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At least 37 records · Page 2

Reconfigurable unitary transformations of optical beam arrays

Spatial transformations of light are ubiquitous in optics, with examples ranging from simple imaging with a lens to quantum and classical information processing in waveguide meshes. Multi-plane light converter (MPLC) systems have emerged as a platform that promises completely general spatial transformations, i.e., a universal unitary. However, until now, MPLC systems have demonstrated transformations that are far from general, e.g., converting from a Gaussian to Laguerre-Gauss mode. Here, we demonstrate the promise of an MLPC, the ability to impose an arbitrary unitary transformation that can be reconfigured dynamically. Specifically, we consider transformations on superpositions of parallel free-space beams arranged in an array, which is a common information encoding in photonics. We experimentally test the full gamut of unitary transformations for a system of two parallel beams and make a map of their fidelity. We obtain an average transformation fidelity of 0.85 ± 0.03. This high-fidelity suggests that MPLCs are a useful tool for implementing the unitary transformations that comprise quantum and classical information processing.

47 OTHER INSTRUMENTATION

Experimental determination of critical resolved shear stress for strain-induced phase transformation

The current investigation reports the first attempt to measure the critical resolved shear stress to initiates strain-induced phase transformation in a three-dimensional polycrystalline aggregate using high-energy diffraction microscopy (HEDM). In situ tensile testing was performed on a Fe38.5Mn20Co20Cr15Si5Cu1.5 metastable alloy exhibiting transformation-induced plasticity (TRIP). Grains with a higher propensity for strain-induced phase transformation were tracked using HEDM. A sharp drop in grain specific stress, coinciding with the appearance of a new ε-hcp grain oriented relative to the parent γ-fcc phase, was taken as evidence of grain-specific stress required to trigger phase transformation. The highest resolved shear stress on the potential transformation systems was identified as the critical resolved shear stress (CRSS) for strain-induced phase transformation. For the studied metastable alloy, CRSS for transformation was determined to be 86±3 MPa which was very close to theoretical CRSS value determined using Schmid factor (89±12 MPa) compared to the value determined using Taylor factor (62±7 MPa).

Jain, Roopam

Multiplexing and Demultiplexing Signals for Radiography Application Using the Discrete Fourier Transform

Our goal is to develop an X-ray phase-contrast imaging system that can provide excellent soft tissue contrast of phase, attenuation, and small-angle scatter. We propose to replace the common system of G0, G1, and G2 gradings with a biprism array to replace the G1 grading and introduce a novel X-ray tube designed to replace the motion of the phase stepping grading G2. The proposed X-ray tube uses temporal multiplexing to provide simultaneous virtual “electronic phase stepping.” In this work the discrete Fourier transform is used to separate from the composite measurement individual X-ray phase contrast measurements sampled at different frequencies. The method performs a discrete Fourier transform of a composite refence sequence to obtain using the frequency amplitudes calibration factors needed to extract the X-ray phase contrast measurement amplitudes from the composite image. The composite reference sequence is the sum of the individual sequences, at different frequencies, with amplitudes of one. The method takes the discrete Fourier transform of this composite reference sequence; whereby, the amplitude of each frequency component is compared with the total sum of its stand-alone sequence amplitude. A calibration factor is determined so that the amplitude of this composite reference frequency times the calibration factor must equal the total sum of the sequence amplitude—the zero-frequency amplitude of the discrete Fourier transform of its stand-alone sequence. To demultiplex the composite measured signal these calibration factors are multiplied by the amplitudes of the frequency components of the discrete Fourier transform of the composite X-phase-contrast measurement to obtain the amplitude of each frequency encoded measurement. Using these calibration factors, we demonstrate with the discrete Fourier transform in Mathematica the extraction of individual images from a composite image that one would expect obtaining from our proposed new X-ray phase contrast imaging system. We then demonstrate as an example how using images from X-ray phase contrast data one can calculate phase, attenuation and the dark field images using grading phase step data supplied to use from Microworks, GmbH in Karlsruhe, Germany.

