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At least 721 records · Page 40

Charge Density Waves and Electronic Properties of Superconducting Kagome Metals

We report that kagome metals AV 3 Sb 5 (A = K, Rb, and Cs) exhibit intriguing superconductivity below 0.9 ~ 2.5 K, a charge density wave (CDW) transition around 80 ~ 100 K, and $\mathbb{Z}$ 2 topological surface states. The nature of the CDW phase and its relation to superconductivity remains elusive. In this work, we investigate the electronic and structural properties of CDW by first-principles calculations. We reveal an inverse Star of David deformation as the 2 x 2 x 2 CDW ground state of the kagome lattice. The kagome lattice shows softening breathing-phonon modes, indicating the structural instability. However, electrons play an essential role in the CDW transition via Fermi surface nesting and van Hove singularity. The inverse Star of David structure agrees with recent experiments by scanning tunneling microscopy (STM). The CDW phase inherits the nontrivial $\mathbb{Z}$ 2 -type topological band structure. Further, we find that the electron-phonon coupling is too weak to account for the superconductivity T c in all three materials. It implies the existence of unconventional pairing of these kagome metals. Our results provide essential knowledge toward understanding the superconductivity and topology in kagome metals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗

Electrochemistry of Thin Films with In Situ/Operando Grazing Incidence X-Ray Scattering: Bypassing Electrolyte Scattering for High Fidelity Time Resolved Studies

Electroactive polymer thin films undergo repeated reversible structural change during operation in electrochemical applications. While synchrotron X-ray scattering is powerful for the characterization of stand-alone and ex situ organic thin films, in situ/operando structural characterization has been underutilized-in large part due to complications arising from supporting electrolyte scattering. This has greatly hampered the development of application relevant structure property relationships. Therefore, a new methodology for in situ/operando X-ray characterization that separates the incident and scattered X-ray beam path from the electrolyte is developed. As a proof of concept, the operando structural characterization of weakly-scattering, organic mixed conducting thin films in an aqueous electrolyte environment is demonstrated, accessing previously unexplored changes in the $\pi-\pi$ peak and diffuse scatter, while capturing the solvent swollen thin film structure which is inaccessible in previous ex situ studies. These in situ/operando measurements improve the sensitivity to structural changes, capturing minute changes not possible ex situ, and have multimodal potential such as combined Raman measurements that also serve to validate the true in situ/operando conditions of the cell. Finally, new directions enabled by this in situ/operando cell design are examined and state of the art measurements are compared.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cracking the code of multi-layer films to promote circularity in single-use plastic packaging

Multi-layer film packaging (MLF) revolutionized food preservation by combining diverse material layers to optimize barrier properties, mechanical strength, and shelf-life. These materials are essential for transporting perishables across various climates and allow for access to fresh goods in “food deserts”, but they pose significant recycling challenges due to their structural complexity. This perspective examines key structure-property relationships governing barrier performance and highlights innovations in material design. We explore how machine learning can predict performance metrics and propose recyclable alternatives, integrating data-driven approaches with material science insights. By challenging the status quo of MLF design, we advocate for circularity in food packaging, inspiring innovation at the intersection of sustainability, material science, and artificial intelligence.

36 MATERIALS SCIENCE↗

A generalized wind turbine cross section as a reduced-order model to gain insights in blade aeroelastic challenges

In this work, we present an approach to study the aeroelastic stability of a wind turbine by focusing on the dynamics of a blade cross section. We present a methodology to obtain a reduced-order model of the blade dynamics in the form of generalized cross-sectional quantities that approximates the aerodynamic and structural properties of the full blade. The motivation for the work is to gain a physical understanding of the influence of aerodynamic models such as dynamic wake and dynamic stall on the frequency and damping of the structure using a reduced-order model with low computational cost. The model may be coupled to two-dimensional computational fluid dynamics softwares or engineering unsteady airfoil aerodynamics models accounting for dynamic wake and dynamic stall. In the latter case, we can obtain monolithic state-space forms of the aeroelastic system of equations, which simplifies the determination of the modal parameters and therefore the study of stability. The work investigates wind turbines in operation or at standstill, where vortex-induced vibrations and stall-induced vibrations, respectively, might be an issue. The implementation is made available as part of the open-source Python package WELIB and as part of the open-source unsteady aerodynamic driver of OpenFAST.

