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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Identification of Phyllosilicates in Mudstone Samples Using Water Releases Detected by the Sample Analysis at Mars (SAM) Instrument in Gale Crater, Mars

The Sample Analysis at Mars (SAM) instrument on board the Curiosity Rover has detected high temperature water releases from mud-stones in the areas of Yellowknife Bay, Pahrump Hills, Naukluft Plateau, and Murray Buttes in Gale crater. Dehydroxylation of phyllosilicates may have caused the high temperature water releases observed in these samples. Because each type of phyllosilicate undergoes dehydroxylation at distinct temperatures, these water releases can be used to help constrain the type of phyllosilicate present in each sample.

Hogancamp, J. V. (Clark)↗
DOE OSTI2020

An outbreak of Septoria canker caused by Sphaerulina musiva on Populus trichocarpa in eastern Oregon

Branch and stem cankers were observed in a Populus trichocarpa L. plantation in late summer of 2018 near Boardman, Oregon USA. Stem cankers were flat faced with swollen margins and the bark in the center of the cankers was black and depressed (Figure 1). 254 out of 1054 trees (25%) observed had cankers. Symptomatic stems and branches from several trees were brought to Oregon State University for identification. Cankers were surface-disinfested in a 5% NaOCl for 2 min and rinsed twice in deionized H 2 O for 2 min. Bark was removed from cankers and pieces of wood at the margin between healthy and necrotic tissue were plated on KV8 medium amended with streptomycin sulfate at 100 mg liter–1 and chloramphenicol (Amresco) at 240 mg liter–1 (Dunnell and LeBoldus 2017). Eight sporulating colonies typical of Sphaerulina musiva (Peck) Quaedvlieg, Verkley, and Crous (Syn. = Septoria musiva Peck) developed within 7 days of plating. S. musiva was identified by morphological characteristics (conidium size = 28–54 × 3.5–4 µm) and confirmed by comparing the sequence of the ITS region (accession numbers: MN275180-MN275187) to JX901814 with 99% identity. We tested 13 additional cankers collected from the plantation using S. musiva specific primers (Abraham et al. 2018). Eight of the 13 samples were positive for S. musiva DNA. Dormant cuttings from three genotypes of P. trichocarpa (BESC-184; BESC-259; BESC-388) were collected in a field planting near Oregon State University (OSU). These were planted in cone-tainers in the greenhouse at OSU and grown to approximately 30 cm in height. Four replicates of each of the three genotypes were inoculated in the greenhouse with one Oregon isolate using a suspension of 1x10 6 conidia ml-1. The entire tree was sprayed until runoff using a spray bottle (LeBoldus et al. 2010). The experimental design was a completely randomized design with four replicates of each genotype. Sterile deionized H 2 O was sprayed on one control tree of each genotype. The mean number of resulting cankers were BESC-184 = 11, BESC-259 = 1, and BESC-388 = 13.75. The controls did not develop any cankers. The pathogen was successfully reisolated from one canker from each genotype. Sphaerulina musiva can cause severely damaging leaf spot and stem canker diseases in the eastern and central USA and Canada (Bier 1939; Herath et al. 2016). Susceptible Populus species and hybrids develop cankers which can girdle and weaken stems, leading to breakage or tree death (Bier 1939). A previous survey of the region did not detect S. musiva (Newcombe et al. 1995). This outbreak of Septoria canker underscores the potential threat of this pathogen to P. trichocarpa in the Pacific Northwest where it is a keystone species in riparian ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A novel approach to identify the ionomer phase in PEMFC by EELS

Proton exchange membrane fuel cells are one of the most promising technologies of energy conversion for both automotive and stationary applications, due to their ultimate cleanness and high efficiency. A critical factor, which strongly affects the fuel cell performance, is the ionomer distribution and coverage over the carbon support, since the catalysts, which are typically Pt and/or Pt-alloy nanoparticles, must be located at the carbon support/ionomer interface to catalyze the sluggish oxygen reduction reaction. However, the characterization and identification of the ionomer film, in terms of ionomer distribution and coverage over the carbon surface, is a long standing challenge. This is because the ionomer film may suffer from beam damage during the characterization, either from x-rays, neutrons or an electron beam, which causes morphological changes. In this regard, we report here a novel approach to identify and differentiate the ionomer, using the carbon signal produced by STEMEELS. Using this approach, not only the ionomer distribution, but also the carbon support distribution, can be probed at high spatial resolutions. In addition, this new approach allows us to identify ionomer-rich and carbon-support rich regions, which are quite challenging to determine using other methods.