42 ENGINEERING

Nanocrystal Geometry Governs Phase Transformation Pathways in Palladium Hydride

Pathways and structural dynamics of phase transformations impact performance of materials in energy and information storage technologies. Palladium hydride (PdH x ) nanocrystals are an ideal model system for studying solute-induced phase transformations, where elastic energy from lattice mismatch between α-PdH x and β-PdH x phases is often considered a key to determining the transformation pathways. α/β-PdH x interfacial elastic energy is affected by the confined geometry of a nanocrystal. However, how nanocrystal geometry influences phase transformation pathways is largely unknown. Using in situ liquid phase transmission electron microscopy, we directly visualize hydrogenation in Pd nanocrystals with two geometries, a nanocube and a hexagonal nanoplate. Both follow similar sequences of an initially curved nucleus, interface flattening, and reverse-stage nucleation; however, their evolving α/β-PdH x interfaces exhibit geometry-dependent crystallographic alignments. In nanocubes, {100}-aligned configurations conform to static elastic energy ordering, representing a pathway that maintains a local mechanical equilibrium, whereas nanoplates display both {110}- and {211}-aligned interfaces. Theoretical simulations show that geometry determines the accessibility of alternative phase transformation pathways as the system is driven far from equilibrium during hydrogenation. In conclusion, these findings identify geometry as a fundamental parameter for directing phase transformation pathways, offering design principles for accessing atypical configurations and improving properties of intercalation-based devices.

Lee, Daewon [Lawrence Berkeley National Laboratory

Mechanism of the wurtzite to rocksalt phase transformation in cadmium sulfide single crystals shock compressed along the 𝑐-axis to elastic impact stresses of ∼ 5 GPa

Cadmium sulfide (CdS), which exhibits a wurzite (WZ) to rocksalt (RS) phase transformation at elevated stresses, is an ideal system to address the role of deformation on phase transformation mechanisms and kinetics. CdS has been shown to have very different elastic-inelastic behavior for shock propagation along the WZ 𝑐- and 𝑎-axes, and also exhibits significant differences in the time scale for the phase transformation when shocked along these different axes. As an important first step in examining the role of deformation in shock-induced phase transformations, here we present in situ, time-resolved x-ray diffraction (XRD) measurements in single-event, shock wave experiments on CdS single crystals shocked along the WZ 𝑐-axis to elastic impact stresses near or above ∼ 5 GPa, where a marked increase in the kinetics of this transformation has been reported. The XRD measurements are compared with forward diffraction simulations to evaluate different proposed phase transformation mechanisms and are shown to be consistent with a shearing mechanism that results in the RS [001] direction being aligned with the original WZ 𝑐-axis and the RS [110] direction being aligned with the original WZ 𝑎-axis. In order to reproduce all observed RS diffraction spots the forward diffraction simulations required three different RS crystalline domains, each with a [110] direction aligned with one of the three original WZ 𝑎-axes, and a significant mosaicity, particularly about the RS [001] direction (the direction of shock propagation). In conclusion, this large mosaicity is likely due to variations in the possible shearing mechanisms that connect the WZ and RS structures, which can create crystallites with up to ∼ ±10° of relative rotations about the RS [001] direction, as well as further rotation of these crystallites as they grow, merge, and coalesce.

Crystal structure

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab

Solid State Transformer Architecture and Control Compensation for Common Mode Currents

A high-altitude electromagnetic pulse (HEMP) or similar geomagnetic disturbance (GMD) has the potential to impact the operation of large-scale electric power grids. By introducing low-frequency common-mode (CM) currents, these events can degrade the performance of critical system components, such as large power transformers by introducing CM currents which can lead to magnetic saturation of the transformer core. In this work, a solid-state transformer (SST) is developed to replace susceptible equipment and improve grid resiliency by safely absorbing these CM disturbances. This device will be referred to as a common-mode solid-state transformer (CM-SST). An SST architecture based on a four-legged AC/DC converter is developed. This architecture enables active control of CM signals without disturbing the AC voltages or the real and reactive power delivery capabilities. A system-level model of this architecture is created, and time-domain simulations are performed to evaluate the SST’s performance in response to simulated CM disturbances. A control strategy for mitigating CM current is also investigated. Hamiltonian surface shaping and power flow control (HSSPFC) is used to design a nonlinear controller for the SST’s output inverter. The objectives of the controller are to suppress CM-induced AC current offsets and regulate AC currents to desired setpoints. Nonlinear system analysis is applied to design and validate the controller. Two cases are tested: (a) the proposed four-leg inverter and (b) a standard three-leg inverter. The results show that the proposed controller rapidly mitigates CM disturbances while maintaining high-quality AC current waveforms in the four-leg configuration. Finally, the hardware performance of an SST prototype is evaluated. In particular, the ability of the SST to safely redirect and absorb CM currents is demonstrated, showing how it can protect neighboring conventional transformers in the system. The study confirms that appropriate control laws allow the SST to protect both itself and adjacent transformers during a HEMP or GMD event.