17 WIND ENERGY↗

Optical high-order harmonic generation as a structural characterization tool

Structural characterization is essential to material engineering, but few tools can detect structural properties in the time domain. High harmonic generation (HHG) emerges as a new frontier that touches the heart of condensed-matter physics from the symmetry to quantum geometrical nature of electrons, but its capability in structural characterization has not been materialized. Here, we establish a crucial connection between the symmetry of a material and the helicity of light. We employ monolayer MoS 2 as an example. In this work, we show that a linearly polarized laser pulse used in experiments is not ideal for structural characterization because it only generates in-plane anisotropy. It is the circularly polarized laser field that is capable of producing four distinctive HHG signals from the four phases of MoS 2 . This finally links the laser helicity to the crystal structure. The results are generic and are not affected by the Berry curvature, the interband or intraband contribution. Our study unleashes the power of HHG as a structural characterization tool for technologically important materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Engineering a Cu‐Pd Paddle‐Wheel Metal–Organic Framework for Selective CO 2 Electroreduction

Optimizing the binding energy between the intermediate and the active site is a key factor for tuning catalytic product selectivity and activity in the electrochemical carbon dioxide reduction reaction. Copper active sites are known to reduce CO 2 to hydrocarbons and oxygenates, but suffer from poor product selectivity due to the moderate binding energies of several of the reaction intermediates. Here, we report an ion exchange strategy to construct Cu−Pd paddle wheel dimers within Cu-based metal–organic frameworks (MOFs), [Cu 3-x Pd x (BTC) 2 ] (BTC=benzentricarboxylate), without altering the overall MOF structural properties. Compared to the pristine Cu MOF ([Cu 3 (BTC) 2 ], HKUST-1), the Cu−Pd MOF shifts CO 2 electroreduction products from diverse chemical species to selective CO generation. In situ X-ray absorption fine structure analysis of the catalyst oxidation state and local geometry, combined with theoretical calculations, reveal that the incorporation of Pd within the Cu−Pd paddle wheel node structure of the MOF promotes adsorption of the key intermediate COOH* at the Cu site. This permits CO-selective catalytic mechanisms and thus advances our understanding of the interplay between structure and activity toward electrochemical CO 2 reduction using molecular catalysts.

CO2 electroreduction reaction↗

Electronic and Spintronic Open-Shell Macromolecules, Quo Vadis ?

Open-shell macromolecules (i.e., polymers containing radical sites either along their backbones or at the pendant sites of repeat units) have attracted significant attention owing to their intriguing chemical and physical (e.g., redox, optoelectronic, and magnetic) properties, and they have been proposed and/or implemented in a wide range of potential applications (e.g., energy storage devices, electronic systems, and spintronic modules). These successes span multiple disciplines that range from advanced macromolecular chemistry through nanoscale structural characterization and on to next-generation solid-state physics and the associated devices. In turn, this has allowed different scientific communities to expand the palette of radical-containing polymers relatively quickly. However, critical gaps remain on many fronts, especially regarding the elucidation of key structure–property–function relationships that govern the underlying electrochemical, optoelectronic, and spin phenomena in these materials systems. Here, we highlight vital developments in the history of open-shell macromolecules to explain the current state of the art in the field. Moreover, we provide a critical review of the successes and bring forward open opportunities that, if solved, could propel this class of materials in a meaningful manner. Finally, we provide an outlook to address where it seems most likely that open-shell macromolecules will go in the coming years. Furthermore, our considered view is that the future of radical-containing polymers is extremely bright and the addition of talented researchers with diverse skills to the field will allow these materials and their end-use devices to have a positive impact on the global science and technology enterprise in a relatively rapid manner.

