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At least 361 records · Page 20

Integration of Ag-CBRAM crossbars and Mott ReLU neurons for efficient implementation of deep neural networks in hardware

In-memory computing with emerging non-volatile memory devices (eNVMs) has shown promising results in accelerating matrix-vector multiplications. However, activation function calculations are still being implemented with general processors or large and complex neuron peripheral circuits. Here, we present the integration of Ag-based conductive bridge random access memory (Ag-CBRAM) crossbar arrays with Mott rectified linear unit (ReLU) activation neurons for scalable, energy and area-efficient hardware (HW) implementation of deep neural networks. We develop Ag-CBRAM devices that can achieve a high ON/OFF ratio and multi-level programmability. Compact and energy-efficient Mott ReLU neuron devices implementing ReLU activation function are directly connected to the columns of Ag-CBRAM crossbars to compute the output from the weighted sum current. We implement convolution filters and activations for VGG-16 using our integrated HW and demonstrate the successful generation of feature maps for CIFAR-10 images in HW. Our approach paves a new way toward building a highly compact and energy-efficient eNVMs-based in-memory computing system.

Mott insulators↗

Growth–defense trade‐offs and yield loss in plants with engineered cell walls

Summary As a major component of plant secondary cell walls, lignin provides structural integrity and rigidity, and contributes to primary defense by providing a physical barrier to pathogen ingress. Genetic modification of lignin biosynthesis has been adopted to reduce the recalcitrance of lignified cell walls to improve biofuel production, tree pulping properties and forage digestibility. However, lignin‐modification is often, but unpredictably, associated with dwarf phenotypes. Hypotheses suggested to explain this include: collapsed vessels leading to defects in water and solute transport; accumulation of molecule(s) that are inhibitory to plant growth or deficiency of metabolites that are critical for plant growth; activation of defense pathways linked to cell wall integrity sensing. However, there is still no commonly accepted underlying mechanism for the growth defects. Here, we discuss recent data on transcriptional reprogramming in plants with modified lignin content and their corresponding suppressor mutants, and evaluate growth‐defense trade‐offs as a factor underlying the growth phenotypes. New approaches will be necessary to estimate how gross changes in transcriptional reprogramming may quantitatively affect growth. Better understanding of the basis for yield drag following cell wall engineering is important for the biotechnological exploitation of plants as factories for fuels and chemicals.

Ha, Chan Man↗

DIAS: A Data-Informed Active Subspace Regularization Framework for Inverse Problems

This paper presents a regularization framework that aims to improve the fidelity of Tikhonov inverse solutions. At the heart of the framework is the data-informed regularization idea that only data-uninformed parameters need to be regularized, while the data-informed parameters, on which data and forward model are integrated, should remain untouched. We propose to employ the active subspace method to determine the data-informativeness of a parameter. The resulting framework is thus called a data-informed (DI) active subspace (DIAS) regularization. Four proposed DIAS variants are rigorously analyzed, shown to be robust with the regularization parameter and capable of avoiding polluting solution features informed by the data. They are thus well suited for problems with small or reasonably small noise corruptions in the data. Furthermore, the DIAS approaches can effectively reuse any Tikhonov regularization codes/libraries. Though they are readily applicable for nonlinear inverse problems, we focus on linear problems in this paper in order to gain insights into the framework. Various numerical results for linear inverse problems are presented to verify theoretical findings and to demonstrate advantages of the DIAS framework over the Tikhonov, truncated SVD, and the TSVD-based DI approaches.

Nguyen, Hai↗

An AMUSING look at the host of the periodic nuclear transient ASASSN-14ko reveals a second AGN

