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31 records · Page 2

Effects of low-temperature neutron irradiation on the microstructure and tensile properties of duplex 2304 stainless steel and its electron-beam welds

A lean duplex stainless steel material (2304-grade) in its base metal and electron beam (e-beam) welded conditions were studied microstructurally and mechanically as a function of irradiation conditions to evaluate its use as a structural material at low temperatures (60–100 °C). Neutron irradiation up to a fluence of 1.40 × 10 19 n/cm 2 (E > 0.1 MeV) or ~0.011 dpa decreased the total elongation of both base metal and e-beam welded samples. Overall, radiation hardening was observed in all the samples. The transversely cut irradiated samples showed some nonuniform quasi-cleavage and shearing in their fracture surfaces, indicating the variance of ductile nature of the two-phased (deformable austenite and harder ferrite) duplex structure. The e-beam welded samples also showed quasi-cleavage fracture, which is a characteristic of radiation-induced embrittlement. Furthermore, these observations of the e-beam welded samples were attributed to the formation of coarse ferrites, grain boundary and intragranular phases such as γ 2 and γ 3 , and minor impurity phases such as CrN and Cr 2 N in the weld pool and/or heat-affected zone of the samples. Radiation-induced elemental segregation was also identified in the post-irradiated base metal.

36 MATERIALS SCIENCE↗

pvlib iotools—Open-source Python functions for seamless access to solar irradiance data

Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radiation models, and validating irradiance datasets. However, lack of standardization in data formats and access interfaces across providers constitutes a major barrier to entry for new users. pvlib python’s iotools subpackage aims to solve this issue by providing standardized Python functions for reading local files and retrieving data from external providers. All functions follow a uniform pattern and return convenient data outputs, allowing users to seamlessly switch between data providers and explore alternative datasets. The pvlib package is community-developed on GitHub: https://github.com/pvlib/pvlib-python. As of pvlib python version 0.9.5, the iotools subpackage supports 12 different datasets, including ground measurement, reanalysis, and satellite-derived irradiance data. The supported ground measurement networks include the Baseline Surface Radiation Network (BSRN), NREL MIDC, SRML, SOLRAD, SURFRAD, and the US Climate Reference Network (CRN). Additionally, satellite-derived and reanalysis irradiance data from the following sources are supported: PVGIS (SARAH & ERA5), NSRDB PSM3, and CAMS Radiation Service (including McClear clear-sky irradiance).

14 SOLAR ENERGY↗

High-temperature corrosion of a nickel-based alloy in a molten chloride environment – The effect of thermal and chemical purifications

There is currently an ever-increasing demand for higher process efficiencies in next generation (Gen3) concentrating solar power (CSP). Higher process efficiencies may be procured by increasing the operating temperature, and simultaneously, minimizing the degradation of materials used for construction of CSP plants (e.g., piping, thermal storage tanks, solar receivers and heat exchangers). Thus, understanding materials corrosion in the presence of molten salt mixtures used as thermal energy storage media and heat transfer fluids is indispensable for CSP development. The present paper provides insights into the effects of salt purification on the corrosion of a nickel-based alloy (Haynes 230) isothermally exposed to a stagnant chloride-based salt mixture at 800 °C. The MgCl 2 -based salt mixture was thermally dehydrated and chemically treated with (0.1 and 0.5 wt %) elemental magnesium. Results reveal the electrochemical nature of the corrosion process, and the formation of corrosion products such as oxides (MgO, MgCr 2 O 4 , and MgAl 2 O 4 ) and nitrides (CrN) on the alloy surface and in sub-surface regions. Magnesium additions enhanced the ability to resist corrosion by reducing the concentration of impurities (H 2 O, MgOH + , OH - species) and polarizing the alloy surface. The formation of nitrides in all cases studied indicates the impact of using nitrogen as a protective gas in the system. Results also reveal that a single step treatment of the salt using metallic Mg could be considered as a measure to control the salt's impurity level, e.g., if required for system control.

