Crystallographic and calorimetric analysis on Pleurotus ostreatus lectin and its sugar complexes - promiscuous binding driven by geometry
Abstract not provided
Vajravijayan, S.↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Secondary porosity prediction in complex carbonate reefs using 3D CT scan image analysis and machine learning
Development and preservation of carbonate porosity and permeability are critical to characterizing reservoirs. However, secondary porosity, such as vugs and fractures, are difficult to identify and require collection of expensive wireline tools or core sampling. Wireline logs and cores have traditionally been used to identify the presence of secondary porosity but fail to quantify the contribution to total reservoir porosity. Additionally, advanced wireline logs and core are not readily available for most wells. Dual energy CT scans were collected on whole core from the A-1 Carbonate and Brown Niagaran formations drawn from six wells in northern Michigan. 3D analysis techniques were applied to identify and isolate secondary porosity features. A series of machine learning and data analytics techniques were applied to the dataset to predict secondary porosity features on basic wireline logs. The predictive model successfully predicted secondary porosity with high confidence.
02 PETROLEUM↗
Ground and excited states analysis of alkali metal ethylenediamine and crown ether complexes
Quantum calculations show that ethylenediamine and crown ethers polarize and displace valence electrons of alkali metals to the periphery of the formed complex. The nature of the building blocks of expanded metals and electrides is discussed.
Ariyarathna, Isuru R.↗
Structural analysis of the PTEN:P-Rex2 signaling complex reveals how cancer-associated mutations coordinate to hyperactivate Rac1
The dual-specificity phosphatase PTEN functions as a tumor suppressor by hydrolyzing PI(3,4,5)P 3 to PI(4,5)P 2 to inhibit PI3K-AKT signaling and cellular proliferation. P-Rex2 is a guanine nucleotide exchange factor for Rho GTPases and can be activated by Gβγ subunits downstream of G protein–coupled receptor signaling and by PI(3,4,5)P 3 downstream of receptor tyrosine kinases. The PTEN:P-Rex2 complex is a commonly mutated signaling node in metastatic cancer. Assembly of the PTEN:P-Rex2 complex inhibits the activity of both proteins, and its dysregulation can drive PI3K-AKT signaling and cellular proliferation. Here, using cross-linking mass spectrometry and functional studies, we gained mechanistic insights into PTEN:P-Rex2 complex assembly and coinhibition. We found that PTEN was anchored to P-Rex2 by interactions between the PDZ-interacting motif in the PTEN C-terminal tail and the second PDZ domain of P-Rex2. This interaction bridged PTEN across the P-Rex2 surface, preventing PI(3,4,5)P 3 hydrolysis. Conversely, PTEN both allosterically promoted an autoinhibited conformation of P-Rex2 and blocked its binding to Gβγ. In addition, we observed that the PTEN-deactivating mutations and P-Rex2 truncations combined to drive Rac1 activation to a greater extent than did either single variant alone. These insights enabled us to propose a class of gain-of-function, cancer-associated mutations within the PTEN:P-Rex2 interface that uncouple PTEN from the inhibition of Rac1 signaling.
D’Andrea, Laura↗
HPC for the EEC: Industrial Trade Tools for the Aging Energy Infrastructure
The petrochemical and refining sectors are challenged with reliably delivering safer and cleaner energy to US consumers, while meeting an ever-growing global demand. The petrochemical and refining infrastructure in the USA is aging, and corrosion and damage mechanisms are constant threats to mechanical integrity, safety, and profitability. However, governments and industry stakeholders are reluctant to replace or upgrade the existing infrastructure due to the immense cost. To better understand and mitigate the risks of aging energy infrastructure, strong technical analysis capabilities, combined with optimized monitoring and decision making, is critical. Today, this is accomplished via complex simulations and data analysis. To this end, advanced High-Performance-Computing (HPC) software will be leveraged and integrated in easy-to-use industrial trade tools, to lower the barrier for new users, increase the ease of access for experienced users, and allow for smarter decisions to be made in the midstream and downstream energy sectors.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Real-Time Coupling of Geographically Distributed Research Infrastructures: Taxonomy, Overview, and Real-World Smart Grid Applications
Novel concepts enabling a resilient future power system and their subsequent experimental evaluation are experiencing a steadily growing challenge: large scale complexity and questionable scalability. The requirements on a research infrastructure (RI) to cope with the trends of such a dynamic system therefore grow in size, diversity and costs, making the feasibility of rigorous advancements questionable by a single RI. Analysis of large scale system complexity has been made possible by the real-time coupling of geographically separated RIs undertaking geographically distributed simulations (GDS), the concept of which brings the equipment, models and expertise of independent RIs, in combination, to optimally address the challenge. This article presents the outputs of IEEE PES Task Force on Interfacing Techniques for Simulation Tools towards standardization of GDS as a concept. First, the taxonomy for setups utilized for GDS is established followed by a comprehensive overview of the advancements in real-time couplings reported in literature. The overview encompasses fundamental technological design considerations for GDS. The article further presents four application oriented case studies (real-world implementations) where GDS setups have been utilized, demonstrating their practicality and potential in enabling the analysis of future complex power systems.