24 POWER TRANSMISSION AND DISTRIBUTION

Understanding the deformation behavior of the γ rich transformative Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy using in situ synchrotron diffraction

In situ tensile testing coupled with synchrotron x-ray diffraction was used to study the deformation behavior of metastability-engineered Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy. Monitoring the evolution of phase fraction and strain hardening response allowed the determination of true critical stress for the onset of the transformation-induced plasticity (TRIP) to be ∼375 MPa, preceded by slip starting at ∼255 MPa. In situ EBSD was used to validate the critical stress for transformation at the microstructure level and observe slip traces to confirm prior slip activity before the transformation. Further, a modeling framework based on stacking fault energy (SFE) was developed to predict the critical stress for transformation. Modeling suggested the SFE of the alloy to fall nearly 15 mJ/m 2 , which agrees well with SFE values calculated using synchrotron peak shifting (12 mJ/m 2 ) and thermodynamic calculation (11 mJ/m 2 ). As a result of γ-fcc to ε-hcp phase transformation, new {0002} ε planes emerged parallel to unaligned {111} γ planes with the tensile loading following S-N orientation relationship. Such selective emergence of new diffraction rings corresponding to ε phase is understood based on the reorientation of γ crystals with reference to tensile axis. In conclusion, this approach can be extended to effectively design alloys based on critical stress required for activating different deformation mechanisms to further push the limits of the strength-ductility envelope.

Complex concentrated alloy

Computational simulation of asymmetric phase transformation in cracked Li₇La₃Zr₂O₁₂: Variant selection and chemo-mechanical implications

Coupling between microcracks and phase transformation in ion-conducting ceramics can jointly affect mechanical responses and ion transport. In this work we investigate the cubic-to-tetragonal phase transformation in Li₇La₃Zr₂O₁₂ in the presence of a microcrack under hydrostatic loading and quantify its implications for crack-tip stress concentration and Li-ion transport using phase-field and molecular dynamics simulations. The phase transformation exhibits a strong asymmetry between hydrostatic tension and compression. Under tension, the crack edge nucleates one tetragonal variant that amplifies the crack-tip stress intensity and promotes crack opening. Under compression, the crack tip nucleates a different tetragonal variant that enhances the stress-induced crack-closure tendency. Effective Li diffusivity analysis shows faster transport degradation under compression due to accelerated transformation kinetics, exposing a trade-off between mechanical stability and ionic conductivity. These results highlight the intertwined nature of cracking, phase transformation, and ionic transport in ion-conducting oxides and provide mechanistic insights into chemo-mechanical degradation of solid electrolytes.

36 MATERIALS SCIENCE

A Discrete Hankel Transform Approach to Nuclear Data Processing for Fusion Applications

This study introduces advancements to the numerical solutions employed in the processing of nuclear data for fusion applications. It leverages the convolution theorem and Fourier transform techniques to enhance computational efficiency and broaden applicability. Building upon a previously reported discrete Hankel transform approach for Doppler broadening, this work refines the solution of convolution integrals central to these applications. The methodology provides a general and unified framework for evaluating any convolution operation, regardless of whether the underlying problem involves temperature effects in nuclear reactions. The applicability to the nuclear data processing for fusion is demonstrated by deriving the convolution integrals for some of the fusion-related quantities. As before, the convolution operation utilizes a Gaussian-based kernel; however, the discrete Hankel transform of order $𝛼$ = $\frac{1}{2}$ is now applied to the forward Fourier transform of the nonkernel argument, rather than the inverse Fourier transform. This modification eliminates the need for the integration of the nonkernel, cross section–based function, which is a step that posed challenges for certain pointwise cross-section representations. It also removes the requirement for cross-section linearization. Optimized for graphics processing unit architectures, the approach significantly improves computational performance. These advancements are currently under evaluation as the foundation for the next-generation thermonuclear data file processing codes being developed at Lawrence Livermore National Laboratory.

Nuclear science and engineering

Viral‐mediated delivery of morphogenic regulators enables leaf transformation in Sorghum bicolor (L.)

