Fundamental Linkage Between Structure, Electrochemical Properties, and Chemical Compositions of LiNi1-x-yMnxCoyO2 Cathode Materials
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99 GENERAL AND MISCELLANEOUS↗
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Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques
By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.
simplex, compositional data analysis, balance, log↗
Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture
Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.
54 ENVIRONMENTAL SCIENCES↗
Prediction of intrinsic topological superconductivity in Mn-doped GeTe monolayer from first-principles
The recent discovery of topological superconductors (TSCs) has sparked enormous interest. The realization of TSC requires a delicate tuning of multiple microscopic parameters, which remains a great challenge. Here, we develop a first-principles approach to quantify realistic conditions of TSC by solving self-consistently Bogoliubov-de Gennes equation based on a Wannier function construction of band structure, in presence of Rashba spin-orbit coupling, Zeeman splitting and electron-phonon coupling. We further demonstrate the power of this method by predicting the Mn-doped GeTe (Ge 1- x Mn x Te) monolayer—a well-known dilute magnetic semiconductor showing superconductivity under hole doping—to be a Class D TSC with Chern number of -1 and chiral Majorana edge modes. By constructing a first-principles phase diagram in the parameter space of temperature and Mn concentration, we propose the TSC phase can be induced at a lower-limit transition temperature of ~40 mK and the Mn concentration of x ~0.015%. Our approach can be generally applied to TSCs with a phonon-mediated pairing, providing useful guidance for future experiments.
Chemistry↗
A Methodology to Support the Development of a New State Vision for the U.S. Nuclear Industry
Recent changes in natural gas prices combined with reduced capital costs for solar and wind systems has created challenges for the continued operation of existing nuclear power plants (NPPs) in the United States. A new strategy in the way in which U.S. NPPs are operated, maintained, and supported is needed. One such strategy is to transform the NPP operating model through a business-driven approach that leverages technology to enable new capabilities that improve performance and reduce costs. This paper presents a methodology for developing an achievable yet transformative new state vision that ensures the continued safe and efficient operations of the U.S. NPP fleet. Here this work builds on existing guidance and leverages previous research to comprehensively address both utility needs and high-level human factors engineering design principles when developing a new state vision. The proposed methodology is intended to provide industry-wide guidance for developing a new state vision that leverages both the selected vendor’s capabilities in a way that meets the utility’s modernization goals while ensuring state-of-the-art systems engineering and human factors engineering principles are applied that promote overall plant safety, performance, and efficiency.
99 GENERAL AND MISCELLANEOUS↗
Design of nematic liquid crystals to control microscale dynamics
The dynamics of small particles, both living such as swimming bacteria and inanimate, such as colloidal spheres, has fascinated scientists for centuries. If one could learn how to control and streamline their chaotic motion, that would open technological opportunities in the transformation of stored or environmental energy into systematic motion, with applications in micro-robotics, transport of matter, guided morphogenesis. This review presents an approach to command microscale dynamics by replacing an isotropic medium with a liquid crystal. Orientational order and associated properties, such as elasticity, surface anchoring, and bulk anisotropy, enable new dynamic effects, ranging from the appearance and propagation of particle-like solitary waves to self-locomotion of an active droplet. By using photoalignment, the liquid crystal can be patterned into predesigned structures. In the presence of the electric field, these patterns enable the transport of solid and fluid particles through nonlinear electrokinetics rooted in anisotropy of conductivity and permittivity. Director patterns command the dynamics of swimming bacteria, guiding their trajectories, polarity of swimming, and distribution in space. This guidance is of a higher level of complexity than a simple following of the director by rod-like microorganisms. Namely, the director gradients mediate hydrodynamic interactions of bacteria to produce an active force and collective polar modes of swimming. The patterned director could also be engraved in a liquid crystal elastomer. When an elastomer coating is activated by heat or light, these patterns produce a deterministic surface topography. The director gradients define an activation force that shapes the elastomer in a manner similar to the active stresses triggering flows in active nematics. Finally, the patterned elastomer substrates could be used to define the orientation of cells in living tissues. The liquid-crystal guidance holds a major promise in achieving the goal of commanding microscale active flows.
