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At least 1,729 records · Page 96

Establishing a Design Strategy for Corrosion Resistant Structural Materials in Molten Salt Technologies

To address the gap in material design strategies for structural components in molten salt-powered technologies, the current work aimed to identify key parameters governing corrosion induced degradation of materials during exposures in molten halide salts. The applicability of the data on dissolution rates of pure metals (e.g., Cr) in a given molten salt to enable predictions of corrosion behavior of multicomponent binary and ternary Fe-based model and Ni-based commercial alloys isothermally exposed in the purified KCl-MgCl 2 in quartz capsules at 700 and 800°C was evaluated. The influence of alloy chemistry on initial dissolution rates and the consequent impact on the time-dependent corrosion induced microstructural evolution in the alloy subsurface was predicted with a coupled thermodynamic-kinetic model. Finally, the model was well able to predict the Cr depletion in all investigated alloys demonstrating the ability of the proposed approach to enable a unique design strategy for structural materials in molten salts.

36 MATERIALS SCIENCE↗

Cancer Treatment-Associated Pericardial Disease: Epidemiology, Clinical Presentation, Diagnosis, and Management

Purpose of Review: Cancer therapeutics have seen tremendous growth in the last decade and have been effective in the treatment of several cancer types. However, with advanced therapies like kinase inhibitors and immunotherapies, there have been unintended consequences of cardiotoxicities. While traditional chemotherapy and radiation-induced cardiotoxicity have been well studied, further research is needed to understand the adverse effects of newer regimens. Recent Findings: Both immune-mediated and non-immune-medicated cytotoxicity have been noted with targeted therapies such as tyrosine kinase inhibitors and immune checkpoint inhibitors. In this manuscript, we describe the pericardial syndromes associated with cancer therapies and propose management strategies. Pericardial effusion and pericarditis are common presentations in cancer patients and often difficult to diagnose. Concomitant myocarditis may also present with pericardial toxicity, especially with immunotherapies. In addition to proper history and physical, additional testing such as cardiovascular imaging and tissue histology need to be obtained as appropriate. Holding the offending oncology drug, and institution of anti-inflammatory medications, and immunosuppressants such as steroids are indicated. Summary: A high index of suspicion, use of standardized definitions, and comprehensive evaluation are needed for early identification, appropriate treatment, and better outcomes for patients with cancer treatment-associated pericardial disease. Further research is needed to understand the pathophysiology and to evaluate how the management of pericardial conditions in these patients differ from traditional management and also evaluate new therapies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Transient disease dynamics across ecological scales

Analyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.

59 BASIC BIOLOGICAL SCIENCES↗

Finding Promising Candidates for Wet Growing Conditions: The Effect of Two Row Spacings on Biomass Production of Four Bioenergy Prairie Cordgrass Populations in a Wet Marginal Land

Demand for energy and the environmental consequences associated with fossil fuel emissions has created a need for alternative energy sources. To avoid conflict over the conversion of existing agricultural land from food production to fuel production, bioenergy crops could instead be cultivated on marginal land. Here, this study compared the performances, biomass yield, tiller density, and lignocellulosic bioenergy feedstock composition of four prairie cordgrass populations with two-row spacings cultivated on a waterlog-prone marginal land, as well as three other bioenergy candidate crops used as controls: big bluestem, M. × giganteus , and switchgrass. Across all populations and spacings, annual biomass yield of prairie cordgrass was 13 Mg ha −1 . Row spacing had significant impacts on prairie cordgrass productivity, with higher biomass yields observed in the 45 cm spacing than in the 90 cm spacing. Feedstock composition (cellulose, hemicellulose, ADL, and ash concentration) was not influenced by row spacing and did not deviate from expected values for growth on agricultural lands. However, biomass yields of the control species M . × giganteus and switchgrass planted in 45 cm spacing were higher than the prairie cordgrass. Our results provide evidence that prairie cordgrass could be a good energy crop with comparable biomass yield production to the energy crops M . × giganteus and switchgrass on waterlogged marginal land.