distributed laboratories↗
Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis
Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems
Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Low-cost calculation and analysis of 2D IR spectra of model diiron trinitrosyl complexes in the NO stretch region with vibrational perturbation theory
Two-dimensional infrared spectroscopy offers unique capabilities for probing vibrational coupling in complex metal–ligand systems. In this paper, we combine two-dimensional infrared spectroscopy with vibrational perturbation theory to investigate vibrational coupling in a diiron trinitrosyl complex across three stable redox states. Although these systems are challenging for electronic structure methods, we demonstrate that key features of experimental 2D IR spectra can be accurately reproduced using reduced-dimensional anharmonic calculations with a small harmonic frequency scaling. Analysis reveals that N–O stretching modes maintain high locality across all redox states, with coupling patterns that directly reflect variations in Fe–N bond strength. Using curvilinear coordinate analysis, we demonstrate these differences result from systematic changes in cubic anharmonic force constants rather than mode delocalization. Our results establish N–O stretches as sensitive probes of metal–ligand bonding strength, expanding the toolkit for studying biologically relevant nitrosyl complexes.
Moran, Hayden A. [Texas A&M University, College St↗
DFT-based investigation of solvation of Nd(III)/Yb(III) cations in room-temperature ionic-liquid
We report a DFT study on the solvation of bare rare-earth (RE) cations [Nd(III) and Yb(III)] in the room-temperature ionic-liquid (RTIL) based on 1,3-dimethyl-imidazolium + , PF 6 - , [MMI][PF 6 ]. In the present article, we aim to investigate whether the chosen RTIL can preferentially solvate any of the RE cations under study. First, the RTIL binding to the RE cation is studied in the gas phase, and then explored with continuum solvation model employing RTIL parameters. First, we considered the formation of the first solvation shell, where the PF 6 - anions directly bond with the Ln(III) cation. We then further surrounded the first solvation shell with [MMI]+ cations to form the second solvation shell. The stability of PF 6 - coordinated complexes is studied by calculating the binding energy values. The number of PF 6 - anions for both Ln(III) cations starts with three ligands and goes until the maximum binding energy in the RTIL medium is reached. The coordination number and binding modes of PF 6 - depend on the size of the RE cation. Comparing the binding energy values between the RE cations for the first solvation shell complexes, it is noticed that Yb-complexes have relatively greater binding energy than Nd-complexes. We have further performed a Boltzmann population analysis to find out the most dominant conformer among each category of PF 6 - coordinated complexes. A study using Natural Population Analysis shows that after complexation with PF 6 - the charge on the Yb-centers lower to a greater extent than Nd-centers, implying stronger bonding between Yb and PF 6 - , which is in harmony with the binding energy analysis. Overall, the computational investigation provides an in-depth understanding of the complexation phenomena of RE cations in RTIL, which can be useful for the practical separation of RE cations using RTIL.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Design Engineer Qualification Standard
This document describes the training and qualification requirements for the Design Engineer (DE) position at Los Alamos National Laboratory (LANL). A Design Engineer translates design inputs into design output documents using design analysis and calculations, national codes and standards, DOE orders and standards, maintenance considerations, LANL best practices, and complex-wide lessons learned. Analysis performed by a DE requires sufficient detail in the purpose, method, assumptions, design input, references, and units such that a qualified engineer is able to review and understand the content and verify the adequacy of the results without recourse to the originator. A DE is assigned to a project by Engineering Management.
42 ENGINEERING↗
Functional and transcriptional characterization of complex neuronal co-cultures
Brain-on-a-chip systems are designed to simulate brain activity using traditional in vitro cell culture on an engineered platform. It is a noninvasive tool to screen new drugs, evaluate toxicants, and elucidate disease mechanisms. However, successful recapitulation of brain function on these systems is dependent on the complexity of the cell culture. In this study, we increased cellular complexity of traditional (simple) neuronal cultures by co-culturing with astrocytes and oligodendrocyte precursor cells (complex culture). We evaluated and compared neuronal activity (e.g., network formation and maturation), cellular composition in long-term culture, and the transcriptome of the two cultures. Compared to simple cultures, neurons from complex co-cultures exhibited earlier synapse and network development and maturation, which was supported by localized synaptophysin expression, up-regulation of genes involved in mature neuronal processes, and synchronized neural network activity. Also, mature oligodendrocytes and reactive astrocytes were only detected in complex cultures upon transcriptomic analysis of age-matched cultures. Functionally, the GABA antagonist bicuculline had a greater influence on bursting activity in complex versus simple cultures. Collectively, the cellular complexity of brain-on-a-chip systems intrinsically develops cell type-specific phenotypes relevant to the brain while accelerating the maturation of neuronal networks, important features underdeveloped in traditional cultures.