ABSTRACT We present Multi-Unit Spectroscopic Explorer (MUSE) integral-field spectroscopy of ESO 253−G003, which hosts a known active galactic nucleus (AGN) and the periodic nuclear transient ASASSN-14ko, observed as part of the All-weather MUse Supernova Integral-field of Nearby Galaxies survey. The MUSE observations reveal that the inner region hosts two AGN separated by $1.4\pm 0.1~\rm {kpc}$ (≈1${_{.}^{\prime\prime}}$7). The brighter nucleus has asymmetric broad permitted emission-line profiles and is associated with the archival AGN designation. The fainter nucleus does not have a broad emission-line component but exhibits other AGN characteristics, including $\hbox{$v_{\rm {FWHM}}$} \approx 700~\hbox{km~s$^{-1}$}$ forbidden line emission, $\rm{\log _{10}(\rm{[O\,\small {III}]}/\rm{H\beta})} \approx 1.1$, and high-excitation potential emission lines, such as [Fe vii] λ6086 and He ii λ4686. The host galaxy exhibits a disturbed morphology with large kpc-scale tidal features, potential outflows from both nuclei, and a likely superbubble. A circular relativistic disc model cannot reproduce the asymmetric broad emission-line profiles in the brighter nucleus, but two non-axisymmetric disc models provide good fits to the broad emission-line profiles: an elliptical disc model and a circular disc + spiral arm model. Implications for the periodic nuclear transient ASASSN-14ko are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Structural coordination between active sites of a CRISPR reverse transcriptase-integrase complex

CRISPR-Cas systems provide adaptive immunity in bacteria and archaea, beginning with integration of foreign sequences into the host CRISPR genomic locus and followed by transcription and maturation of CRISPR RNAs (crRNAs). In some CRISPR systems, a reverse transcriptase (RT) fusion to the Cas1 integrase and Cas6 maturase creates a single protein that enables concerted sequence integration and crRNA production. To elucidate how the RT-integrase organizes distinct enzymatic activities, we present the cryo-EM structure of a Cas6-RT-Cas1—Cas2 CRISPR integrase complex. The structure reveals a heterohexamer in which the RT directly contacts the integrase and maturase domains, suggesting functional coordination between all three active sites. Together with biochemical experiments, our data support a model of sequential enzymatic activities that enable CRISPR sequence acquisition from RNA and DNA substrates. These findings highlight an expanded capacity of some CRISPR systems to acquire diverse sequences that direct CRISPR-mediated interference.

59 BASIC BIOLOGICAL SCIENCES↗

Microwave-driven heterogeneous catalysis for activation of dinitrogen to ammonia under atmospheric pressure

This paper presents an innovative approach to producing energy-dense, carbon–neutral liquid ammonia as a means for carrying energy. This approach synergistically integrates microwave reaction chemistry with novel heterogeneous catalysis that decouples dinitrogen activation from high-temperature and high-pressure reactions, altering reaction pathways and increasing ammonia formation rate. Results presented here demonstrate that ammonia synthesis can be conducted at 280 ? and ambient pressure to achieve ~1 mmol ammonia/g cat/h over supported ruthenium catalyst systems utilizing microwave irradiation. It is further shown that adding promoter ions such as potassium, cerium, and barium significantly improves the ammonia production rate over undoped ruthenium-based catalysts. This effect could be attributed to enhanced dielectric loss processes that lead to stronger microwave absorption by the catalyst. Measurement of the equilibrium constant under microwave conditions showed a higher ammonia yield than under thermal equilibrium conditions for both the iron- and ruthenium-based catalysts. Finally, this study also illustrates the advantages of using a variable-frequency microwave reactor for ambient-pressure ammonia synthesis. Mechanistically, investigators believed that the oscillating electric fields of the radiation can couple with adsorbed nitrogen on the surface and accelerate its dissociation. Since dinitrogen dissociation on the surface is rate limiting, this effectively accelerates the reaction.