08 HYDROGEN↗
DOE OSTI2024

Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1

Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Determination of Martian soil mineralogy and water content using the Thermal Analyzer for Planetary Soils (TAPS)

Physical and chemical interactions between the surface and atmosphere of Mars can be expected to embody a strong cause-and-effect relationship with the minerals comprising the martian regolith. Many of the minerals in soils and sediments are probably products of chemical weathering (involving surface/atmosphere or surface/hydrosphere reactions) that could be expected to subsequently influence the sorption of atmospheric gases and water vapor. Therefore, identification of the minerals in martian surface soils and sediments is essential for understanding both past and present interactions between the Mars surface and atmosphere. Clearly, the most definitive mineral analyses would be achieved with well-preserved samples returned to Earth-based laboratories. In advance of a Mars sample return mission, however, significant progress could be made with in situ experiments that fill current voids in knowledge about the presence or abundance of key soil minerals such as clays (layered-structured silicates), zeolites, and various salts, including carbonates. TAPS is intended to answer that challenge by providing first-order identification of soil and sediment minerals.

Gooding, James L.↗
NASA NTRS2010

Analysis of Dependencies and Impacts of Metroplex Operations

This report documents research performed by Purdue University under subcontract to the George Mason University (GMU) for the Metroplex Operations effort sponsored by NASA's Airportal Project. Purdue University conducted two tasks in support of the larger efforts led by GMU: a) a literature review on metroplex operations followed by identification and analysis of metroplex dependencies, and b) the analysis of impacts of metroplex operations on the larger U.S. domestic airline service network. The tasks are linked in that the ultimate goal is an understanding of the role of dependencies among airports in a metroplex in causing delays both locally and network-wide. The Purdue team has formulated a system-of-systems framework to analyze metroplex dependencies (including simple metrics to quantify them) and develop compact models to predict delays based on network structure. These metrics and models were developed to provide insights for planners to formulate tailored policies and operational strategies that streamline metroplex operations and mitigate delays and congestion.

DeLaurentis, Daniel A.↗
NASA NTRS2020

Spatial distribution of the X-ray-emitting plasma of U Geminorum in quiescence and outburst

We present our analysis of the Suzaku data of U Geminorum (U Gem) from 2012 both in quiescence and outburst. Unlike SS Cygni (SS Cyg), the hard X-ray flux of U Gem is known to increase at times of optical outburst. A sophisticated spectral model and reliable distance estimate now reveal that this can be attributed to the fact that the mass accretion rate onto the white dwarf (WD) does not exceed the critical rate that causes the optically thin to thick transition of the boundary layer. From comparison of the X-ray and optical light curves, the X-ray outburst peak seems to be retarded by 2.1 ± 0.5 d, although there remains uncertainty in the X-ray peak identification, due to short data coverage. The larger delay than SS Cyg (0.9–1.4 d) also supports the lower accretion rate in U Gem. A fluorescent iron 6.4 keV emission line bears significant information about the geometry of the X-ray-emitting hot plasma and the accretion disk (AD) that reflects the hard X-ray emission. Our reflection simulation has shown that the optically thick AD is truncated at a distance of 1.20–1.25 times the white dwarf radius (RWD) in quiescence, and the accreting matter in the disk turns into the optically thin hard-X-ray-emitting plasma at this radius. In outburst, on the other hand, our spectral analysis favors the picture that the optically thick disk reaches the WD surface, although disk truncation can take place in the region of <1.012 RWD. From the profile of the 6.4 keV line, we have also discovered that the accreting matter is heated up close to the maximum temperature immediately after the matter enters the boundary layer at the disk truncation radius. This is consistent with the fact that the hard X-ray spectra of dwarf novae, in general, can be well represented with the cooling flow model.

