the contamination budget analysis that tracked current and predicted future cleanliness against End-of-Life requirements for JWST’s critical surfaces. At CSG, the walls successfully maintained an ISO Class 7 environment or better within their envelope in each location, despite their presence in ISO Class 8 facilities with dense integration operations.
Sequential Monte Carlo (SMC) samplers are powerful tools for Bayesian inference but suffer from high computational costs due to their reliance on large particle ensembles for accurate estimates. We introduce persistent sampling (PS), an extension of SMC that systematically retains and reuses particles from all prior iterations to construct a growing, weighted ensemble. By leveraging multiple importance sampling and resampling from a mixture of historical distributions, PS mitigates the need for excessively large particle counts, directly addressing key limitations of SMC such as particle impoverishment and mode collapse. Crucially, PS achieves this without additional likelihood evaluations-weights for persistent particles are computed using cached likelihood values. This framework not only yields more accurate posterior approximations but also produces marginal likelihood estimates with significantly lower variance, enhancing reliability in model comparison. Furthermore, the persistent ensemble enables efficient adaptation of transition kernels by leveraging a larger, decorrelated particle pool. Experiments on high-dimensional Gaussian mixtures, hierarchical models, and non-convex targets demonstrate that PS consistently outperforms standard SMC and related variants, including recycled and waste-free SMC, achieving substantial reductions in mean squared error for posterior expectations and evidence estimates, all at reduced computational cost. PS thus establishes itself as a robust, scalable, and efficient alternative for complex Bayesian inference tasks.