36 MATERIALS SCIENCE↗
Wall diffuser velocity effects on American Shad ( Alosa sapidissima ) inside a fishway entrance channel
Attraction water for fishways is typically introduced through a diffuser inside the entrance channel, often through the floor or wall. In the spring of 2019, this laboratory study examined how 151 adult American Shad (Alosa sapidissima) responded to different gross velocities through a wall diffuser inside a full-scale fishway entrance channel. Two velocity conditions were studied, 0.152 m/s and 0.305 m/s, both without turning vanes inside the auxiliary water channel. The fish were tracked using the passive integrated transponder telemetry technique. The results of the experiments showed no difference in American Shad behavior when exhibited to the low and high velocity treatments. Moreover, shad passed the diffuser in roughly 3 out of every 4 attempts, regardless of the treatment. However, the similarity in shad behavior and passage performance is believed to be more of a result of the similarity in flow fields that resulted from the lack of flow guidance devices inside the auxiliary water channel. Furthermore, these findings therefore highlight the importance of properly maintained flow guidance devices, an often-overlooked component of an auxiliary water system.
13 HYDRO ENERGY↗
Dynamics and chemical mode analysis of plasma thermal-chemical instability
The stability of the weakly ionized plasma and the transition from a stable homogeneous discharge to unstable filaments play an important role in gas laser physics, plasma-assisted combustion, chemical reforming, and material synthesis. Here, theoretical stability analysis and thermal-chemical mode analysis were performed to understand the mechanism of plasma thermal-chemical instability by using a zero-dimensional plasma system with both simplified and detailed chemical kinetics of H 2 /O 2 /N 2 mixtures. The plasma dynamic and kinetic models accounted for multiple physical mechanisms in the chemically-reactive weakly ionized plasma, including ionization, attachment/detachment, recombination, vibrational and electronic energy relaxation, convective and diffusive species/heat removal, Joule heating, and detailed chemical kinetics. An analytical criterion and the explosive mode species/temperature pointers were formulated while the representative active species were identified for different thermal-chemical modes. The results showed that in addition to the classical thermal-ionization mechanism, various chemical modes from chemical heat imbalance and elementary kinetics significantly modified the time dynamics and the stability of the weakly ionized plasma. The present analysis provides insights and guidance to control plasma instability using chemical kinetics.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs
Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data
Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source-receiver observation geometry. Here, we develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.
58 GEOSCIENCES↗
Imaging the structural organization of chemical elements in growth cones of developing hippocampal neurons
Abstract During neurodevelopment, neurons form growth cones, F-actin rich extensions located at the distal end of the neurites. Growth cones allow dendrites and axons to build synaptic connections through a process of neurite guidance whose mechanisms have not been fully elucidated. Calcium is an important element in this process by inducing F-actin reorganization. We hypothesized that other biologically active elements might be involved in the growth cone-mediated neurite guidance mechanisms. We performed super resolution and confocal microscopy of F-actin, followed by synchrotron X-ray fluorescence microscopy of phosphorous, sulfur, chlorine, potassium, calcium, iron and zinc on growth cones from primary rat hippocampal neurons. We identified two main patterns of element organization. First, active growth cones presenting an asymmetric distribution of Ca co-localized with the cytoskeleton protein F-actin. In active growth cones, we found that the distributions of P, S, Cl, K, and Zn are correlated with Ca. This correlation is lost in the second pattern, quiescent growth cones, exhibiting a spread elemental distribution. These results suggest that Ca is not the only element required in the F-actin rich active regions of growth cones. In addition, highly concentrated Fe spots of submicrometer size were observed in calcium-rich areas of active growth cones. These results reveal the need for biological active elements in growth cones during neural development and may help explain why early life deficiencies of elements, such as Fe or Zn, induce learning and memory deficits in children.