Mai Takeo↗
NASA NTRS1981

Geological remote sensing: Identification and mapping of rock types for non-renewable resources

Efforts concentrated on developing a technique for relating laboratory spectral reflectance curves of known rocks and vegetation on LANDSAT multispectral images. The techniques involves determination of the laboratory spectral signature of a material of interest and searching a stack of spatially registered multispectral images for materials with the desired spectral signature. Changes in spectral reflectance caused by vegetation cover were also investigated in surface samples from Hawaii.

Adams, J. B.↗
NASA NTRS1988

An alternative to Guyan reduction of finite-element models

Structural modeling is a key part of structural system identification for large space structures. Finite-element structural models are commonly used in practice because of their general applicability and availability. The initial models generated by using a standard computer program such as NASTRAN, ANSYS, SUPERB, STARDYNE, STRUDL, etc., generally contain tens of thousands of degrees of freedom. The models must be reduced for purposes of identification. Not only does the magnitude of the identification effort grow exponentially as a function of the number of degrees of freedom, but numerical procedures may also break down because of accumulated round-off errors. Guyan reduction is usually applied after a static condensation. Misapplication of Guyan reduction can lead to serious modeling errors. It is quite unfortunate and disappointing, since the accuracy of the original detailed finite-element model one tries very hard to achieve is lost by the reduction. First, why and how Guyan reduction always causes loss of accuracy is examined. An alternative approach is then introduced. The alternative can be thought of as an improvement of Guyan reduction, the Rayleigh-Ritz method, and in particular the recent algorithm of Wilson, Yuan, and Dickens. Unlike Guyan reduction, the use of the alternative does not need any special insight, experience, or skill for partitioning the structural degrees of freedom. In addition to model condensation, this alternative approach can also be used for predicting analytically, quickly, and economically, what are those structural modes that are excitable by a force actuator at a given trial location. That is, in the excitation of the structural modes for identification, it can be used for guiding the placement of the force actuators.

Lin, Jiguan Gene↗
DOE OSTI2020

Staphylococcus pseudintermedius 5'-nucleotidase suppresses canine phagocytic activity

Staphylococcus pseudintermedius is a major opportunistic bacterial pathogen and the leading cause of pyoderma in dogs. In canines it is also often associated with infections of the urinary system and wounds and occasionally infects people. Widespread antimicrobial resistance has made the development of alternative treatments a high priority. The development of a staphylococcal vaccine, however, has proven challenging. Identification of virulence factors that inhibit phagocytosis and avoid innate immunity may play a significant role in preventing or treating infection with S. pseudintermedius. In this study, we identified a putative 5'-nucleotidase provisionally named SpAdsA, a S. pseudintermedius cell- wall protein encoded by SpAdsA. SpAdsA shares approximately 52% identity with the orthologous protein of Staphylococcus aureus and 14.8% identity with that of Streptococcus suis type2. It catalyzes the dephosphorylation of adenosine triphosphate and attenuation of this enzyme with critical amino acid substitutions nearly eliminated its hydrolytic activity. Furthermore, exogenous adenosine inhibited phagocytosis of S. pseudintermedius by canine neutrophils and monocytes. Conversely, the addition of SpAdsA inhibitor or A2A adenosine receptor antagonist impaired the capacity of S. pseudintermedius to escape from killing by phagocytic cells. The neutralizing ability of canine antibody produced against SpAdsA-M was determined. Taken together, these results suggest that SpAdsA likely plays an important role in S. pseudintermedius virulence and that attenuated SpAdsA may be a good candidate for inclusion in a vaccine against S. pseudintermedius.