36 MATERIALS SCIENCE↗

Phonon mixing in the charge density wave state of ScV6Sn6

Abstract Kagomé metals are widely recognized, versatile platforms for exploring topological properties, unconventional electronic correlations, magnetic frustration, and superconductivity. In the R V 6 Sn 6 family of materials ( R = Sc, Y, Lu), ScV 6 Sn 6 hosts an unusual charge density wave ground state as well as structural similarities with the A V 3 Sb 5 system ( A = K, Cs, Rb). In this work, we combine Raman scattering spectroscopy with first-principles lattice dynamics calculations to reveal phonon mixing processes in the charge density wave state of ScV 6 Sn 6 . In the low temperature phase, we find at least four new peaks in the vicinity of the V-containing totally symmetric mode near 240 cm −1 suggesting that the density wave acts to mix modes of P 6/ m m m and $$R\bar{3}m$$ R 3 ¯ m symmetry - a result that we quantify by projecting phonons of the high symmetry state onto those of the lower symmetry structure. We also test the stability of the short-range ordered density wave state under compression and propose that both physical and chemical pressure quench the effect. We discuss these findings in terms of symmetry and the structure-property trends that can be unraveled in this system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Better understanding and prediction of antiviral peptides through primary and secondary structure feature importance

The emergence of viral epidemics throughout the world is of concern due to the scarcity of available effective antiviral therapeutics. The discovery of new antiviral therapies is imperative to address this challenge, and antiviral peptides (AVPs) represent a valuable resource for the development of novel therapies to combat viral infection. We present a new machine learning model to distinguish AVPs from non-AVPs using the most informative features derived from the physicochemical and structural properties of their amino acid sequences. To focus on those features that are most likely to contribute to antiviral performance, we filter potential features based on their importance for classification. These feature selection analyses suggest that secondary structure is the most important peptide sequence feature for predicting AVPs. Our Feature-Informed Reduced Machine Learning for Antiviral Peptide Prediction (FIRM-AVP) approach achieves a higher accuracy than either the model with all features or current state-of-the-art single classifiers. Understanding the features that are associated with AVP activity is a core need to identify and design new AVPs in novel systems. The FIRM-AVP code and standalone software package are available at https://github.com/pmartR/FIRM-AVP with an accompanying web application at https://msc-viz.emsl.pnnl.gov/AVPR.

59 BASIC BIOLOGICAL SCIENCES↗

The First Neptunium Dioxide Neutron Diffraction Experiment at HFIR

Here we present the first neutron diffraction experiment of a 50 mg sample of neptunium(IV) dioxide (NpO 2 ) powder at the High Flux Isotope Reactor (HFIR) using the wide-angle neutron diffractometer (WAND 2 ) HB-2C. We also provide a brief literature survey to pinpoint gaps in the crystal, electronic, and magnetic structure of NpO 2 to determine the optimum experiment to be pursued in the next HFIR user proposal cycle. Characterizing actinide materials with neutron diffraction, inelastic scattering, neutron imaging, polarized neutron studies, and small-angle neutron scattering techniques will increase our understanding of 5f electron behavior and elucidate atomic and magnetic structural properties. This strategy will help fill gaps in the literature and provide theoretical physicists with the data needed to build physical and chemical models to guide and validate computational methods. These methods may be used for predicting structural and chemical features of actinide-based materials. This proof-of-principle effort begins to uncover how to advance actinide science and technology at Oak Ridge National Laboratory (ORNL) using neutron capabilities. This effort has already sparked collaborative discussions between researchers outside the Radioisotope Science and Technology Division, including theoretical physicists from the Nuclear Nonproliferation Division and beamline scientists in the Neutron Scattering Division. We intend to continue pursuing neutron experiments and develop a scientific strategy focused on studying transuranium elements (e.g., Np, Pu, Am, and Cm) using the advanced neutron capabilities at ORNL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Prediction of Research/Motor Octane Number and Octane Sensitivity Using Artificial Neural Networks