60 APPLIED LIFE SCIENCES↗
Efficient boundary-guided scanning for high-resolution X-ray ptychography
In the realm of X-ray ptychography experiments, a considerable amount of ptychography scans are typically performed within a field of view encompassing the target sample. While it is crucial to obtain overlapping scans in small increments over the region of interest for achieving high-resolution sample reconstruction, a significant number of these scans often redundantly measure the empty background within the wide field of view. To address this inefficiency, an innovative algorithm is proposed that introduces automatic guidance for data acquisition. The algorithm first directs the scan point to actively search for the object of interest within the field of view. Subsequently, it intelligently scans along the perimeter of the sample, strategically acquiring measurements exclusively within the boundary of the region of interest. By employing this approach, a reduction in the number of measurements required to obtain high-resolution reconstruction images is demonstrated, as compared with conventional raster scanning methods. Furthermore, the automatic guidance provided by the algorithm offers the added advantage of saving valuable time during the reconstruction process. Through practical implementation on real experiments, these findings showcase the efficacy of the proposed algorithm in enhancing the efficiency and accuracy of X-ray ptychography experiments. This novel approach holds immense potential for advancing sample analysis and imaging techniques in various scientific disciplines.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Global harmonization of immediate‐release solid oral drug product bioequivalence recommendations and the impact on generic drug development
Immediate-release (IR) solid oral drug products constitute a significant portion of approved drug products and products under development. Bioequivalence (BE) assessment for these oral products is important for establishing therapeutic equivalence for generic products to their respective comparator products. In December 2022, the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) published the first new draft guideline on BE for IR solid oral dosage forms (M13A). To support the development of ICH M13A, we comprehensively reviewed the landscape of oral IR products approved by the U.S. Food and Drug Administration (FDA) and compared BE recommendations for these products in the current U.S. FDA and European Medicines Agency (EMA) BE guidances. We utilized databases including Drugs@FDA, Orange Book, and product-specific guidances (PSGs) published on the U.S. FDA and EMA websites to collect information. Oral IR products account for 46% of all FDA-approved new drug applications currently listed in Orange Book with 82.5% solids, 0.9% semi-solids, and 16.6% liquids. For all published U.S. FDA PSGs for solid oral IR products, in vivo BE studies with pharmacokinetic (PK) endpoints account for 88% of BE approaches recommended. Of these PK BE studies, 86.5% recommended fasting and fed BE studies, while only 15.9% EMA PSGs recommended both fasting and fed BE studies. This review helps clarify the scope of U.S. solid oral IR products impacted by the new ICH M13A draft guideline and demonstrates how recommendations in draft ICH M13A could significantly harmonize BE recommendations for IR oral products to facilitate global drug development.
60 APPLIED LIFE SCIENCES↗
Oxidation and microstructure of SiC f /SiC composites in moist air up to 1600°C by X‐ray tomographic characterization
Abstract SiC f /SiC composites that possess PyC or BN interface layers were fabricated and then oxidized in moist air at 1000, 1200, 1400, and 1600°C. High‐resolution CT was used for capturing 3D images and quantifying the SiC phase, mesophase, and voids. The oxidation behavior and microstructural evolution of SiC f /SiC with PyC or BN interface are discussed in this study. The microstructure of the SiC f /SiC with a PyC layer was seriously damaged in moist air at high temperature, whereas the BN interface layer enhanced the oxidation resistance of the SiC f /SiC. These results are also confirmed by using XRD, oxidation mass gain, tensile testing, and SEM measurements. The results of the oxidation behavior and microstructural evolution for SiC f /SiC oxidized in dry air are also compared with the results of this study. Comparing the SiC f /SiC with a PyC interface layer, the composite with a BN interface layer oxidized in moist air exhibits a high void growth rate and a low SiO 2 grain growth rate from 1000 to 1600°C. This work will provide guidance for predicting the service life of SiC f /SiC for multiscale damage rate models of materials at a local scale and will also provide guidance on the life service design of SiC f /SiC materials.