5'-nucleotidase↗
NASA NTRS1976

Crystal activation experiment MA-151

The crystal activation experiment consisted of two sample packages that were flown in the command module and returned to earth for analysis of the radioactivity induced in them during the flight. The objective of the experiment was to define the background caused by detector activation that interferes when gamma radiation is measured in the 0.02- to 10-megaelectronvolt range from earth orbit. Preliminary results show that the activation of the NaI(Tl) crystal was a factor of 3 below that from a similar measurement on Apollo 17. The identification of certain species and the level of activation observed show an important contribution from the interactions of thermal and energetic neutrons produced as secondaries in the spacecraft. That the activation was reduced by only a factor of 3 compared with the Apollo 17 experiment, despite the geomagnetically shielded orbit, possibly indicates more efficient secondary neutron production by the more energetic cosmic rays.

Trombka, J. I.↗
NASA NTRS2007

STS-114 Micrometeoroid/Orbital Debris (MMOD) Post-Flight Assessment

NASA Johnson Space Center (JSC) personnel assisted Kennedy Space Center (KSC) inspection teams in the identification of 41 micrometeoroid/orbital debris (MMOD) impact sites on the OV-103 vehicle (Discovery) during STS-114 postflight inspections. There were 14 MMOD impacts reported on the crew module windows (Figure 1). The largest impact feature, a 6.6 mm x 5.8 mm crater on window #4, was caused by a particle with an estimated diameter of 0.22 mm (Figure 2). This impact was among the largest ever recorded on a crew module window. The window was removed and replaced. Scanning Electron Microscope/Energy Dispersive X-ray (SEM/EDX) analysis of dental mold samples from the impact site to determine particle origin was inconclusive, possibly due to contamination picked up on the ferry flight from Edwards Air Force Base to KSC. The radiators on the inside of the payload bay doors sustained 19 impacts (Figure 3) with one of the impacts causing a face sheet perforation. The 0.61 mm diameter hole was produced by a particle with an estimated diameter of 0.4 mm, which approaches the 0.5-mm critical particle diameter of the wing leading edge reinforced carbon-carbon (RCC) panel high-temperature regions (Zone 3, Figure 4) that was established during Return to Flight testing of the RCC panels. An inspection of the payload bay door exterior insulation (FRSI) revealed a 5.8 mm x 4.5 mm defect that was caused by an MMOD particle with unknown composition, as the sample obtained was contaminated. Figure 5 provides a summary of the exterior surface survey that was conducted following the STS-114 mission. Two windows were removed and replaced due to hypervelocity impact. Nineteen impacts were recorded on the payload bay door radiators, with one face sheet penetration. Three impact sites were identified on the FRSI. There were four hypervelocity impact sites detected on the wing leading edge RCC panels. One impact was detected on the top cover of the TPS sample box (TSB) payload that was mounted on a carrier in the aft portion of the payload bay.

Hyde, J.↗
DOE OSTI2024

Chemical composition based machine learning model to predict defect formation in additive manufacturing

With a goal of exploiting additive manufacturing to improve the manufacturing of existing reactor materials, we developed a chemical composition-based machine learning model to predict the printability of any given alloy in laser powder bed fusion (L-PBF) using experimental data from peer-reviewed literature. We defined printability as the ability to avoid defects like cracking, balling, porosity, and lack of fusion, that are caused by thermal stresses (during solidification or liquation), molten pool disintegration into disconnected small beads or lack of heat input respectively. Our models predict the tendency of balling defect formation and porosity percentage for a given composition, under a given set of processing conditions. To predict the likelihood of balling defect, three models: a random forest classifier, a gradient boost regressor and a neural network were trained on a dataset containing both traditional alloys and high entropy alloys. The neural network model showed the highest accuracy of 92.3 % in predicting the balling defect formation. A random forest regressor, gradient boost regressor and neural network were trained and tested on a dataset of various alloys to predict porosity. The random forest regressor showed the best predictions with an R 2 score of 0.97. The models also revealed the relative importance of the input descriptors on defect-formation tendency. Of particular significance was the identification of carbon as an important element in determining the occurrence of balling and percent porosity in alloys like steel, as well as being moderately important to the percentage porosity in other alloys as well as steel. Manganese was also identified as a key descriptor for the percentage of porosity in steel and other alloys. Manganese’s low thermal conductivity and consistent presence in the dataset is the likely cause for its contribution. Carbon’s role is attributable to its relatively high specific heat and high melting temperature. In conclusion, our model serves as a swift, chemistry-based tool to design experiments and find modified compositions better suited for additive manufacturing.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Develop advanced nonlinear signal analysis topographical mapping system