Hu, Jianli (John)↗

Summary Report of the FY24 DOE Contributions to the GIF VHTR CMVB

The Generation-IV Forum (GIF) Very-High-Temperature Reactor-Computational Methods Validation and Benchmark (VHTR-CMVB) initiative, involving organizations from Korea Atomic Energy Research Institute (KAERI) (South Korea), Institute of Nuclear and New Energy Technology of Tsinghua University (INET) (China), U.S. Department of Energy (DOE) (U.S.), Joint Research Centre (JRC) (Europe), and Japan Atomic Energy Agency (JAEA) (Japan), is dedicated to the verification and validation of tools for High-Temperature Gas-Cooled Reactors (HTGRs) analysis, using data shared by Computational Methods Validation and Benchmark (CMVB) signatories. For FY24, the US DOE CMVB has committed to several critical activities. Under WP1, led by the US, the integration of the High Temperature Gas Cooled Reactor - Pebble-Bed Module (HTR-PM) Phenomena Identification and Ranking Table (PIRT) into the comparative PIRT is progressing, with a new draft of the comparison tables issued earlier this year and currently being utilized by INET for their contribution. Neutronic validation efforts under WP3 include the preparation of the burnup analysis benchmark, preliminary calculations, and the development of reference models and results. In WP2, a validation exercise for hot gas mixing in the lower plenum of HTR-PM is in progress, using experimental data from INET (China) to validate modeling approaches. A model of the experimental facility has been developed using StarCCM+, with initial calculations slated for presentation at the GIF CMVB meeting this fall. Another WP2 activity focuses on validating numerical models for air-cooled Reactor Cavity Cooling System (RCCS) with experimental data from the Wisconsin Madison RCCS facility. A high-fidelity model, developed using NEK-RS, is currently being validated with available data from a low power forced convection test. These efforts are aimed at enhancing and confirming the accuracy of HTGR analysis tools, ensuring their alignment with experimental data and regulatory requirements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗

Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows (IPPD) (Final Report)

This report details the accomplishments from the ASCR funded project “Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows” under the award numbers FWP-66406 and DE-SC0012630, with a focus on the UC San Diego (Award No. DE-SC0012630) part of the accomplishments. We refer to the project as IPPD. The main activities of IPPD were centered on the development and integration of provenance information to capture empirically workflow information and identify the sources of bottlenecks as well as variability, and modeling and simulation to provide insights and predictively explore multiple scenarios for development of advanced techniques for optimization of resources and workflow execution. After a Phase I of the project, a Phase II effort focused on three major aspects: a) observe how data is generated, distributed, and used; b) analyze how data is (repeatedly) consumed with a focus both on repeated patterns and anomalies; and c) explore how to optimize data motion. The project leveraged and extended our existing tools with new research and demonstrated our work on the Belle II workflow suite as well as on workflows from NSLS-II.

97 MATHEMATICS AND COMPUTING↗

Boosting the performances of protonic solid oxide fuel cells for co-production of propylene and electricity from propane by integrating thermo- and electro- catalysis

Protonic solid oxide fuel cells (p-SOFC) integrated with clean thermal energy sources are promising platforms for decarbonized chemical production in addition to power generation, such as on-purpose propylene production from propane dehydrogenation (PDH). The catalytic performance of the conventional nickel-cermet-based anode materials in p-SOFC for propane conversion is restrained by their low active surface area and proneness to coking. In this work, by integration of a highly efficient industry-relevant thermal catalyst PtGa/ZSM-5 for PDH reaction, we demonstrate that both the electrochemical and catalytic performance of the propane-fueled p-SOFC can be effectively enhanced. The PtGa catalyst integrated p-SOFC exhibits a peak power density of 93 mW cm -2 at 600°C, which is greater by about 100% and 50% than that without catalyst or with a perovskite-based (Pr 0.3 Sr 0.7 ) 0.9 Ni 0.1 Ti 0.9 O 3 (PSNT) catalyst layer, respectively. The PDH activity and olefin selectivity of the PtGa catalyst is also significantly higher than that of the PSNT catalyst. In addition, much improved coke tolerance and propylene selectivity (over 90%) compared to the catalyst-free Ni-cermet anode materials were achieved by integrating the industrial catalyst layer. The propane conversion can be further improved by an applied current density, whereas the olefin selectivity is almost unaltered. The excellent performance of the PtGa catalyst integrated p-SOFC is attributed to the high surface area, intrinsically high catalytic activity, selectivity, and anti-coking properties of the catalytic layer for propane conversion. In conclusion, this work provides a general approach and a case study for boosting the performances of p-SOFCs in chemical production by integrating thermo- and electro- catalysis.

