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At least 433 records · Page 24

Utah FORGE 4-2492: Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery - Workshop Presentation

This is a presentation on the Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery Efficiency at the Utah FORGE Site project by The University of Texas at Austin, presented by Professor Mukul M. Sharma. The project's objectives were to place fractures uniformly in a horizontal well (improve cluster efficiency) to ensure uniform distribution of flow into all hydraulic fractures, maximize the area of the created fracture network, ensure connectivity of the fractures from the injector to the producer, and optimize fracture size. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 4-2541: Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design - Workshop Presentation

This is a presentation on the Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design at Utah FORGE project by Fervo Energy, presented by Sireesh Dadi. The project's objective was to develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system. These factors include: achieving sufficient injectivity to support high cross-well flow rates, distributing flow evenly across the wellbore and reservoir, and overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 5-2428: Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior - Workshop Presentation

This is a presentation on the Fracture Permeability Impact on Seismic Slip Behavior project by Lawrence Livermore National Laboratory, presented by Dr. Kayla A. Kroll. The project's objective is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemical (THMC) workflow that includes evaluation of induced seismic slip in EGS reservoirs. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 5-2557: Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes - Workshop Presentation

This is a presentation on the Role of Fluid and Temperature in Fracture Mechanics and Coupled Thermo-Hydro-Mechanical-Chemical (THMC) Processes for Enhanced Geothermal Systems project by Purdue University, presented by Distinguished Professor of Physics & Astronomy, Laura J. Pyrak-Nolte. The project's objective was to develop and validate a macroscopic model that accounts for local deformation/frictional behavior, seismic/aseismic behavior, chemical reactions, and determine the adequacy of classic Coulomb failure vs. rate-and-state friction. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 5-2565: Hydrothermal Evolution of Fracture Properties - Workshop Presentation

This is a presentation on the Evolution of Permeability and Strength Recovery of Shear Fractures Under Hydrothermal Conditions project by the U.S. Geological Survey, presented by Dr. David Lockner. The project's objective was to determine how thermal, hydraulic, mechanical, and chemical processes affect the sustainability of fracture networks in geothermal reservoirs and provide strategies for improved EGS techniques that maximize thermal coupling and increase reservoir longevity. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 5-2615: Thermo-poromechanical Response of Fractured Rock - Workshop Presentation

This is a presentation on the Experimental Determination and Modeling-Informed Analysis of Thermo-poromechanical Response of Fractured Rock for Application to Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Prof. The project objective is to improve understanding and control of coupled thermo-poromechanical (or thermo-hydro-mechanical- TPM) processes in reservoir development, and to study any role in interpretations of the fracture closure. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Molecular Hypernetworks for Exploration of Multi-Dimensional Metabolomics Data (Chyper)

Orthogonal separations of data from high-resolution mass spectrometry can provide insight into sample composition and help address the challenge of complete annotation of molecules in untargeted metabolomics. “Molecular networks” (MNs), as used, for example, in the Global Natural Products Social Molecular Networking platform, are an increasingly popular computational strategy for exploring and visualizing molecular relationships and improving annotation. MNs use graph representations to show the relationships between measured multidimensional data features. MNs also show promise for using network science algorithms to automatically identify targets for annotation candidates and to dereplicate features associated to a single molecular identity. However, more advanced methods may better represent the complexity present in samples. Our work aims to increase confidence in annotation propagation by extending molecular network methods to include “molecular hypernetworks” (MHNs), able to natively represent multiway relationships among observations supporting both human and analytical processing. In this paper we first introduce MHNs illustrated with simple examples, and demonstrate how to build them from liquid chromatography- and ion mobility spectrometry- separated MS data. We then describe a method to construct MHNs directly from existing MNs as their “clique reconstructions”, demonstrating their utility by comparing examples of previously published graph-based MNs to their respective MHNs.

