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At least 523 records · Page 29

Creep of MARBN-type 9Cr martensitic steel in gaseous CO 2 environment

Here, with an interest in moving from steam to supercritical CO 2 as the working fluid in advanced energy systems, it is important to study the mechanical response of structural alloys to CO 2 -containing environments. MARBN-type 9Cr martensitic steel was originally developed for application in boilers for supercritical and ultra-supercritical power plants where the steam temperature reaches 650 °C. In this research, a MARBN-type 9Cr martensitic steel designed and manufactured at NETL was creep tested in a gaseous CO 2 environment (i.e., 0.1 MPa at 650 °C), and the results are directly compared to creep tests conducted in air. It was found that environmentally-assisted cracking facilitated by carbide formation beneath the growing oxide accelerated failure in gaseous CO 2 . This work indicates that creep-oxidation interactions in advanced martensitic steels represent an important consideration for materials selection in supercritical CO 2 power cycles. Furthermore, this work confirms that more oxidation-resistant alloys will be required for the highest temperature portions of these systems.

36 MATERIALS SCIENCE↗

A new paradigm in electron microscopy: Automated microstructure analysis utilizing a dynamic segmentation convolutional neutral network

Over the past half century, the transmission electron microscope enabled insight into the fundamental arrangements and structures of materials. State-of-the-art electron microscopes can acquire large image datasets across multiple imaging modalities. However, the manual annotation process for feature or defect quantification may not be feasible with the modern microscope. Convolutional neural networks emerged to characterize individual microstructural features from an image in a cost-effective, consistent manner. However, many of these neural network approaches rely on thousands to hundreds of thousands of manual annotations of each feature type across hundreds of images to train the network for adequate performance. This work focused on the development and application of a pixel-wise defect detection machine-learning dynamic segmentation convolutional neural network with associated automated acquisition and postprocessing to identify microstructural features rapidly and quantitatively from a small initial dataset incorporating multiple imaging modes. The approach was demonstrated for characterization of superalloy 718 from both single image acquisition on multiple detectors to in-situ evolution captured with a single detector on a standard desktop computer to demonstrate the low barrier to entry required for widespread adoption. Pixel-by-pixel class identification was excellent with strong identification of chemically distinct phases, structurally distinct phases, and defect structures, thus demonstrating the new paradigm of machine learning-assisted characterization.

36 MATERIALS SCIENCE↗

Sub-25 ps timing measurements with 10 × 10 cm 2 PICOSEC Micromegas detectors

The PICOSEC Micromegas detector is a precise timing gaseous detector based on a Cherenkov radiator coupled to a semi-transparent photocathode and a Micromegas amplifying structure. First single-pad prototypes demonstrated a time resolution below σ = 25 ps, however, to make the concept appropriate to physics applications, several developments are required. The objective of this work was to achieve an equivalent time resolution for a 10 × 10 cm 2 area PICOSEC Micromegas detector. The prototype was designed, produced and tested in the laboratory and successfully operated with a 80 GeV/c muon beam. Preliminary results for this device equipped with a CsI photocathode demonstrated a time resolution below σ = 25 ps for all measured pads. The time resolution was reduced to be below σ = 18 ps by decreasing the drift gap to 180 μm and using dedicated RF amplifier cards as new electronics. The excellent timing performance of the single-channel proof of concept was not only transferred to the 100-channel prototype, but even improved, making the PICOSEC Micromegas detector more suitable for large-area experiments in need of detectors with high time resolutions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Validation of SAS4A/SASSYS-1 for predicting steady-state single-phase natural circulation