Lu, Zilong↗
Comparing Global Spray Combustion Characteristics and Local Shot-to-Shot Variations in a Reacting n -Heptane Spray
In support of efforts to develop improved models of turbulent spray behavior and combustion in diesel engines, experimental data and analysis must be obtained for guidance and validation. For Reynolds-averaged Navier–Stokes (RANS)-based Computational fluid dynamics (CFD) modeling approaches, representative ensemble average experimental results are important. For high-fidelity models such as large eddy simulations (LES)-based CFD, precise individual experimental results are desirable. However, making comparisons between a given experiment and LES is a challenge since local parameters cannot be directly compared. In this work, an optically accessible constant pressure flow rig (CPFR) is utilized to acquire diesel-like fuel injection and reaction behavior simultaneously with three optical diagnostic techniques: rainbow Schlieren deflectometry (RSD), OH* chemiluminescence (OH*), and two-color pyrometry (2CP). The CPFR allows a large number of repeated injection experiments to be performed for statistical analysis and convergence using ensemble-averaging techniques, while maintaining highly repeatable test conditions. Even for stable test conditions, variations in local turbulent fuel–air mixing introduce variability, which manifests as significant differences in OH* and 2CP results. Experimental measurements of characteristic parameters including liquid and vapor jet penetration, liftoff length, soot temperature and concentration, and turbulent flame speed, along with the shot-to-shot variability of each dataset, are presented and discussed. Finally, a statistical method is utilized to analyze the extent of this variability, and to identify superlative injections within the dataset for discussion and analysis of shot-to-shot variations.
42 ENGINEERING↗
HAZARD ANALYSIS OF DIGITAL ENGINEERED SAFETY FEATURES ACTUATION SYSTEM IN ADVANCED NUCLEAR POWER PLANTS USING A REDUNDANCY-GUIDED APPROACH
Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. This paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the triggers of potential single points of failure in the design of digital safety systems in advanced plant designs.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Successive Procedure for Solution Verification Based on User Needs
This paper discusses a revised solution verification procedure for computational fluid dynamics simulations to estimate the uncertainties in the quantities of interest based on discretization error models. This proposed procedure builds upon current procedures described in ASME V&V 20 but provides more guidance in determining the necessary number of mesh levels to build reliable discretization error models. Such guidance is particularly useful for practicing engineers without prior experience in solution verification. The key features of this proposed solution verification procedure are the ability to determine the need for additional mesh levels iteratively and the seamless treatment for underdetermined, exact, and overdetermined solutions of the power series approximation to the discretization error models. This study applies the proposed procedure to a set of synthetic examples to demonstrate the revised procedure’s clarity in determining the number of mesh solutions required for a reliable estimate of the discretization error in computational fluid dynamics settings. Additionally, this proposed procedure prevents a potential pathway in the current procedure in ASME V&V 20 that may lead to unreasonably small discretization errors.
Weinmeister, Justin↗
Anomalous absorption of electromagnetic waves by 2D transition metal carbonitride Ti 3 CNT x (MXene)
Lightweight, ultrathin, and flexible electromagnetic interference (EMI) shielding materials are needed to protect electronic circuits and portable telecommunication devices and to eliminate cross-talk between devices and device components. Here, we show that a two-dimensional (2D) transition metal carbonitride, Ti 3 CNT x MXene, with a moderate electrical conductivity, provides a higher shielding effectiveness compared with more conductive Ti 3 C 2 T x or metal foils of the same thickness. This exceptional shielding performance of Ti 3 CNT x was achieved by thermal annealing and is attributed to an anomalously high absorption of electromagnetic waves in its layered, metamaterial-like structure. These results provide guidance for designing advanced EMI shielding materials but also highlight the need for exploring fundamental mechanisms behind interaction of electromagnetic waves with 2D materials.
Science & Technology - Other Topics↗