59 BASIC BIOLOGICAL SCIENCES↗

ARES. III. Unveiling the Two Faces of KELT-7 b with HST WFC3

We present the analysis of the hot-Jupiter KELT-7 b using transmission and emission spectroscopy from the Hubble Space Telescope, both taken with the Wide Field Camera 3. Our study uncovers a rich transmission spectrum that is consistent with a cloud-free atmosphere and suggests the presence of H{sub 2}O and H{sup −}. In contrast, the extracted emission spectrum does not contain strong absorption features and, although it is not consistent with a simple blackbody, it can be explained by a varying temperature–pressure profile, collision induced absorption, and H{sup −}. KELT-7 b had also been studied with other space-based instruments and we explore the effects of introducing these additional data sets. Further observations with Hubble, or the next generation of space-based telescopes, are needed to allow for the optical opacity source in transmission to be confirmed and for molecular features to be disentangled in emission.

79 ASTRONOMY AND ASTROPHYSICS↗

Database development and exploration of process–microstructure relationships using variational autoencoders

The paper demonstrates graphical representation of a large database containing process–microstructure relationships using an unsupervised machine learning algorithm. Correlating microstructural features to processing is an essential first step to answer the difficult problem of process sequence design. Here, a large database of 346,200 orientation distribution functions resulting from a variety of process sequences is constructed, where each sequence comprises up to four stages of tension, compression and rolling along different directions in various permutations. This open-source database is constructed for collaborative development of process design algorithms. The paper demonstrates a novel application of the large database: graphical representation of texture–process relationships. A variational autoencoder is used to reduce the entire database to a two dimensional latent space where variations in processes and properties can be visualized. Using proximity analysis in this latent space, we can quickly unearth multiple process solutions to the problem of texture or property design.

36 MATERIALS SCIENCE↗

Exploring Demographic Factors Behind the User Preferences in Ridesharing Services

Ridesharing is an increasingly prevalent form of transportation. Personal and pooled rideshare services are the two modes of ridesharing available on the market. While personal rideshare features higher time efficiency and better service experience, especially in terms of privacy, pooled rideshare has better energy efficiency and can reduce traffic congestion. To encourage users to utilize pooled rideshare, it is crucial to understand the factors behind preferences between pooled and personal rideshare services. This study conducted a survey study on a sample of 2,884 participants from the U.S. The stated-choice method was employed to collect the usage rate of pooled rideshare in designed scenarios. A detailed analysis of pooled rideshare usage rates among participants from different demographic backgrounds was performed. The results demonstrated demographic factors related to variations in pooled rideshare usage rates. Findings from this study explore the impacts of demographic factors on people's choices in ridesharing and provide important information for the modeling and optimization of ridesharing transportation systems.

Su, Haotian↗

Ultrasonic Testing (UT) and Computed Tomography (CT) Comparative Scanning of Proposed Additive Manufacturing Reference Standard

This report presents qualitative results of ultrasonic full matrix capture/total focusing method (FMC/TFM) scanning of two series of blocks, additively manufactured by powder bed fusion, containing a variety of internal features and structures that would not be achievable by conventional manufacturing techniques. The purpose of the first series of additively manufactured (AM) blocks was to explore the possibility of building calibration blocks for FMC/TFM ultrasonic testing (UT). It was confirmed that AM is a suitable candidate for generation of unusual and novel reflector forms, such as rotating slots, purposely embedded voids, and tapering holes, and that FMC/TFM was very capable of characterizing them. The intended use of the second series of AM blocks was as UT reference blocks to characterize the AM process quality or the interrogating UT technique. The larger block in this series was scanned from multiple faces, using multiple UT methods (conventional UT and FMC/TFM) and X-ray computed tomography for comparative purposes. The performance of each method was quantified by a metric corresponding to the detection limit of each feature, and the quantitative results are discussed.