The validation of system analysis codes for nuclear reactor systems is required for the development and application of these computational tools. Designed as a comprehensive system analysis code for advanced nuclear reactors, SAS4A/SASSYS-1 requires validation of its physics model for capturing single-phase natural circulation behavior. To support the validation of SAS4A/SASSYS-1, high-precision experiments are performed capturing steady-state single-phase natural circulation on a scaled facility with comprehensive instrumentation. In this work, dedicated tests are performed quantifying the critical modeling parameters, and a single-phase natural circulation benchmark dataset is obtained with well-documented uncertainty and comprehensive facility description. The validation is then performed against the dataset examining the capability of SAS4A/SASSYS-1 in simulating steady-state single-phase natural circulation. The experimental facility is modeled in the candidate code. Solution verification is performed using Richardson-extrapolation-based estimators which quantify and restrict numerical errors from discretization. Input uncertainty provided by the benchmark dataset is forward propagated through the candidate code, quantifying the output uncertainty in a Monte Carlo approach. The composition of the output uncertainty is also quantified through a variance-based sensitivity analysis. With the uncertainty quantified for each individual condition, a detailed comparison between the simulation results and experimental data is performed covering the whole dataset. The results show consistent agreement for all primary parameters. The current validation activity provides a valuable benchmark dataset for the validation of system analysis codes in capturing single-phase natural circulation and demonstrates satisfactory prediction capability of SAS4A/SASSYS1 for steady-state single-phase natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

From classical thermodynamics to phase-field method

Phase-field method is a density-based computational method at the mesoscale for modeling and predicting the temporal microstructure and property evolution during materials processes. The focus of this article is on connecting the most common phase-field equations to the very basic first and second laws of classical thermodynamics through rudimentary irreversible thermodynamics. It briefly discusses the relations of the continuum phase-field equations to their counter parts at the microscopic and atomic levels. It attempts to clarify the contributions of long-range elastic, electrostatic, and magnetic interactions to domain structure evolution during structural, ferroelectric, and ferromagnetic phase transformations by separating order parameter changes due to the presence of quasi-static fields and those arising from phase transformations. A few examples are presented to demonstrate the possibility of employing the phase-field method to provide guidance to designing materials for optimum properties or discovering novel mesoscale phenomena or new materials functionalities. Here, the article ends with a brief perspective on a number of potential future directions on the development and applications of phase-field method beyond its traditional applications to structural alloys.

36 MATERIALS SCIENCE↗

Language models for materials discovery and sustainability: Progress, challenges, and opportunities

Significant advancements have been made in one of the most critical branches of artificial intelligence: natural language processing (NLP). These advancements are exemplified by the remarkable success of OpenAI’s GPT-3.5/4 and the recent release of GPT-4.5, which have sparked a global surge of interest akin to an NLP gold rush. Here, in this article, we offer our perspective on the development and application of NLP and large language models (LLMs) in materials science. We begin by presenting an overview of recent advancements in NLP within the broader scientific landscape, with a particular focus on their relevance to materials science. Next, we examine how NLP can facilitate the understanding and design of novel materials and its potential integration with other methodologies. To highlight key challenges and opportunities, we delve into three specific topics: (i) the limitations of LLMs and their implications for materials science applications, (ii) the creation of a fully automated materials discovery pipeline, and (iii) the potential of GPT-like tools to synthesize existing knowledge and aid in the design of sustainable materials.

36 MATERIALS SCIENCE↗

On the quantitative characterization of weld microstructures

Here, a new technique to quantify grain shape and grain boundary curvature in the fusion zone (FZ) and the heat-effected zone (HAZ) of refractory metals and alloys has been developed. The application of this technique to quantify the effect of welding speed on these microstructural characteristics in simulated molybdenum welds is highlighted in this study. A 50% increase in weld speed more than doubles the fraction of grain segments in the fusion zone with orientations between 00 to 300 to the normal to the welding direction, with a corresponding 50% decrease in the fraction of grain segments oriented along the welding direction. This increase in weld speed also results in a reduction in grain size from approximately 120 µm to 84 µm along the WD at the FZ centerline. Grain boundary curvature is negative near the weld centerline and the edge of the fusion zone, indicating that with increasing distance from the weld centerline, the grain segments progressively rotate towards a direction normal to the welding direction at both locations. Presence of regions with relatively straight grain segments indicated by curvatures close to zero were identified in between the weld centerline and the edge of the FZ at all weld speeds.