30 DIRECT ENERGY CONVERSION↗

Time Disciplined Non-PLL Active Synchronization for Grid Forming Inverters

Two major issues facing grid-forming inverters are synchronism and phase reference inaccuracies. Prior literature has addressed these problems with solutions such as disciplining the phase reference using GPS and active synchronization modes but these methods have not yet been integrated together. This paper serves to unite solutions and develop a means for an inverter to remain synchronized and grid-forming without phase reference inaccuracies through a novel time-disciplined active synchronization phase reference. Further, this work expands upon prior literature on active synchronization to include black-start capabilities. Finally, the time disciplined phase reference is evaluated in Simulink as a grid-forming inverter capable of any synchronization circumstance and assessed by key metrics from modern standards.

blackstart↗

Engineering integration in elementary science classrooms: Effects of disciplinary language scaffolds on English learners' content learning and engineering identity

Abstract Background Limited research examines the effects of integrated science and engineering (SE) instruction emphasizing disciplinary literacy and language activities on engineering identity and content understanding. Far fewer studies target English learners (ELs). Purpose The impact of an SE intervention on the development of science, engineering, and technology knowledge as well as engineering identity was examined. To address ELs' learning needs, the curricular design was built on a validated SE model by integrating (1) developmental, (2) language scaffolds, and (3) culturally based accommodations. Design/Method Separate analysis of variance examined the effects of the intervention on science, engineering, and technology knowledge as well as engineering identity. The relationship among engineering identity and content outcomes was also examined. ELs from kindergarten to second grade classrooms were randomly assigned to the integrated SE group or control group. Results Integrated SE instruction significantly increased ELs' science, engineering, and technology knowledge as well as a substantially developed engineering identity. Overall, ELs' engineering identity is associated with an increase in science, engineering, and technology content knowledge. However, second grade girls' identity development was not associated with learning measures. These correlations suggest the context of the engineering activity may have reinforced gendered stereotypes and reduced the effects for girls' engineering attitudes. Conclusions Integrated SE instruction emphasizing disciplinary literacy and cultural accommodations increases early elementary ELs' learning and engineering identity. Future studies should examine the unique effects of language scaffolds and cultural modifications on student learning and the impact of gender stereotypes on girls' engineering attitudes.

Aguirre‐Muñoz, Zenaida↗

NADH-bound AIF activates the mitochondrial CHCHD4/MIA40 chaperone by a substrate-mimicry mechanism

Mitochondrial metabolism requires the chaperoned import of disulfide-stabilized proteins via CHCHD4/MIA40 and its enigmatic interaction with oxidoreductase Apoptosis-inducing factor (AIF). By crystallizing human CHCHD4’s AIF-interaction domain with an activated AIF dimer, we uncover how NADH allosterically configures AIF to anchor CHCHD4’s β-hairpin and histidine-helix motifs to the inner mitochondrial membrane. The structure further reveals a similarity between the AIF-interaction domain and recognition sequences of CHCHD4 substrates. NMR and X-ray scattering (SAXS) solution measurements, mutational analyses, and biochemistry show that the substrate-mimicking AIF-interaction domain shields CHCHD4’s redox-sensitive active site. Disrupting this shield critically activates CHCHD4 substrate affinity and chaperone activity. Regulatory-domain sequestration by NADH-activated AIF directly stimulates chaperone binding and folding, revealing how AIF mediates CHCHD4 mitochondrial import. These results establish AIF as an integral component of the metazoan disulfide relay and point to NADH-activated dimeric AIF as an organizational import center for CHCHD4 and its substrates. Importantly, AIF regulation of CHCHD4 directly links AIF’s cellular NAD(H) sensing to CHCHD4 chaperone function, suggesting a mechanism to balance tissue-specific oxidative phosphorylation (OXPHOS) capacity with NADH availability.