Bioenergy crops↗

Towards an Integrated Process for CO 2 Capture and Utilization: Cultivation of Scenedesmus acutus Using Gaseous CO 2 and NH 3

Integrating CO 2 scrubbing from flue gas with its utilization in algae cultivation represents a potential means of lowering the cost of CO 2 capture. Towards this goal, this study sought to assess the feasibility of using gaseous a CO 2 /NH 3 stream, derived from CO 2 capture using aqueous ammonia, as a C- and N-source for algae cultivation. Scenedesmus acutus was cultured in 800 mL photobioreactors using gaseous CO 2 /NH 3 in mole ratios varying from 7 to 18. Excellent growth of Scenedesmus acutus was observed, the average growth rate for CO 2 /NH 3 = 10 of 0.171 ± 0.015 g/L·day exceeding that obtained using 1% CO 2 /N 2 and urea as the N-source (0.099 ± 0.28 g/L·day). Under optimal growth conditions (CO 2 /NH 3 mole ratio of 10), CO 2 utilization ranged from 57% to 72%, while the NH 3 utilization was >90%. The CO 2 /NH 3 feed rate was also found to exert a significant effect on algae productivity, excessive feed rates leading to accumulation of NH 3 in the culture at concentrations that were toxic to the algae. Consequently, to avoid the toxic effects of high NH 3 concentrations (>2.0 mM), it proved necessary to balance the NH 3 supply with the algae growth rate so that excessive NH 3 accumulation was prevented. This indicates that for practical applications, a CO 2 /NH 3 feed control strategy would be required that takes into account the ammonium ion concentration in solution and the pH so as to avoid significant concentrations of free NH 3 . Furthermore, analysis of the harvested biomass revealed a high protein (≥ 47 wt%) and a low ash content (< 3.6 wt%), suggesting it would be well suited for use as animal feed or as a feedstock for the production of bioplastics.

03 NATURAL GAS↗

Developing occupant archetypes within urban low-income housing: A case study in Mumbai, India

Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural and psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling↗

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗

Geophysical Constraints on Decarbonized Systems—Building Spatio-Temporal Uncertainties into Future Electricity Grid Planning

Future electricity grids will be characterized by the high penetration of renewables to support the decarbonization process. Yet, this transition will further expose grids to a broad spectrum of geophysical forces, such as weather and climate, land and space, minerals and materials. Understanding their role is thus important to support the grid decarbonization process. Here, we synthesize the current body of knowledge on the relationship between geophysical constraints and electricity grid planning. Additionally, we show that there have been promising advances in the data, methods, and modelling tools needed to incorporate the effect of geophysical constraints on demand, resource availability, and grid operations. There are, however, multiple research avenues that deserve further attention. More system-specific and finer-scale analyses are necessary to better understand how spatio-temporal variability---and associated uncertainty---in geophysical forces affect grid planning. Moreover, we need a broader focus on the multi-sectoral implications of grid decarbonization efforts, so as to limit the risk of unintended consequences. Importantly, all these efforts are challenged by the computational requirements of existing power system models, which often limit our ability to characterize uncertainty, scale analyses across larger domains, or study the multi-sector implications of grid expansion decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Energy Justice Through Energy Storage: Supporting Energy Resilience in Disadvantaged Communities

This paper reviews energy storage technologies as a possible solution to address power outages and mitigate the impacts, enhancing vulnerable communities’ resilience to climate change. More frequent and severe extreme weather events are one of the main consequences of climate change. These events, coupled with the nation’s aging and frail energy infrastructure, are causing many communities throughout the United States to experience more frequent and longer power outages, resulting in economic, health, and social impacts. Impacts from power outages are not equally felt across communities, with disproportionate impacts across communities representing a matter of energy justice. From an energy justice standpoint, programs and policies that facilitate energy storage technologies should be intentionally designed to include distributive, procedural, recognition, and restorative justice.