36 MATERIALS SCIENCE↗

Art and Science of the Cellular Mesoscale

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.

59 BASIC BIOLOGICAL SCIENCES↗

Hydrodynamic irreversibility of non-Brownian suspensions in highly confined duct flow

The irreversible behaviour of a highly confined non-Brownian suspension of spherical particles at low Reynolds number in a Newtonian fluid is studied experimentally and numerically. In the experiment, the suspension is confined in a thin rectangular channel that prevents complete particle overlap in the narrow dimension and is subjected to an oscillatory pressure-driven flow. In the small cross-sectional dimension, particles rapidly separate to the walls, whereas in the large dimension, features reminiscent of shear-induced migration in bulk suspensions are recovered. Furthermore, as a consequence of the channel geometry and the development and application of a single-camera particle tracking method, three-dimensional particle trajectories are obtained that allow us to directly associate relative particle proximity with the observed migration. Companion simulations of a steadily flowing suspension highly confined between parallel plates are conducted using the force coupling method, which also show rapid migration to the walls as well as other salient features observed in the experiment. While we consider relatively low volume fractions compared to most prior work in the area, we nevertheless observe significant and rapid migration, which we attribute to the high degree of confinement.

42 ENGINEERING↗

Optimization Modeling for Advanced Syngas to Olefin Reactive Systems

Reactor designs with mixed catalysts play an important role in transforming a multiple reactor system to single-shot reactors. In addition to savings in capital and ease of implementation, single-shot reactors are useful to break equilibrium limitations, thereby increasing the yield and selectivity of desired product as shown in previous studies. However, the nonlinear and highly exothermic nature of mixed-catalyst systems makes it difficult for commercial process simulation and optimization tools to optimize these systems. This study describes the development and application of optimization strategies for mixed-catalyst, single-shot reactors for syngas to olefin (STO) processes. Finding the optimal catalyst distribution is challenging and requires advanced solution strategies for singular optimal control problems, which are poorly conditioned and often lead to flat response surfaces. The graded bed and partial-moving finite-element approaches are used to find the optimal catalyst distribution that maximizes the olefins yield. A 1.3% increase in the yield is observed from one zone to three zones. The yield further improves from three zones to the exact infinite dimensional solution by 0.2%. This improvement can be realized in practice by changing only the catalyst distribution, without any extra investment. Lastly, the results suggest that a mixed-catalyst single shot reactor bed can be applied to other reaction mechanisms to increase reactor performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Condensed Phase Water Molecular Multipole Moments from Deep Neural Network Models Trained on Ab Initio Simulation Data

Ionic solvation phenomena in liquids involve intense interactions in the inner solvation shell. For interactions beyond the first shell, the ion–solvent interaction energies result from the sum of many smaller-magnitude contributions that can still include polarization effects. Deep neural network (DNN) methods have recently found wide application in developing efficient molecular models that maintain near-quantum accuracy. In this work, we extend the DeePMD-kit code to produce accurate molecular multipole moments in the bulk and near interfaces. The new method is validated by comparing the DNN moments with those generated by ab initio simulations. The moments are used to compute the electrostatic potential at the center of a molecular-sized hydrophobic cavity in water. The results show that the fields produced by the DNN models are in quantitative agreement with the AIMD-derived values. These efficient methods will open the door to more accurate solvation models for large solutes such as proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strong Correlation Between Superconductivity and Ferromagnetism in an Fe-Chalcogenide Superconductor

