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Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles
Abstract The sciences struggle to integrate across disciplines, coordinate across data generation and modeling activities, produce connected open data, and build strong networks to engage stakeholders within and beyond the scientific community. The American Geophysical Union (AGU) is divided into 25 sections intended to encompass the breadth of the geosciences. Here, we introduce a special collection of commentary articles spanning 19 AGU sections on challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross‐system transferability of science outcomes. This article (a) summarizes the ICON principles; (b) discusses the crowdsourced approach to creating the collection; (c) explores insights from across the articles; and (d) proposes steps forward. There were common themes among the commentary articles, including broad agreement that the benefits of using ICON principles outweigh the costs, but that using ICON principles has important risks that need to be understood and mitigated. It was also clear that the ICON principles are not monolithic or static, but should instead be considered a heuristic tool that can and should be modified to meet changing needs. As a whole, the collection is intended as a resource for scientists pursuing ICON science and represents an important inflection point in which the geosciences community has come together to offer insights into ICON principles as a unified approach for improving how science is done across the geosciences and beyond.
Co-introduction of precipitate hardening and TRIP in a TWIP high-entropy alloy using friction stir alloying
Tuning deformation mechanisms is imperative to overcome the well-known strength-ductility paradigm. Twinning-induced plasticity (TWIP), transformation-induced plasticity (TRIP) and precipitate hardening have been investigated separately and have been altered to achieve exceptional strength or ductility in several alloy systems. In this study, we use a novel solid-state alloying method—friction stir alloying (FSA)—to tune the microstructure, and a composition of a TWIP high-entropy alloy by adding Ti, and thus activating site-specific deformation mechanisms that occur concomitantly in a single alloy. During the FSA process, grains of the as-cast face-centered cubic matrix were refined by high-temperature severe plastic deformation and, subsequently, a new alloy composition was obtained by dissolving Ti into the matrix. After annealing the FSA specimen at 900 °C, hard Ni–Ti rich precipitates formed to strengthen the alloy. An additional result was a Ni-depleted region in the vicinity of newly-formed precipitates. The reduction in Ni locally reduced the stacking fault energy, thus inducing TRIP-based deformation while the remaining matrix still deformed as a result of TWIP. Our current approach presents a novel microstructural architecture to design alloys, an approach that combines and optimizes local compositions such that multiple deformation mechanisms can be activated to enhance engineering properties.
Introduction of Chalcogenide Glasses to Additive Manufacturing: Nanoparticle Ink Formulation, Inkjet Printing, and Phase Change Devices Fabrication
Abstract Chalcogenide glasses are one of the most versatile materials that have been widely researched because of their flexible optical, chemical, electronic, and phase change properties. Their application is usually in the form of thin films, which work as active layers in sensors and memory devices. In this work, we investigate the formulation of nanoparticle ink of Ge–Se chalcogenide glasses and its potential applications. The process steps reported in this work describe nanoparticle ink formulation from chalcogenide glasses, its application via inkjet printing and dip-coating methods and sintering to manufacture phase change devices. We report data regarding nanoparticle production by ball milling and ultrasonication along with the essential characteristics of the formed inks, like contact angle and viscosity. The printed chalcogenide glass films were characterized by Raman spectroscopy, X-ray diffraction, energy dispersive spectroscopy and atomic force microscopy. The printed films exhibited similar compositional, structural, electronic and optical properties as the thermally evaporated thin films. The crystallization processes of the printed films are discussed compared to those obtained by vacuum thermal deposition. We demonstrate the formation of printed thin films using nanoparticle inks, low-temperature sintering and proof for the first time, their application in electronic and photonic temperature sensors utilizing their phase change property. This work adds chalcogenide glasses to the list of inkjet printable materials, thus offering an easy way to form arbitrary device structures for optical and electronic applications.
Expanding Uranyl Peroxide Cluster Chemistry via the Introduction of Superoxide Radicals
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Chapter 1: Introduction - Motivation of Polycrystalline Thin-Film Solar Cells
Thin-film solar cell development may be conceptualized as improving processes to lower costs and improve performance, with characterization as a guide along the way. Yet, pushing the boundaries of characterization is as much at the core of thin-film solar cell development as material synthesis. As PV continues to mature, there is an endless drive to improve performance to compete. Hence, PV technology is striving for increasing levels of perfection, requiring a corresponding sophistication in characterization and understanding. Consequently, the topic of this book -advanced characterization-is timely and critical to develop the potential of thin-film solar technology.