Octane sensitivity (OS), dfined as the research octane number (RON) minus the motor octane number (MON) of a given fuel, has gained interest among researchers due to its apparent ffect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially with respect to advanced compression ignition engines. RON/MON must be experimentally tested to determine OS; however, the experimental methods utilized require a substantial amount of time, a significant monetary investment, and specialized equipment. To this end, predictive computational models trained with existing experimental data and molecular properties would allow for the preemptive screening of compounds prior to performing these experiments. The present work proposes two methods for predicting the OS of a given compound: using artficial neural networks (ANNs) trained with quantitative structure-property relationship (QSPR) descriptors to predict RON and MON individually to compute OS from RON/MON predictions (derived octane sensitivity, dOS), and using an ANN trained with QSPR descriptors to directly predict OS. ANNs trained to predict RON and MON achieved test set root-mean-square errors (RMSEs) of 10.499 and 7.551 respectively. dOS calculations were found to have a test set RMSE of 6.432 while predicting OS directly resulted in a test set RMSE of 7.019, showing it is more bene cial to obtain OS from RON/MON predictions than predicting it directly. Furthermore, relationships between individual QSPR descriptors and RON/MON/OS are discussed, highlighting correlations between specfic molecular features and these properties.

09 BIOMASS FUELS↗

Nonexcitonic mechanism for electronic and structural phase transitions in Ta 2 ⁢Ni⁢(Se,S) 5

Here, we present a first-principles study based on density functional theory (DFT) on the electronic and structural properties of Ta 2 NiSe 5 , a layered transition metal chalcogenide that has been considered as a possible candidate for an excitonic insulator. Our systematic DFT results however provide a nonexcitonic mechanism for the experimentally observed electronic and structural phase transitions in Ta 2 NiSe 5 , in particular explaining why sulfur substitution of selenium reduces the distortion angle in the low-temperature phase and potassium dosing closes the gap in the electronic structure. Moreover, the calculations show that these two effects couple to each other. Further, our first-principles calculations predict several changes in both the crystal structure and electronic structure under the effects of uniform charge dosing and uniaxial strain, which could be tested experimentally.

Tang, Weichen [University of California, Berkeley,↗

ORNL_AISD_DL-HLgap

This dataset provides supplementary molecular dataset of Deep Learning Workflow for the Inverse Design of Molecules with Specific Optoelectronic Properties. The dataset comprises three main directories such as GDB-9_dataset, Low_HL_Gap_dataset, and High_HL_Gap_dataset which individually has csv files, smiles_txt files, pdb files and xyz files containing information of molecular structures, properties and coordinates generated from deep learning workflow using generative model, surrogate model and DFTB calculation results. GDB-9_dataset contains the molecular data extracted from the original GDB-9 dataset with additional data of DFTB HL gap, surrogate HL gap and molecular property analysis. (the number of atoms, aromaticity and double bond equivalent) Low_HL_Gap_dataset and High_HL_Gap_dataset contains series of dataset for different generations with further split to train and test dataset that were obtained from the iterative workflow described in the manuscript. Additional directory Chemiscope_visualization in Low_HL_Gap_dataset directory contains compressed json files to visualize molecules using chemiscope.org page or application to help readers examine generated molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhanced Light Outcoupling from OLEDs Fabricated on Novel Low-Cost Patterned Plastic Substrates of Varying Periodicity