14 SOLAR ENERGY↗

Wear penalty for steel rubbing against hard coatings in reactive lubricants due to tribochemical interactions

Hard coatings and surface adsorptive/reactive lubricants are two common strategies for improving wear protection, but what if they are used together? In this study, steel-steel and steel-coating sliding was investigated in boundary lubrication of polar and non-polar oils containing a ZDDP or an ionic liquid. Two hard coatings, diamond-like-carbon (DLC) and chromium nitride (CrN), were used. Furthermore, for a steel-steel contact, wear was effectively reduced by using a more surface reactive lubricant, as expected. However, the steel ball wear was increased against a hard coating and further worsened with a more polar oil and/or a more surface reactive additive. The wear mechanism is proposed as a combined effect of physicochemical interactions with the lubricant, mechanical polishing by the counterface, and material adhesion.

36 MATERIALS SCIENCE↗

Synthesis and Physical Properties of Manganese Chromium Nitride Thin Films Grown via Molecular Beam Epitaxy

Here, we demonstrate the ability to grow epitaxial thin films of manganese–chromium nitride (Mn x Cr 1–x N) across the entire composition range on magnesium oxide (MgO) (1 0 0) surfaces by molecular beam epitaxy. By independently controlling the ratio of the atomic fluxes of manganese and chromium, the compositional dependence of structural and electrical transport properties is determined. Soft X-ray absorption shows that the valence states of Cr( 3+ ) and Mn( 3+ ) remain identical among these MnCrN epitaxial films. The metallic transport behavior of binary manganese nitride (MnN) and chromium nitride (CrN) is suppressed in the ternary alloys. Changes in room temperature electrical resistivity of up to 100 times and 5 orders of magnitude at cryogenic temperatures are observed. This work expands the variety of nitride compounds available for epitaxial integration and could provide additional flexibility for the development of metal–semiconductor–insulator junctions for spintronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Amorphous materials exhibit various characteristics that are not featured by crystals and can sometimes be tuned by their degree of disorder (DOD). Here, we report results on the mechanical properties of monolayer amorphous carbon (MAC) and monolayer amorphous boron nitride (maBN) with different DOD. The pertinent structures are obtained by kinetic-Monte-Carlo (kMC) simulations using machine-learning potentials (MLP) with density-functional-theory (DFT)-level accuracy. An intuitive order parameter, namely the areal fraction F x occupied by crystallites within the continuous random network, is proposed to describe the DOD. We find that F x captures the essence of the DOD: Samples with the same F x but different sizes and arrangements of crystallites, obtained using two distinct kMC procedures, have virtually identical radial distributions functions as well as bond-length and bond-angle distributions. Furthermore, by simulating the fracture process with molecular dynamics, we found that the mechanical responses of MAC and maBN before fracture are mainly determined by F x and are insensitive to the sizes and specific arrangements and to some extent the numbers and area distributions of the crystallites. The behavior of cracks in the two materials is analyzed and found to mainly propagate in meandering paths in the CRN region and to be influenced by crystallites in distinct ways that toughen the material. Furthermore, the present results reveal the relation between structure and mechanical properties in amorphous monolayers and may provide a universal toughening strategy for 2D materials.

2-dimensional systems↗

Room-Temperature Ferromagnetism at an Oxide-Nitride Interface

Heterointerfaces have led to the discovery of novel electronic and magnetic states because of their strongly entangled electronic degrees of freedom. Single-phase chromium compounds always exhibit antiferromagnetism following the prediction of the Goodenough-Kanamori rules. So far, exchange coupling between chromium ions via heteroanions has not been explored and the associated quantum states are unknown. In this work, we report the successful epitaxial synthesis and characterization of chromium oxide (Cr 2 O 3 )-chromium nitride (CrN) superlattices. Room-temperature ferromagnetic spin ordering is achieved at the interfaces between these two antiferromagnets, and the magnitude of the effect decays with increasing layer thickness. First-principles calculations indicate that robust ferromagnetic spin interaction between Cr 3+ ions via anion-hybridization across the interface yields the lowest total energy. This work opens the door to fundamental understanding of the unexpected and exceptional properties of oxide-nitride interfaces and provides access to hidden phases at low-dimensional quantum heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗

Catalyst: Fast and flexible modeling of reaction networks

We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.