Recent advancements in monocot transformation, using leaf tissue as explant material, have expanded the number of grass species capable of transgenesis. However, the complexity of vectors and reliance on inducible excision of essential morphogenic regulators have so far limited widespread application. Plant RNA viruses, such as Foxtail Mosaic Virus (FoMV), present a unique opportunity to express morphogenic regulator genes, such as Babyboom (Bbm), Wuschel2 (Wus2), Wuschel-like homeobox protein 2a (Wox2a) and the GROWTH-REGULATING FACTOR 4 (GRF4) GRF-INTERACTING FACTOR 1 (GIF1) fusion protein transiently in leaf explant tissues. Furthermore, altruistic delivery of conventional and viral vectors could provide opportunities to simplify vectors used for leaf transformation—facilitating vector optimization and reducing reliance on morphogenic regulator gene integration. In this study, both viral and conventional T-DNA vectors were tested for their ability to promote the formation of embryonic calli, a critical step in leaf transformation protocols, using Sorghum bicolor leaf explants. Although conventional leaf transformation vectors yielded viable embryonic calli (43.2 ± 2.9%: GRF4-GIF1, 50.2 ± 3%: Bbm/Wus2), altruistic conventional vectors employing the GRF4-GIF1 morphogenic regulator resulted in improved efficiencies (61.3 ± 4.7%). Altruistic delivery was further enhanced with the use of viral vectors employing both GRF4-GIF1 and Bbm/Wus2 regulators, resulting in 75.1 ± 2.3% and 79.2 ± 2.5% embryonic calli formation, respectively. Embryonic calli generated from both conventional and viral vectors produced shoots expressing fluorescent reporters, which were confirmed using molecular analysis. This work provides an important proof-of-concept for the use of both altruistic vectors and viral-expressed morphogenic regulators for improving plant transformation.

59 BASIC BIOLOGICAL SCIENCES

Data for "Viral-mediated Delivery of Morphogenic Regulators Enables Leaf Transformation in Sorghum bicolor (L.)"

Recent advancements in monocot transformation, using leaf tissue as explant material, have expanded the number of grass species capable of transgenesis. However, the complexity of vectors and reliance on inducible excision of essential morphogenic regulators have so far limited widespread application. Plant RNA viruses, such as Foxtail Mosaic Virus (FoMV), present a unique opportunity to express morphogenic regulator genes, such as Babyboom ( Bbm ), Wuschel2 ( Wus2 ), Wuschel-like homeobox protein 2a ( Wox2a ) and the GROWTH-REGULATING FACTOR 4 (GRF4) GRF-INTERACTING FACTOR 1 (GIF1) fusion protein transiently in leaf explant tissues. Furthermore, altruistic delivery of conventional and viral vectors could provide opportunities to simplify vectors used for leaf transformation—facilitating vector optimization and reducing reliance on morphogenic regulator gene integration. In this study, both viral and conventional T-DNA vectors were tested for their ability to promote the formation of embryonic calli, a critical step in leaf transformation protocols, using Sorghum bicolor leaf explants. Although conventional leaf transformation vectors yielded viable embryonic calli (43.2 ± 2.9%: GRF4-GIF1, 50.2 ± 3%: Bbm/Wus2), altruistic conventional vectors employing the GRF4-GIF1 morphogenic regulator resulted in improved efficiencies (61.3 ± 4.7%). Altruistic delivery was further enhanced with the use of viral vectors employing both GRF4-GIF1 and Bbm/Wus2 regulators, resulting in 75.1 ± 2.3% and 79.2 ± 2.5% embryonic calli formation, respectively. Embryonic calli generated from both conventional and viral vectors produced shoots expressing fluorescent reporters, which were confirmed using molecular analysis. This work provides an important proof-of-concept for the use of both altruistic vectors and viral-expressed morphogenic regulators for improving plant transformation.

gene editing

Insulating Nanofluids and Solids to Upgrade our Large Aging Transformer Equipment (Advanced Research Projects Agency – Energy Research Final Report)

This project developed a highly promising, minimally invasive pathway for transformers with up to double the thermal life that is achieved today. Thermal life is important because it is occasionally necessary to overload transformers in service and this overload raises the internal temperature, accelerating aging2. A seminal initial finding in the research was that a likely achievable increase in the thermal conductivity of the transformer paper could double the thermal life. Oil-impregnated paper is used to wrap the electrical conductors in a transformer to provide a good balance of electrical insulation and thermal conductivity. The novel approach to increase the thermal conductivity was to add micrometer boron nitride particles to the paper during manufacturing. This is encouraging because it provides benefits with minimal impact on the manufacturing processes of the paper or of a transformer.