36 MATERIALS SCIENCE↗

Using anion photoelectron spectroscopy of cluster models to gain insights into mechanisms of catalyst-mediated H 2 production from water

We report that metal oxide cluster models of catalyst materials offer a powerful platform for probing the molecular-scale features and interactions that govern catalysis. This perspective gives an overview of studies implementing the combination of anion photoelectron (PE) spectroscopy and density functional theory calculations toward exploring cluster models of metal oxides and metal-oxide supported Pt that catalytically drive the hydrogen evolution reaction (HER) or the water–gas shift reaction. The utility in the combination of these experimental and computational techniques lies in our ability to unambiguously determine electronic and molecular structures, which can then connect to results of reactivity studies. In particular, we focus on the activity of oxygen vacancies modeled by suboxide clusters, the critical mechanistic step of forming proximal metal hydride and hydroxide groups as a prerequisite for H2 production, and the structural features that lead to trapped dihydroxide groups. The pronounced asymmetric oxidation found in heterometallic group 6 oxides and near-neighbor group 5/group 6 results in higher activity toward water, while group 7/group 6 oxides form very specific stoichiometries that suggest facile regeneration. Studies on the trans-periodic combination of cerium oxide and platinum as a model for ceria supported Pt atoms and nanoparticles reveal striking negative charge accumulation by Pt, which, combined with the ionic conductivity of ceria, suggests a mechanism for the exceptionally high activity of this system towards the water–gas shift reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Radiation-Induced Noise Resilience of Neuromorphic Architectures

Neuromorphic event-based networks use asynchronous time-dependent information to extract features from input data that can allow for edge-based distributed applications such as object recognition. The noise resilience properties of such networks, especially in the context of space applications, are yet to be explored. In this paper, we use the hierarchy of time surfaces (HOTS) algorithm, which is one of the neuromorphic algorithms, to understand the least and most resilient modules in a neuromorphic network. The HOTS algorithm relies on the computing of time surfaces that maps the temporal delays between neighboring pixels into normalized features that involve many computations that are also found in other neuromorphic networks such as exponential decays, distance computations, etcetera. We implemented HOTS on a Digilent PYNQ board with a Xilinx Zynq 7020 system on a chip, and we subjected the boards running the HOTS network inference to neutron radiation at the Los Alamos Neutron Science Center. Furthermore, we used simulation models from our previous similar experiments on the event-based sensor to create a neutron induced noise model to quantify the effect of this noise on the overall performance of the network. This experiment provides the preliminary measurements of the reliability of the HOTS algorithm and proposes methods to create a more reliable HOTS architecture in future spacecraft missions.

Engineering↗

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Abstract Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal ( RCSB.org ) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal ( PDB101.RCSB.org ) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org ; and (v) supports training, outreach, and education via PDB101.RCSB.org . New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

59 BASIC BIOLOGICAL SCIENCES↗

Cancer/testis antigen LDHC promotes proliferation and metastasis by activating the PI3K/Akt/GSK-3β-signaling pathway and the in lung adenocarcinoma

The cancer/testis antigen lactate dehydrogenase-C4 (LDHC) is a specific isoenzyme of the LDH family that regulates invasion and metastasis in some malignancies; however, little is known regarding its role in progression of lung adenocarcinoma (LUAD). Thus, we investigated LDHC expression by immunohistochemistry, and analyzed its clinical significance in 88 LUAD specimens. The role and molecular mechanisms subserving LDHC in cellular proliferation, migration, and invasion were explored both in vitro and in vivo. As a result, we found that high LDHC expression was significantly correlated with clinicopathological features of aggressive LUAD and a poor prognosis. Overexpression of LDHC induced LUAD cells to produce lactate and ATP, increased their metastatic and invasive potential—, and accelerated xenograft tumor growth. We further demonstrated that overexpression of LDHC affected the expression of cell proliferation-related proteins (cyclin D1 and c-Myc) and epithelial-mesenchymal transition (EMT)-related proteins (MMP-2, MMP-9, E-cadherin, Vimentin, Twist, Slug, and Snail) both in vitro and in vivo. Finally, excessive activation of LDHC enhanced the phosphorylation levels of AKT and GSK-3β, revealing activation of the PI3K/Akt/GSK-3β oncogenic-signaling pathways. Treatment with a PI3K inhibitor reversed the effects of LDHC overexpression by inhibiting cellular proliferation, migration, and invasion, with diminished levels of p-Akt and p-GSK3β. PI3K inhibition also reversed cell proliferation-related and EMT-related proteins in LDHC-overexpressing A549 cells. In conclusion, LDHC promotes proliferation, migration, invasion, and EMT in LUAD cells via activation of the PI3K/Akt/GSK-3β pathway.