OLEDs continue to make strides in display applications, but their commercial utilization in solid-state lighting (SSL) is lagging. An ongoing challenge, in particular for manufacturing, is the need for enhanced efficiency and hence the necessity to increase in an inexpensive approach the extraction of the light generated inside the OLED into the forward (viewing) hemisphere. In conventional OLEDs fabricated on a transparent flat anode coated on glass, the external quantum efficiency (EQE) is only ~20%. About 50% of the light is lost to internal waveguiding in the high refractive index (RI) organic + ITO anode layers and to surface plasmon polaritons (SPPs) at the organic/metal cathode interface. Another ~30% of the light is externally waveguided in the substrate to its edges. While extraction of the externally waveguided light is commonly addressed by adding a microlens array (MLA) or a scattering layer at the substrate’s air-side, light outcoupling increases by only ~1.6-1.7x (vs up to 2.5x in improving from ~20% to ~50%). The use of a hemispherical lens or an index matching fluid (IMF) at the substrate/photodetector (PD) interface increases the outcoupling by at least 2x; these approaches however, are not viable industrially, and even a MLA is sometimes undesirable due to its non-planar, scattering structure. In multi-stack tandem OLEDs, where the metal cathode is far from the emitting zone(s), the impact of photons loss to SPPs decreases. Our project addressed the ~50% loss to the internally waveguided light and SPPs. We evaluated OLEDs fabricated on patterned or planarized plastic substrates manufactured in a cost-effective approach compatible with a roll-to-roll (R2R) process. The OLEDs were either (i) patterned to various degrees depending on the pitch a and height or depth h of the pattern features or (ii) planar, with a pattern buried under a flat high RI planarization layer. We demonstrated that the outcoupling from green patterned OLEDs reaches ~50% by mitigating plasmon–related loss and internal waveguiding, even without the addition of a MLA, a hemispherical lens, or IMF. Simulations conducted in parallel with the experimental effort demonstrated how diffraction by conformally corrugated OLEDs increases the outcoupling to >60%. Structures with varying pitch values were also simulated indicating that combining domains of varying pitch could increase outcoupling to 55-60%. Experimentally, we additionally assessed the role a and h in determining not only the OLED efficiencies, but also their structural properties, i.e., the uniformity and conformality throughout the OLED stack. As planar OLEDs are preferred over corrugated devices, we studied different patterns in plastic substrates that were planarized by a high RI formulation. Planar green OLEDs on such structures showed enhanced efficiencies with EQEs larger than 60% with the addition of an IMF (to extract the substrate mode) at the substrate/Si PD interface. White OLEDs showed EQEs of 45.5%. Plastic substrates are currently less attractive than glass substrates due to drawbacks such as permeability to water vapor and oxygen, and in some cases thermal instability. Plastic substrates however, are flexible and easy to handle unlike thin flexible glass, and once transparent thin barrier films are available, they will become more attractive; they are already of interest in medical applications. Importantly, as it is easy to generate various patterns in different plastic materials, they provide excellent means for assessing and optimizing enhancing extracting structures. Such structures can also be transferred to glass substrates with some process modifications. The technical effectiveness and economic feasibility of the project lie in the patterning of the extracting plastic substrates in an approach that is scalable to R2R manufacturing. R2R processes are of drastically lower-cost than batch or single-unit fabrication. The patterned plastic can be a part of an integrated substrate either plastic or glass, which includes also a MLA or a planar layer with embedded scattering particles, as well as a conductive metal mesh/electrode design. SSL is environmentally-friendly and as OLED SSL becomes more efficient it will reduce electricity consumption, and hence lighting cost, as well as produce less expensive attractive lighting fixtures. Our university-industry collaboration is hence of major benefit to the public as it demonstrates the feasibility of manufacturing optimized extracting substrates for highly efficient OLEDs for SSL in a future R2R process, which would drastically reduce the manufacturing cost and increase production in the USA. Moreover, newly developed methods by our team allow low-cost roll manufactured substrates to be transferred to flexible or rigid glass substrates, which solves the plastic substrate barrier issues, and when combined with device encapsulation will increase the OLEDs’ environmental stability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Pyrochlore-type lanthanide titanates and zirconates: Synthesis, structural peculiarities, and properties