The interplay among topology, superconductivity, and magnetism promises to bring a plethora of exotic and unintuitive behaviors in emergent quantum materials. The family of Fe-chalcogenide superconductors FeTe x Se 1–x are directly relevant in this context due to their intrinsic topological band structure, high-temperature superconductivity, and unconventional pairing symmetry. Despite enormous promise and expectation, the local magnetic properties of FeTe x Se 1–x remain largely unexplored, which prevents a comprehensive understanding of their underlying material properties. Exploiting nitrogen vacancy (NV) centers in diamond, here we report nanoscale quantum sensing and imaging of magnetic flux generated by exfoliated FeTe x Se 1–x flakes, demonstrating strong correlation between superconductivity and ferromagnetism in FeTe x Se 1–x . The coexistence of superconductivity and ferromagnetism in an established topological superconductor opens up new opportunities for exploring exotic spin and charge transport phenomena in quantum materials. The demonstrated coupling between NV centers and FeTe x Se 1–x may also find applications in developing hybrid architectures for next-generation, solid-state-based quantum information technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dithieno[3,2-c:3′,2′‑ h ][2,6]naphthyridine-4,9(5H,10H)-dione-Based Conjugated Polymers for High Stable n‑Type Organic Electrochemical Transistors

Amide/imide-based conjugated polymers have been utilized as n-type OECT materials and have demonstrated promising device performance. However, their performance remains insufficient in terms of both efficiency and stability, which limits their practical applications. The development of conjugated polymers based on amide and imide groups represents a promising approach to address this issue. Here, in this study, we introduced dithieno­[3,2-c:3′,2′-h]­[2,6]­naphthyridine-4,9­(5H,10H)-dione (TVTDA) into the design of the OECT materials for the first time. By copolymerizing it with (E)-2,2′-(ethene-1,2-diyl)­bis­(thiophene-3-carbonitrile), we prepared two polymers, TVTDA-2CNTVT-ST and TVTDA-2CNTVT-BR, which contain linear or branched ethylene glycol side chains, respectively. OECT devices based on these polymers demonstrate n-type charge transport characteristics, achieving promising μC* values of 7.17 and 26.5 F cm –1 V –1 s –1 for TVTDA-2CNTVT-ST and TVTDA-2CNTVT-BR, respectively. The higher electron mobility and μC* of TVTDA-2CNTVT-BR can be attributed to its mixed edge-on and face-on stacking mode, larger crystalline coherence length, and larger domain size in the thin film. To our delight, the OECT devices based on both polymers exhibit good operational stability after operating in an aqueous solution for 2000 s, with current retention rates exceeding 93%, representing the high level among the OECT devices based on amide/imide-conjugated polymers. Our study demonstrates that the TVTDA unit holds great potential for constructing high-performance n-type OECT materials.

36 MATERIALS SCIENCE↗

Kinetic and X-ray Absorption Spectroscopic Analysis of Catalytic Redox Cycles over Highly Uniform Polymetal Oxo Clusters

Metal–organic framework materials (MOFs) offer an opportunity for investigating catalytic properties of polymetal oxo clusters that are highly well defined and uniform in nature, in contrast to other classes of catalysts that may exhibit a propensity toward active site heterogeneity. We report herein a kinetic and X-ray absorption spectroscopy (XAS) analysis of the two-electron oxidation of CO over divalent metal sites in MIL-100(M = Fe, Cr) (MIL = Materials of Institut Lavoisier) materials carrying μ 3 -oxo bridged trimers, and connect observations about the kinetic relevance of redox steps to density functional theory (DFT) predictions published previously. The high degree of uniformity evident from in situ titration measurements leads to a congruence in mechanistic inferences made from steady-state catalytic, transient stoichiometric, isotopic exchange, and isotopic tracer data that all point to a sequential mechanism comprised of separate oxidation and reduction half-cycle steps conjoined by an active oxygen intermediate. In situ XAS data reinforce mechanistic conclusions derived from kinetic analysis, and suggest that the active oxygen intermediate may be more appropriately characterized as an iron-oxyl (Fe 3+ –O – ) rather than an iron-oxo (Fe 4+ =O 2– ) species. The Cr analogue of MIL-100 exhibits contrasting rate features that can be rationalized using an identical sequence of steps as MIL-100(Fe), but with a highly dissimilar set of kinetic parameters that can also be validated using transient stoichiometric experiments. The larger coverages of active oxygen intermediates on MIL-100(Cr) are consistent with predictions from prior DFT studies that suggest more stable and less reactive active oxygen species for metals with lower d-electron counts, and point to metal identity as a lever for precisely controlling the kinetic relevance of oxidation and reduction half-cycles in catalytic redox sequences over polymetal oxo clusters. Importantly, the results presented point to the utility of developing broadly applicable structure–catalytic property relationships over MOF nodes specifically, and highly uniform catalysts more generally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanocrystal Assemblies: Current Advances and Open Problems