24 POWER TRANSMISSION AND DISTRIBUTION

Visualizing Crystallization Dynamics and Transformation Pathways of Disordered Rocksalt Oxides During Thermally Activated Sol–Gel Synthesis

Sol–gel synthesis is a wet-chemical processing route for fabricating functional materials with control over composition and microstructure at relatively low temperatures compared to conventional solid-state synthesis. While sol–gel process initiates with intermixed molecular precursors, the early-stage nucleation pathways are insufficiently understood. Here, in this study, the chemical and structural transformation of ion disordered rocksalt (DRX) Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO), a promising cathode material for lithium batteries, is studied by multiscale characterizations. In situ heating transmission electron microscopy (TEM) using a liquid cell visualizes and identifies crystallization pathways at the nanoscale. While some regions follow a classical multi-step transition through thermodynamically stable intermediates, others exhibit a kinetic shortcut via a localized amorphous matrix to directly form the DRX structure. Macroscale Fourier transform infrared spectroscopy corroborates the findings and reveals that transition metal ions are more strongly incorporated into the acetate-coordinated network than lithium. Although in situ heating TEM captures diverse local transformation pathways, in situ synchrotron X-ray diffraction indicates that the macroscopic transformation proceeds predominantly through spinel LMTO and lithium titanates toward DRX-LMTO. The findings uncover the spatiotemporal chemical and structural transformations in sol–gel derived DRX-LMTO materials, and call for fine-tuning of such sol–gel chemistries to manipulate the crystallization pathways and achieve target material homogeneity more efficiently.

cathode material

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite

Direct observations of transient weakening during phase transformations in quartz and olivine

Phase transformations are widely invoked as a source of rheological weakening during subduction, continental collision, mantle convection and various other geodynamic phenomena. However, despite more than half a century of research, the likelihood and magnitude of such weakening in nature remain poorly constrained. Here we use experiments performed on a synchrotron beamline to reveal transient weakening of up to three orders of magnitude during the polymorphic quartz to coesite (SiO 2 ) and olivine to ringwoodite (Fe 2 SiO 4 ) phase transitions. Weakening becomes increasingly prominent as the transformation outpaces deformation. We suggest that this behaviour is broadly applicable among silicate minerals undergoing first-order phase transitions and examine the likelihood of weakening due to the olivine-spinel, (Mg,Fe) 2 SiO 4 , transformation during subduction. Modelling suggests that cold, wet slabs are most susceptible to transformational weakening, consistent with geophysical observations of slab stagnation in the mantle transition zone beneath the western Pacific. In conclusion, our study highlights the importance of incorporating transformational weakening into geodynamic simulations and provides a quantitative basis for doing so.

Cross, Andrew J. [Woods Hole Oceanographic Institu

Forecast of Wildfire Potential Across California USA Using a Transformer

Wildfires are a major issue facing the United States, a matter further exacerbated by an ever-changing climate. In California alone, wildfires are responsible for billions of dollars in damages and take lives each year. Accurately predicting fire danger conditions allows preparation awareness before wildfires start. Transformers are a class of deep learning models designed to identify patterns in sequential datasets. In recent years, transformers have gained popularity through their impressive performance in natural language processing and other applications of signal recognition. This analysis demonstrates the ability of a transformer with a residual connection to forecast fire danger potential over the state of California. Wildland fire potential index (WFPI) maps collected from the US Geological Survey database from January 1st 2020 to December 31st 2023 were used to tune, train and evaluate the transformer. Meteorological inputs (provided by Daymet daily weather and climatological summaries), the normalized difference vegetation index (NDVI) (calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS)), and outputs from the Scott and Burgman fire behavior fuel models (to characterize maps of fuel types), were used as inputs. Our results show that a transformer can effectively emulate the US Forest Service modeled WFPI maps of California USA for four week long forecasts over the month of July, 2023, with correlations ranging from 0.85 – 0.98.

Limber, Russell [ORNL]

Defining a Platform Approach and Market Participation: Data Driven Business Models for Solid State Transformer-Based Synthetic Inertia and Voltage Stability Controls (CRADA Final Report, Project 1, Mod 1)

The primary objective of this project is to determine the incremental value created with the medium voltage solid-state transformer (MV SST) technology to different stakeholders in view of the updated DER grid regulations. This includes studying the benefits of the MV SST technology in a range of use cases for EV and DER penetration including (1) “corridor charging” for EVs and (2) solar plus storage (FERC 2222). The potential customers of this technology include utilities for EV charging, DER installers who must meet utility interconnection requirements, balancing authorities, and DER aggregators. The traditional transformers on the grid could be a limiting factor for the EV-grid integration as the distribution transformers were not designed to handle the dynamic and fluctuating EV charging loads. Thus, the issues such as voltage fluctuations, increased losses and reduced efficiency [1] can negatively impact the grid operation. To address these challenges, transformers with flexibility and adaptability become imperative to meet the evolving energy demands. In this regard, the concept of Medium Voltage Solid-State Transformers.

14 SOLAR ENERGY