59 BASIC BIOLOGICAL SCIENCES↗
Core Analysis Report (Deliverable 6.1.a)
Establishing an Early CO2 Storage Complex in Kemper County, Mississippi (ECO2S): Core Analysis Report (Deliverable 6.1.a)
Koperna, George↗
Numerical Analysis of Regular Material Point Method and its Application to Multiphase Flows
The material point method (MPM) is gaining wide popularity in engineering research to model and simulate complex multiphase flow dynamics. The method relies on solving the governing equations of motion and transport in a Lagrangian framework using particles also known as material points. The fluid and kinematic properties are stored on the material points while the spatial gradient calculation and temporal integration are performed on a background grid. This Lagrangian framework allows for large deformations, easy integration of constitutive models, and direct import of complex geometries as particles. However, despite their increasing popularity, very few studies have addressed the issues of numerical resolution and stability of MPM techniques. The presence of additional factors such as the number of material points-per-cell, the location of the material points, the CFL-like condition used in time update, and the grid shape functions also increase the complexity of the error analysis when compared to other finite element methods. In this presentation, we analyze the various forms of error incurred in the application of MPM to continuum mechanics and multiphase flows. The effect of the previously mentioned factors on the error dynamics is studied. The application of these principles to canonical and industrial problems is also presented.
high pressure reverse osmosis↗
Life Cycle Analysis of Greenhouse Gas Emissions for the Niagaran Reef Complex CO 2 -EOR Operations
The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. A greenhouse gas emissions life cycle analysis (LCA) was completed for 22 years of carbon dioxide-enhanced oil recovery (CO 2 -EOR) operations at the Niagaran reef complex in the northern Michigan Basin based on research by the MRCSP. The objective of the greenhouse gas LCA was to account for the total greenhouse gas emissions generated through the CO 2 -EOR process. Methane produced from the 300 to 500 meter-deep Antrim shale has CO 2 content ranging from 5 percent to 30 percent. Therefore, the produced gas stream is gathered outside of Gaylord, Michigan, at the Chester 10 central gas processing plant, and run through an amine-based CO 2 separation process to remove the CO 2 so the methane can be sold to the market. The CO 2 is periodically dehydrated, compressed, and transported via pipeline for CO 2 -EOR in nearby 5,000- to 6,500-foot (1500-2000 m) deep carbonate Niagaran reefs. The produced mixture of oil, water, and CO 2 is separated at the Dover 36 oil processing facility. The processed CO 2 is recycled to the reefs for CO 2 -EOR in a closed loop system. During this process, a portion of the CO2 remains permanently stored in the reefs.
01 COAL, LIGNITE, AND PEAT↗
Polyoxometalate-Assisted Crystallization: A General Strategy Enabling Structural Characterization of Molecular Radium Complexes
A fundamental understanding of radium (Ra) coordination chemistry has been hindered by the scarcity and radiological hazards of 226 Ra, leaving the structural characterization of molecular Ra complexes almost entirely unexplored. Here, we introduce a polyoxometalate (POM)-assisted crystallization strategy that enables single-crystal X-ray diffraction analysis of Ra–chelator complexes from microgram-scale samples. Employing the plenary Keggin anion [SiW 12 O 40 ] 4– , we isolated and structurally characterized Ra 2+ complexes of 18-crown-6 and the bis-picolinate macrocycle macropa, together with their Sr 2+ and Ba 2+ analogues. The resulting structures reveal systematic, size-dependent trends in coordination number and metal-donor distances across the alkaline earth series and provide the first direct experimental measurements of Ra–N and Ra–OCOO bond distances. Together, these results establish POM-assisted crystallization as a robust approach for obtaining solid-state structural information on Ra 2+ complexes of organic chelators, opening new opportunities to advance the coordination chemistry needed to fully realize radium’s potential in isotope production and targeted radiotherapy. More broadly, this approach expands the experimental toolkit available for studying scarce, highly radioactive elements accessible only in microgram quantities.
Anions↗
Metabolic complexity drives divergence in microbial communities
Microbial communities are shaped by environmental metabolites, but the principles that govern whether different communities will converge or diverge in any given condition remain unknown, posing fundamental questions about the feasibility of microbiome engineering. Here, in this work, we studied the longitudinal assembly dynamics of a set of natural microbial communities grown in laboratory conditions of increasing metabolic complexity. We found that different microbial communities tend to become similar to each other when grown in metabolically simple conditions, but they diverge in composition as the metabolic complexity of the environment increases, a phenomenon we refer to as the divergence-complexity effect. A comparative analysis of these communities revealed that this divergence is driven by community diversity and by the assortment of specialist taxa capable of degrading complex metabolites. An ecological model of community dynamics indicates that the hierarchical structure of metabolism itself, where complex molecules are enzymatically degraded into progressively simpler ones that then participate in cross-feeding between community members, is necessary and sufficient to recapitulate our experimental observations. In addition to helping understand the role of the environment in community assembly, the divergence-complexity effect can provide insight into which environments support multiple community states, enabling the search for desired ecosystem functions towards microbiome engineering applications.
59 BASIC BIOLOGICAL SCIENCES↗
Analysis of Transient Pressure and Rate Data in a Complex of Enhanced Oil Recovery Fields in Northern Michigan
This report discusses the methodology and results of various types of analyses performed with reservoir pressure and injection rate data data, with the primary objective of characterizing the in-situ permeability of the formation of interest (i.e., reservoir undergoing injection and/or production).
54 ENVIRONMENTAL SCIENCES↗