25 ENERGY STORAGE↗

Distributed intelligence and the equivalence of matter and information

Here, it is argued that science of discontinua represents a major paradigm shift in how scientific research is done. First, a historical perspective is given, followed by key aspects of discontinuum simulations and its potential in aiding research and development. This is followed by a philosophical perspective on equivalence of matter and information as inspired by Aristotle’s quest for souls in living things such as cells. Finally, the universality of the discontinuum approach is explored with its consequences for computing and artificial intelligence.

97 MATHEMATICS AND COMPUTING↗

A Review of Abrupt Permafrost Thaw: Definitions, Usage, and a Proposed Conceptual Framework

Purpose of ReviewWe review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science.Recent FindingsWe address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire.SummaryPermafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.

Webb, Hailey↗

Performance of a Drifting Acoustic Instrumentation SYstem (DAISY) for characterizing radiated noise from marine energy converters

Marine energy converters can generate electricity from energetic ocean waves and water currents. Because sound is extensively used by marine animals, the radiated noise from these systems is of regulatory interest. However, the energetic nature of these locations poses challenges for performing accurate passive acoustic measurements, particularly with stationary platforms. The Drifting Acoustic Instrumentation SYstem (DAISY) is a modular hydrophone recording system purpose-built for marine energy environments. Using a flow shield in currents and mass–spring–damper suspension system in waves, we demonstrate that DAISYs can effectively minimize the masking effect of flow noise at frequencies down to 10 Hz. In addition, we show that groups of DAISYs can utilize time-delay-of-arrival post-processing to attribute radiated noise to a specific source. Consequently, DAISYs can rapidly measure radiated noise at all frequencies of interest for prototype marine energy converters. Furthermore, the resulting information from future operational deployments should support regulatory decision-making and allow technology developers to make design adjustments that minimize the potential for acoustic impacts as their systems are scaled up for utility-scale power generation.

16 TIDAL AND WAVE POWER↗

Palladium/Zeolite Low Temperature Passive NOx Adsorbers (PNA): Structure-Adsorption Property Relationships for Hydrothermally Aged PNA Materials

Zeolites with different framework structures (SSZ-13, ZSM-5, BEA) but similar Si/Al ratios and Pd loading (~1 wr%) were synthesized and evaluated as low temperature passive NOx adsorbers (PNA). These materials exhibit high NOx adsorption efficiency with atomically dispersed Pd the active adsorption site. Hydrothermal aging at 750 ºC for 16 hours in the presence of 10% water vapor in air resulted in the formation of PdO nanoparticles in all three samples as evidenced by high energy XRD. Hydrothermal aging of the small-pore Pd/SSZ-13 (Si/Al = 6), which contain ~100-90% atomically dispersed palladium ions, decreases its PNA performance only by ~10-20%. High-field solid state 27Al NMR studies on the fresh and aged samples substantiate dealumination and significant changes in the distribution of Al (and thus, Bronsted acid) sites after hydrothermal aging. FTIR measurements with NO probe molecule and titration of Bronsted acid sites with nitrosyl (NO+) ions further corroborate the 27Al NMR data. Because framework aluminum atoms are the anchoring sites for atomically dispersed Pd ions, their elution from the framework causes the loss of active atomically dispersed Pd species. Furthermore, with the aid of HAADF-STEM imaging and synchrotron XRD studies, we further confirm and visualize the fate of these Pd species – they agglomerate into PdO nanoparticles on the external surface of zeolite. Consequently, these changes lead to the decrease in PNA performance of these materials after hydrothermal aging. The thus formed agglomerates cannot be re-dispersed back to their ionic state due to the loss of framework Al T-sites and/or inherent stability of such large PdO particles. Our study clearly demonstrates that, unlike in previous studies that found increased PNA performance upon HTA , high temperatures hydrothermal aging of PNA materials that contain atomically dispersed Pd initially, results in a decrease in NOx storage efficiency due mostly to the formation of PdO agglomerates. However, we also highlight the high hydrothermal stability of predominantly atomically dispersed 1-3 wt% Pd/SSZ-13 (Si/Al = 6), whose performance decreases only marginally after prolonged hydrothermal aging at 750 ºC. Overall, this study shows that hydrothermally stable passive NOx materials can be prepared using small-pore SSZ-13 zeolite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical and experimental investigation of the geometry dependent layer-wise evolution of temperature during laser powder bed fusion of Ti–6Al–4V