60 APPLIED LIFE SCIENCES↗

Biosystems Design by Machine Learning

Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. Yet, the intricate connectivity and complexity of biosystems pose a major hurdle in designing biosystems with desired features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patterns within complicated biological data across multiple scales of analysis and can augment biosystems design applications by predicting new candidates for optimized performance. ML is being used at every stage of biosystems design to help find non-obvious engineering solutions with fewer design iterations. In this review, we first describe commonly used models and modeling paradigms within ML. We then discuss some applications of these models that have already shown success in biotechnological applications. Moreover, we discuss successful applications at all scales of biosystems design, including nucleic acids, genetic circuits, proteins, pathways, genomes, and bioprocess. Lastly, we discuss some limitations of these methods and potential solutions as well as prospects of the combination of ML and biosystems design.

59 BASIC BIOLOGICAL SCIENCES↗

Discovery of tunable and soluble organic emitters for solid-state lasers with a self-driving laboratory

We have recently demonstrated the ability of using self-driving laboratories for AI-driven searches of organic emitters for solid-state lasing devices. Our past workflow featured solubility challenges for such large molecular moieties. In this next-generation study, we return to the drawing board to explore a family of com-pounds that are much solution processable and composed of a set of electronic cores that provide a broader color response. Out of 252 potential candidates,and with guidance from DFT calculations, we selectively perform a compre-hensive study exploring 51 fluorene-based A-B-A type organic laser oligomers, armed with our self-driving lab. The candidates range from simple hydrocarbon molecules to complex hetero atom-mixed molecules. As a result of this study, we highlight diketopyrrolopyrrole and benzodiazole derivatives for their largely red-shifted emissions. Furthermore, we investigate the effect of color change aris-ing from hetero atom permutation, fluorine addition, thiophene coupling, and a combination of fluorine addition and thiophene coupling. Amplified spontaneous emission (ASE) measurements in the solid state further corroborate the lasing potential of selected candidates, reinforcing their suitability for future device applications. The computational study with density functional theory confirms the experimental results.

fluorescence↗

Universal chemomechanical design rules for solid-ion conductors to prevent dendrite formation in lithium metal batteries

Dendrite formation during electrodeposition while charging lithium metal batteries compromises their safety. Although high-shear-modulus ( G s ) solid-ion conductors (SICs) have been prioritized to resolve the pressure-driven instabilities that lead to dendrite propagation and cell shorting, it is unclear whether these or alternatives are needed to guide uniform lithium electrodeposition, which is intrinsically density-driven. Here, we show that SICs can be designed within a universal chemomechanical paradigm to access either pressure-driven dendrite-blocking or density-driven dendrite-suppressing properties, but not both. This dichotomy reflects the competing influence of the SIC’s mechanical properties and the partial molar volume of Li + $(V_{\mathrm{Li}^+})$ relative to those of the lithium anode ( G Li and V Li ) on plating outcomes. Within this paradigm, we explore SICs in a previously unrecognized dendrite-suppressing regime that are concomitantly ‘soft’, as is typical of polymer electrolytes, but feature an atypically low $(V_{\mathrm{Li}^+})$ that is more reminiscent of ‘hard’ ceramics. Li plating (1 mA cm -2 ; T = 20 °C) mediated by these SICs is uniform, as revealed using synchrotron hard X-ray microtomography. As a result, cell cycle life is extended, even when assembled with thin Li anodes (~30 µm) and either high-voltage NMC-622 cathodes (1.44 mAh cm -2 ) or high-capacity sulfur cathodes (3.02 mAh cm -2 ).

25 ENERGY STORAGE↗