The SSME has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) Develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system. (2) Develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amounts of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. A high compression ratio can be achieved to allow the minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities. (3) Integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for a quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Jong, Jen-Yi↗
NASA NTRS1994

Develop advanced nonlinear signal analysis topographical mapping system

The Space Shuttle Main Engine (SSME) has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature, pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system; (2) develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amount of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. High compression ratio can be achieved to allow minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities; and (3) integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Source record↗
NASA NTRS2021

Spectral Effects of Varying Texture and Composition in Two-component “Mudpie” Simulations: Insights for Asteroid (101955) Bennu

Data returned by the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft have shown that asteroid (101955) Bennu has a globally low-albedo surface covered in boulders with diverse texture, color, and albedo properties, and an aqueously altered composition dominated by phyllosilicates. To test whether Bennu’s color and albedo diversity could be caused by texture and/or composition variations, we performed a laboratory-based study using simple two-component mixtures (called “mudpies”) of the phyllosilicate saponite and carbon-rich opaques. Each mudpie is prepared in four different textures: fine powder, coarse particles, sanded slab, and textured rock. We find that a sanded slab made from 90% saponite and 10% lampblack is a good analog for Bennu, and the color and albedo changes due to texture variations are substantial. At 550 nm, texture changes alone can create up to 36% brightness contrast, and in color measured as a 473 nm/847 nm ratio, texture changes can provide up to 18% color contrast. In comparison, Bennu shows approximately 25% albedo and <1% color contrasts from boulder type to boulder type. These findings suggest that if texture contributes to color on Bennu, the texture variations are typically more subtle than what we simulated in the laboratory. According to our study, the color and albedo properties of different boulder types on Bennu are consistent with different concentrations of carbon-rich opaques (and possibly consistent with variations in carbonate concentration). The variations within each boulder group are consistent with textural differences.

Antara Sen↗
DOE OSTI2020

Drivers for the cracking of multilayer polyamide‐based backsheets in field photovoltaic modules: In‐depth degradation mapping analysis

Abstract There is a lack of understanding on the root cause of cracking of photovoltaic (PV) backsheets due to the challenge of multilayer characterization and the complicated failure modes at the submodule level. In this work, the in‐depth degradation mapping of field‐exposed polyamide‐based (PA‐based) PV module backsheets was studied, with the major focus on the identification of underlying drivers for the through cracking (in between the solar cells). PV modules were retrieved from five different locations, comprising a variety of climates, including humid subtropical, hot‐summer Mediterranean, tropical savanna climate, and hot arid. A suite of microscale cross‐sectional characterizations, including chemical changes, fluorescence intensity, and modulus as a function of distance from the air surface of the backsheet, was performed. Results showed more advanced signs of degradation of the inner layer than the outer layer in the cracking region. Increases in the modulus were identified as the major indicator for the cracking. Moreover, a rudimentary test by immersion in acetic acid, which forms during photodegradation of the ethylene‐vinyl acetate copolymer (EVA) encapsulant, showed the first‐time direct evidence that acetic acid can largely accelerate the chemical degradation and facilitate the cracking of PA inner layer. This study suggests that the field cracking of PA‐based backsheet can be attributed to the combined effects of chemical degradation and physical reorganization (chemi‐crystallization) under cyclic thermomechanical stresses. Therefore, it is important to consider effects of local microclimates and interlayer infection to understand the heterogeneous nature of backsheet failures.

Lyu, Yadong↗