Abstract Laser powder bed fusion (L-PBF) is currently the additive manufacturing process with the widest industrial use for metal parts. Yet some hurdles persist on the way to a widespread industrial serial production, with reproducibility of the process and the resulting part properties being a major concern. As the geometry changes, so do the local boundary conditions for heat dissipation. Consequently, the use of global, geometry-independent processing parameters, which are today’s state of the art, may result in varying part properties or even defects. This paper presents a numerical simulation as a method to predict the geometry-dependent temperature evolution during the build. For demonstration, an overhang structure with varying angles towards the build platform was manufactured using Ti–6Al–4V. A calibrated infrared camera was integrated into a commercial L-PBF system to measure the temperature evolution over time for a total build height of 10 mm, and the results are used for validation of the simulation. It is shown that the simulation is capable of predicting the temperature between layers. The deviations between simulation and measurement remain in single digit range for smaller overhang structures (90°, 60° and 45°). For large overhang structures (30°), the simulation tends to over-predict the temperatures up to 15 °C. Experiments with varying process parameters showed the feasibility of energy reduction as compensation of the heat accumulation produced by overhang structures.

Li, Gefei (ORCID:0000000174837952)↗

Emulating the impact of additional proton-proton interactions in the ATLAS simulation by pre-sampling sets of inelastic Monte Carlo events

The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton-proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run (2015-2018) there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.

97 MATHEMATICS AND COMPUTING↗

A structural equation modeling approach to leveraging the power of extant sentiment analysis tools

Machine-derived sentiment analysis has become a pervasive and useful tool to address a wide array of issues in natural language processing. Leading technology companies such as Google now provide sentiment analysis tools (SATs) as readily accessible online products. Academic researchers develop and make available SATs to support the research enterprise. One of the major challenges with SATs is the inconsistencies in results among the various SATs. Consequently, the selection of a SAT for a specific purpose may significantly impact the application. This study addresses the foregoing problem by utilizing structural equation modeling to merge the outputs of SATs to develop a combined sentiment metric without the need for a labeled training dataset. This method is applicable to a wide range of text-based problems, is data-driven, and replicable. It was tested using three publicly available datasets and compared against seven different SATs. The results indicate that as a continous measure, the proposed method outperformed other SATs in the movie reviews and SemEval datasets, and achieved a tie for first place with IBM Watson on the Sentiment 140 dataset. Also, compared to the published major alternatives, the arithmetic mean solution, this approach performed better across these three datasets.

97 MATHEMATICS AND COMPUTING↗

Bond-Based Peridynamics: a Tale of Two Poisson’s Ratios

This paper explores the restrictions imposed by bond-based peridynamics, particularly with respect to plane strain and plane stress models. We begin with a review of the derivations in Gerstle et al. (2005) wherein for isotropic materials a Poisson’s ratio restriction of $\frac{1}{4}$ for plane strain and $\frac{1}{3}$ for plane stress is deduced. Next, we show Cauchy’s relations are an intrinsic limitation of bond-based peridynamics and specialize these restrictions to plane strain and plane stress models. This generalizes the results from Gerstle et al. (2005) and demonstrates that the Poisson’s ratio restrictions described in Gerstle et al. (2005) are merely a consequence of Cauchy’s relations for isotropic materials. We conclude with a discussion of the validity of peridynamic plane strain and plane stress models formulated from two-dimensional bond-based peridynamic models.

97 MATHEMATICS AND COMPUTING↗