Here we explore the potential of nanocrystals (a term used equivalently to nanoparticles) as building blocks for nanomaterials, and the current advances and open challenges for fundamental science developments and applications. Nanocrystal assemblies are inherently multiscale, and the generation of revolutionary material properties requires a precise understanding of the relationship between structure and function, the former being determined by classical effects and the latter often by quantum effects. With an emphasis on theory and computation, we discuss challenges that hamper current assembly strategies and to what extent nanocrystal assemblies represent thermodynamic equilibrium or kinetically trapped metastable states. We also examine dynamic effects and optimization of assembly protocols. Finally, we discuss promising material functions and examples of their realization with nanocrystal assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strain and Defect-Tailored Magnetotransport in NiCo 2 O 4 Thin Films and Freestanding Membranes

Magnetic spinel NiCo 2 O 4 is promising for developing spintronic applications due to its high magnetic Curie temperature, high spin polarization, fast spin dynamics, and strain-tunable magnetic anisotropy, while its electronic and magnetic properties depend sensitively on epitaxial strain and disorder. Here, in this study, we use epitaxial NiCo 2 O 4 thin films and freestanding NiCo 2 O 4 membranes as model systems to reveal the complex interplay of strain and defects in determining the metallicity and magnetotransport properties of the ferrimagnetic spinel. NiCo 2 O 4 on perovskite substrates and NiCo 2 O 4 membranes exhibit insulating behaviors and spin canting, in sharp contrast to the metallic NiCo 2 O 4 films on spinel substrates that possess strong perpendicular magnetic anisotropy. Anisotropic magnetoresistance studies provide critical information about disorder-induced spin scattering and strain-induced tetragonal magnetocrystalline anisotropy, which is corroborated by comprehensive electron microscopy characterizations. Our study presents a promising venue for designing flexible magnetic memory, sensor, and spintronic applications.

36 MATERIALS SCIENCE↗

Capacitive Deionization for the Extraction and Recovery of Butyrate

Separation processes underpin chemical manufacturing, energy and fuel production, resource recovery, and water purification. Capacitive deionization (CDI) is an electrochemical separation technique based on electrosorption of charged species from an aqueous solution. This work reports the development and application of CDI for the extraction and recovery of butyrate, a carboxylate anion that is key to bioenergy production, among other applications. Electrosorption of sodium butyrate was evaluated using a bench-scale CDI system with activated carbon cloth electrodes. Applying an external potential (1.2 V) enhanced the adsorption capacity of activated carbon for butyrate by 250%. Reversible electrosorption was also demonstrated by extracting and recovering butyrate at 1.2 and 0 V, respectively. Performance metrics including butyrate adsorption and desorption capacities, adsorption and desorption rates, charge efficiency, energy consumption, and recovery are reported. Furthermore, this study also investigates the long-term operational stability of the system by cycling the cell more than 1000 times using 1.2 and 0 V for charging and discharging, respectively. Subsequent physicochemical characterization indicates increased oxygen content (from similar to 2% to >8%), decreased specific surface area (by similar to 20%), and decreased pore volume (by similar to 20%), attributed to carbon oxidation. Overall, this work informs the design of CDI for organic anion separation and recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