An introduction to Spent Nuclear Fuel decay heat for Light Water Reactors: a review from the NEA WPNCS
This paper summarized the efforts performed to understand decay heat estimation from existing spent nuclear fuel (SNF), under the auspices of the Working Party on Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. Needs for precise estimations are related to safety, cost, and optimization of SNF handling, storage, and repository. The physical origins of decay heat (a more correct denomination would be decay power) are then introduced, to identify its main contributors (fission products and actinides) and time-dependent evolution. Due to limited absolute prediction capabilities, experimental information is crucial; measurement facilities and methods are then presented, highlighting both their relevance and our need for maintaining the unique current full-scale facility and developing new ones. The third part of this report is dedicated to the computational aspect of the decay heat estimation: calculation methods, codes, and validation. Different approaches and implementations currently exist for these three aspects, directly impacting our capabilities to predict decay heat and to inform decision-makers. Finally, recommendations from the expert community are proposed, potentially guiding future experimental and computational developments. One of the most important outcomes of this work is the consensus among participants on the need to reduce biases and uncertainties for the estimated SNF decay heat. If it is agreed that uncertainties (being one standard deviation) are on average small (less than a few percent), they still substantially impact various applications when one needs to consider up to three standard deviations, thus covering more than 95% of cases. The second main finding is the need of new decay heat measurements and validation for cases corresponding to more modern fuel characteristics: higher initial enrichment, higher average burnup, as well as shorter and longer cooling time. Similar needs exist for fuel types without public experimental data, such as MOX, VVER, or CANDU fuels. A third outcome is related to SNF assemblies for which no direct validation can be performed, representing the vast majority of cases (due to the large number of SNF assemblies currently stored, or too short or too long cooling periods of interest). A few solutions are possible, depending on the application. For the final repository, systematic measurements of quantities related to decay heat can be performed, such as neutron or gamma emission. This would provide indications of the SNF decay heat at the time of encapsulation. For other applications (short- or long-term cooling), the community would benefit from applying consistent and accepted recommendations on calculation methods, for both decay heat and uncertainties. This would improve the understanding of the results and make comparisons easier.
Introduction to special issue: Colloidal quantum dots
The quantum confinement effect has driven the development and exploration of colloidal semiconductor nanocrystals over approximately the past three decades. These semiconductor nanostructures are typically synthesized as stable colloidal dispersions in solution-phase chemical batch reactions at relatively low temperatures. Researchers have developed a wide range of reaction conditions to produce a variety of shapes, compositions, and structures with well-controlled sizes and low polydispersities. The shape can be controlled to produce confinement in one, two, or all three spatial dimensions, the latter defining a “quantum dot.” Combining two or more semiconductors within the various nanostructures produces additional optical and electronic degrees of freedom. These mixed compositional nanostructures have properties not accessible in bulk semiconductor systems. Further, researchers have fabricated novel nanoheterostructures, such as “dot-in-rods,” quantum wells, core/shell structures, giant-core/shell tetrapods where the core is one material and the arm is another, Janus structures that consist of spherical structures with well-defined internal heterostructures, nano-dumbbells, hollow-core structures, and many other novel and interesting structures. The structural variations are seemingly only limited by the creativity of the various researchers engaged in these endeavors.
Introduction to the special topic on inertial confinement fusion diagnostics
In the first decade of the 21st century, the United States began operating three leading Inertial Confinement Fusion (ICF) and High-Energy Density Physics (HEDP) facilities. The National Ignition Facility (NIF) began its quest to first surpass the Lawson Criterion and then reach thermonuclear ignition and thermonuclear gain. The Omega EP (Extended Performance) laser provides unprecedented energy, reliability, and consistency for petawatt (PW)-class laser experiments. The Omega laser continues to support over 1000 ICF and HEDP experiments each year. The Z pulsed power machine is a Z-pinch plasma confinement device that was refurbished to increase current drive and improve reliability. The extreme states of matter created in these new facilities required advancement of many technologies. The most important among these was the significant improvement in instrumentation capabilities needed to diagnose plasma conditions and resulting nuclear products. The instruments needed a better temporal, spatial, and energy resolution. They also needed to be hardened against EMP and radiation. Typical events in an ICF implosion include compressing the deuterium–tritium (DT) fuel to greater than 60 g/cm 3 and heating the DT to a temperature greater than 10 keV (110 000 000 K). The DT atoms react to produce 14 MeV neutrons from a volume with a radius of ~30 μm. When the fuel ignites, the DT burn prop agates into cold fuel and the neutron-emitting region can reach sizes of over 200 μm. Furthermore, the burn typically lasts less than 150 ps, but the burn duration will decrease as the DT yield increases. Burn durations as short as 90 ps have been recorded and are predicted to decrease still further to 20 ps. X-ray imaging diagnostics are needed to measure the acceleration and velocity of the capsule enclosing the DT, where the implosion velocities can reach over 400 km/s.