This contribution provides a thorough examination of the structural characteristics of pyrochlore-type lanthanide titanates and zirconates Ln2Ti2O7 and Ln2Zr2O7, across various length scales. This paper also examines their processing, interesting physical properties (electrical, magnetic, and thermal characteristics), and responses to high pressure and ion irradiation. Brief sections on the elemental oxides' crystal chemistry, pertinent phase diagrams, and energetics of defect formation are also provided. Pyrochlore-type Ln2Ti2O7 and Ln2Zr2O7 stand out as truly multifunctional materials. Moreover, they have emerged as fascinating materials due to magnetic geometrical frustration, arising from the ordering of magnetic Ln3+ and non-magnetic Ti4+ (or Zr4+) cations into separate, interpenetrating lattices of corner-sharing tetrahedra. This results in a diverse array of exotic magnetic ground states, such as spin-ice (e.g., Dy2Ti2O7 or Ho2Ti2O7) or quantum spin ice (e.g., Tb2Ti2O7), observed at both low and room temperatures. They also exhibit varied electrical and electrochemical characteristics. Some members such as Gd2Zr2O7, function as fast ion conductors with a conductivity (σ) of ≈10−2 S·cm−1 at 800 °C and activation energy (Ea) ranging from 0.85 to 1.52 eV, depending on the degree of structural disorder. Others, such as Gd2TiMoO7, are mixed ionic-electronic conductors with σ ≈ 25 S·cm−1 at 1000 °C, making them promising candidate materials for applications in energy conversion and storage devices and oxygen separation membranes. Their exceptionally low thermal conductivity (e.g., κ ∼ 1.1–1.7 W·m−1·K−1 between 700 and 1200 °C for Ln2Zr2O7), close to the glass-like lower limit of highly disordered solids, positions them as valuable materials for thermal barrier coatings. They can also effectively accommodate actinides (e.g., Pu, Np, Cm, Am) in solid solutions and sustain prolonged exposure to radiation due to alpha-decay events, while preserving the integrity of the periodic atomic structure. Proposed as major components in actinide-bearing ceramics, they contribute to the long-term immobilization and disposal of long-lived waste radionuclides from nuclear programs. Some of these properties are displayed simultaneously, opening avenues for new applications. Despite the wealth of data available in the literature, this review highlights the need for a better understanding of order/disorder processes in pyrochlore-type materials and the influence of the structural length scale on their physical and chemical properties. Recent experimental evidence has revealed that pyrochlore short-range structure is far more complex than originally thought. Moreover, pyrochlore local structure is now believed to include short-range, lower symmetry, ordered domains, such as the orthorhombic weberite-type of structure. Notably, short- and long-range structures appear decoupled across different length scales and temperature regimes, and these differences persist even in well-ordered samples. We believe that the pyrochlore structure offers a unique opportunity for examining the interplay between chemical composition, defect chemistry, and properties. In Memoriam: Rodney C. Ewing, Fondly Remembered.

Physics↗

Skeletal tissue regulation by catalase overexpression in mitochondria

Accumulation of oxidative damage from excess reactive oxygen species (ROS) may contribute to skeletal aging and mediate adverse responses to physiological challenges. Wild-type (WT) mice and transgenic mice (male, 16 wk of age) with human catalase targeted to the mitochondria (mCAT) were analyzed for skeletal responses to the remodeling stimuli of combined hind-limb unloading and exposure to ionizing radiation ( 137 Cs, 2 Gy). Treatment for 2 wk caused lipid peroxidation in the bones WT but not mCAT mice, showing that transgene expression mitigated oxidative stress. Ex vivo osteoblast colony growth rate was 95% greater in mCAT than WT mice and correlated with catalase activity levels ( P < 0.005, r = 0.67), although terminal osteoblast and osteoclast differentiation were unaffected. mCAT mice had lower cancellous bone volume and cortical size than WT mice. Ambulatory control mCAT animals also displayed reduced cancellous and cortical structural properties compared with control WT mice. In mCAT but not WT mice, treatment caused an unexpectedly rapid radial expansion (+8% cortical area, +22% moment of inertia), reminiscent of compensatory bone growth during advancing age. In contrast, treatment caused similar structural deficits in cancellous tissue of mCAT and WT mice. In sum, mitochondrial ROS signaling via H 2 O 2 was important for the acquisition of adult bone structure and catalase overexpression failed to protect cancellous tissue from treatment. In contrast, catabolic stimuli caused radial expansion in mCAT not WT mice, suggesting that mitochondrial ROS in skeletal cells act to suppress tissue turnover in response to remodeling challenges.

Cell Biology↗

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

3D printing↗