59 BASIC BIOLOGICAL SCIENCES↗

Intergranular Corrosion of Feedstock Modified—Additively Manufactured Stainless Steel After Sensitization

Laser powder bed fusion (LPBF), a metal additive manufacturing technique, was conducted on feedstock-modified 316L stainless steel (316L) powder produced by ball-milling of commercial 316L and 1 wt% additive (cerium oxide—CeO 2 , lanthanum (III) nitrate hexahydrate—La(NO 3 ) 3 ·6H 2 O, and chromium nitride—CrN). The feedstock-modified LPBF-316L specimens were sensitized at 675°C for 24 h, and the influence of additives on intergranular corrosion (IGC) was investigated following ASTM G108-94 and A262-14 standards. The LPBF-316L with La(NO 3 ) 3 ·6H 2 O showed higher IGC resistance. Furthermore, the microstructure of the LPBF specimen was investigated and correlated to understand the improved IGC resistance of LPBF-316L with La(NO 3 ) 3 ·6H 2 O additive.

36 MATERIALS SCIENCE↗

Friction Stir Processed Repair Welding of Dry Storage Canisters and Mitigation Strategies: Effect of Engineered Barrier Layer on Environmental Degradation

The proposed project aims to develop a friction sir based repair technique to heal cracks of stainless steel dry storage canisters (DSCs), created by the effect of stress corrosion cracking (SCC). In real service conditions, the welded parts of the canisters become prone to SCC under exposure to aggressive chemical environment. The focus of the project is on developing a mitigation strategy that can be implemented for countering SCC in DSCs following a two-pronged approach: (i) apply friction stir processing (FSP) as a crack repair technique while creating compressive residual stresses at the canister material surface, thus improving resistance against SCC; (ii) add molybdenum and/or nitrogen by friction stir based alloying process to create compositions that improve pitting resistance and thus enhance resistance against SCC. The specific project objectives are listed below: • Investigate FSW of 304L SS a potential repair welding technique of dry storage canisters; • Optimize the FSW parameters to introduce surface compressive stress profiles in the weldments; • Develop a FSP method to surface alloy the 304L with nitrogen and Mo by adding CrN and Mo powders; • Evaluate the surface compressive residual stress profile during FSW and FSP processes; • Evaluate the localized corrosion resistance of the FSW and FSP samples as a function of temperature, chloride concentration, and surface alloy composition; • Evaluate the SCC behavior of the FSW and FSP samples as a function of stress, chloride concentration, and temperature at different surface chemistries and induced residual stress profiles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ChemComp: Compiling and Computing with Chemical Reaction Networks

The exponential growth in computing demands driven by scientific computing, data analytics, and artificial intelligence is pushing conventional CMOS-based high-performance computing systems to their physical and energy efficiency limits. As we approach the era of post-exascale computing, disruptive approaches are necessary to overcome these barriers and achieve substantial gains in energy efficiency. Analog and hybrid digital-analog computing systems have emerged as promising alternatives, offering the potential for orders-of-magnitude improvements in efficiency. Among these, biochemical computing stands out as a novel paradigm capable of leveraging the natural efficiency of chemical reactions, which have shown promise in solving optimization problems by converging to steady states. By scaling up reaction networks or reaction vessel sizes, biochemical systems present an opportunity to meet the high-performance demands of modern computing tasks. Despite their promise, significant theoretical and practical challenges remain, particularly in formulating and mapping computational problems to chemical reaction networks (CRNs) and designing viable biochemical computing devices. This paper addresses these challenges by introducing new ideas to ChemComp, a compilation and emulation framework for chemical computation. This work describes the mechanisms through which solutions to ordinary differential equations (ODEs) that can be represented as CRN systems can be achieved. Furthermore, we explain the design principles of an ODE dialect implemented as a multi-level intermediate representation (MLIR) compiler extension that will be coupled with existing infrastructure. We demonstrate the potential of our framework through a case study emulating a simplified chemical reservoir computing device. This work establishes foundational tools and methodologies necessary to harness the computational power of chemistry, paving the way for the development of energy-efficient, high-performance computing systems tailored to contemporary and future computational needs.

Bohm Agostini, Nicolas↗