An Introduction to Superconducting Tunnel Junction Radiation Detectors
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Learning dynamical systems from data: An introduction to physics-guided deep learning
Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely on strong modeling assumptions and expensive numerical integration, requiring significant computational resources and domain expertise. While deep learning (DL) provides efficient alternatives for modeling complex dynamics, they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret. Physics-guided DL aims to integrate first-principled physical knowledge into data-driven methods. It has the best of both worlds and is well equipped to better solve scientific problems. Recently, this field has gained great progress and has drawn considerable interest across discipline Here, we introduce the framework of physics-guided DL with a special emphasis on learning dynamical systems. We describe the learning pipeline and categorize state-of-the-art methods under this framework. We also offer our perspectives on the open challenges and emerging opportunities.
Introduction of the Adding and Doubling Method for Solving Bateman Equations for Nuclear Fuel Depletion
This paper introduces and evaluates the Adding and Doubling Method (ADM) for solving the Bateman equations for depletion systems with varying numbers of nuclides and compares it to the Chebyshev Rational Approximation Method (CRAM), both implemented in the reactor physics analysis application Griffin. ADM, when applied to the Crank-Nicolson Finite Difference method, can produce results comparable in accuracy and precision to CRAM with comparable run times for systems with 35 or 297 nuclides. For systems with more than 300 nuclides, the matrix-matrix operations required by ADM are significantly more costly than the matrix-vector operations required by CRAM, making CRAM the more efficient method for systems with large numbers of nuclides. ADM is an accurate method that maintains other advantages over CRAM in that it does not depend on pre-generated coefficients or require complex number operations. ADM also manages to outperform CRAM by a factor of more than 250 in terms of run time for depletion systems that require multiple Bateman solves while the depletion matrix and time step size remain constant over all depletion intervals.
Introduction, Investigation, and Experimental Validation of a Novel Passive Neutron Spectrometer
Unfolding neutron energy spectra are instrumental for determining personal health effects and calculating dose received. This area of study is heavily researched, and Lawrence Livermore National Laboratory (LLNL) is investigating a passive neutron spectrometer for the purpose of acquiring the information needed to determine personnel dose in the event of a criticality accident. A part of this investigation is presented in this article through the examination of four experimental detector responses (DRs). These four DRs were acquired in the presence of 252 Cf, AmBe, GODIVA, and National Ignition Facility (NIF) neutron sources. An algorithm developed at LLNL was used to unfold the neutron fluence from each of the four DRs, and subsequently, fluence-to-dose conversion factors provided by the American National Standards Institute were used to calculate dose. Additionally, a multistep unfolding process was developed and employed to calculate the effects of both direct (from the source) and indirect (from room return) neutrons. The average error when unfolding the direct DR was less than 8%. The dose from 252 Cf was predicted with only 8% error. The multistep approach allowed for the identification of the low-energy neutrons in the 252 Cf, AmBe, and NIF DRs.
Introduction to Special Issue on the Early History of Nuclear Fusion
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The exploration of hot and dense nuclear matter: introduction to relativistic heavy-ion physics
Abstract This article summarizes our present knowledge about nuclear matter at the highest energy densities and its formation in relativistic heavy ion collisions. We review what is known about the structure and properties of the quark-gluon plasma and survey the observables that are used to glean information about it from experimental data.
Preliminary Introduction of a Free Vortex Wake Method Into OpenFAST
Increasing wind turbine size can have substantial economic benefits. However, increasing wind turbine turbine size requires the use of models that accurately capture the aerodynamic response to large deflections and nonstraight blade geometries. Additionally, the installation of offshore floating turbines requires turbine models that can handle large rotor motion. Free vortex wake (FVW) methods are capable of modeling this type of complex physics while remaining computationally tractable to perform the many simulations necessary for turbine design. In this work, a FVW model is added to the National Renewable Energy Laboratory engineering tool OpenFAST to allow for the aerodynamic modeling of highly flexible turbines along with the aero-hydro-servo-elastic response capabilities of OpenFAST. Code implementation is not complete and thus no results are presented. However, areas of potential modeling improvement are discussed, such as modifications to the circulation calculation and the need for different FVW input model specifications when high-thrust cases are being modeled.