Brosey, Chris A↗

Thermodynamic control on the decomposition of organic matter across different electron acceptors

The increasing availability of high-resolution characterization of natural organic matter (OM) data has shifted the paradigm of lumped descriptions of OM components and potential microbial activities. Our recent development of a substrate-explicit thermodynamic model uniquely enables incorporating complex OM pools to formulate biogeochemical reaction models based on their elemental compositions. While this previous work facilitates prediction of aerobic respiration of complex OM, it is equally imperative to consider the role of non-oxygenic electron acceptors in regulating OM turnover and the fate of carbon. In this study, we significantly expand our previous model by flexibly incorporating both detailed OM chemistry and electron acceptors other than oxygen. Here, our modeling analysis has revealed substantial variations in the energy status of OM molecules across different soils, which drive the co-occurrence of different electron-accepting processes. We demonstrated the effectiveness of the proposed model using a consistency check with experimental data. Through systematic evaluation of the impact of diverse chemical inputs (both electron donors and acceptors) on OM decomposition, the new model also revealed how key microbial growth parameters such as carbon use efficiency (CUE) and reaction rates vary across different electron-accepting processes. Our model provides a unified framework integrating thermodynamic and kinetic constraints on microbial metabolic activities. It complements traditional kinetic models, which are often designed solely to capture mass fluxes. We conclude that thermodynamic modeling emerges as a powerful tool for describing the mechanisms underlying the interplay between microbial growth and OM chemistry and cycling across different electron acceptors, enhancing our ability to project complex ecosystem behaviors in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗

High resistivity iron-based, thermally stable magnetic material for on-chip integrated inductors

An on-chip magnetic structure includes a palladium activated seed layer and a substantially amorphous magnetic material disposed onto the palladium activated seed layer. The substantially amorphous magnetic material includes nickel in a range from about 50 to about 80 atomic % (at. %) based on the total number of atoms of the magnetic material, iron in a range from about 10 to about 50 at. % based on the total number of atoms of the magnetic material, and phosphorous in a range from about 0.1 to about 30 at. % based on the total number of atoms of the magnetic material. The magnetic material can include boron in a range from about 0.1 to about 5 at. % based on the total number of atoms of the magnetic material.

Deligianni, Hariklia↗

Management and International Sorption Model Collaboration (M4SF-23LL010302062-NEA-TDB)

This progress report (Level 4 Milestone Number M4SF-23LL010302062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Crystalline International Collaborations Activity Number SF-23LL01030206. The activity is focused on our long-term commitment of engaging our partners in international nuclear waste repository research. This includes participation in the Nuclear Energy Agency Thermochemical Database (NEA-TDB) Project and development of methodologies for integrating US and international thermodynamic databases for use in SFWST Generic Disposal System Assessment (GDSA) efforts. A continuing focus for FY23 efforts has been to support the US participation in the NEA-TDB effort (Mavrik Zavarin replaced Cindy Atkins-Duffin on the NEA-TDB Management Board (MB) and Executive Group (EG)) and developing mechanisms for integration of NEA-TDB thermochemical data with LLNL’s SUPCRTNE thermodynamic database that supports the SFWST GDSA activities. This effort is coordinated with the Argillite work package SUPCRTNE database development efforts. The goal is to provide a downloadable database that will be hosted on a LLNL website which integrates NEA-TDB data into the LLNL SUPCRTNE database where appropriate. As part of our international activities, we continue our effort to integrate international sorption databases into L-SCIE (Zavarin et al., 2022b). We presented opportunities to include sorption in the next phase of NEA-TDB efforts at the April 2023 EG meeting in Paris. FY23 efforts focused on ensuring interoperable database development across multiple international database development activities. The overall goal is to produce an open source database that can be shared and integrated with multiple nuclear waste programs internationally and harness modern data science workflows and algorithms to incorporate these new approaches into reactive transport and performance assessment models. In collaboration with our Helmholtz Zentrum Dresden Rossendorf partners, we recently demonstrated the power of FAIR open source databases by fitting iron oxide (hydrous ferric oxide, goethite, hematite, and magnetite) protolysis constants to all available L-SCIE data. The results were submitted as a manuscript to J. Colloid Interface Science. This work will inform future metal sorption studies on a variety of iron oxides in order to discern the most appropriate acidity constants and surface complexation modeling constructs to account for pH-dependent mineral surface charge behavior. This work also explored automated surface complexation model development workflows in order to generate higher throughput model input files for a more facile incorporation into GDSA activities.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