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At least 577 records · Page 32

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↗

Structural and functional analysis of the human POT1-TPP1 telomeric complex

POT1 and TPP1 are part of the shelterin complex and are essential for telomere length regulation and maintenance. Naturally occurring mutations of the telomeric POT1–TPP1 complex are implicated in familial glioma, melanoma and chronic lymphocytic leukaemia. Here we report the atomic structure of the interacting portion of the human telomeric POT1–TPP1 complex and suggest how several of these mutations contribute to malignant cancer. The POT1 C-terminus (POT1C) forms a bilobal structure consisting of an OB-fold and a holiday junction resolvase domain. TPP1 consists of several loops and helices involved in extensive interactions with POT1C. Biochemical data shows that several of the cancer-associated mutations, partially disrupt the POT1–TPP1 complex, which affects its ability to bind telomeric DNA efficiently. A defective POT1–TPP1 complex leads to longer and fragile telomeres, which in turn promotes genomic instability and cancer.

60 APPLIED LIFE SCIENCES↗

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↗

Evaluation of Sedimentary Structure Near the Advanced Test Reactor Complex at the Idaho National Laboratory

An analysis of relevant sediment stratigraphy near Idaho National Laboratory’s Advanced Test Reactor Complex in support of the proposed remote-handled low-level waste disposal facility is presented. The scope of analysis includes a geostatistical evaluation of sedimentary interbed top elevations and thicknesses compiled for wells near the Advanced Test Reactor Complex from land surface to the elevation of the water table. It also includes an evaluation of expected sediment texture and composition based on information contained in existing reports. Finally, based on this analysis, recommendations for characterization well spacing and appropriate transport model dimensionality are made.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

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↗

Crystal structure of Mdm12 and combinatorial reconstitution of Mdm12/Mmm1 ERMES complexes for structural studies

Membrane contact sites between organelles serve as molecular hubs for the exchange of metabolites and signals. In yeast, the Endoplasmic Reticulum – Mitochondrion Encounter Structure (ERMES) tethers these two organelles likely to facilitate the non-vesicular exchange of essential phospholipids. Present in Fungi and Amoebas but not in Metazoans, ERMES is composed of five distinct subunits; among those, Mdm12, Mmm1 and Mdm34 each contain an SMP domain functioning as a lipid transfer module. We previously showed that the SMP domains of Mdm12 and Mmm1 form a hetero-tetramer. Here we describe our strategy to diversify the number of Mdm12/Mmm1 complexes suited for structural studies. We use sequence analysis of orthologues combined to protein engineering of disordered regions to guide the design of protein constructs and expand the repertoire of Mdm12/Mmm1 complexes more likely to crystallize. Using this combinatorial approach we report crystals of Mdm12/Mmm1 ERMES complexes currently diffracting to 4.5 Å resolution and a new structure of Mdm12 solved at 4.1 Å resolution. Our structure reveals a monomeric form of Mdm12 with a conformationally dynamic N-terminal β-strand; it differs from a previously reported homodimeric structure where the N-terminal β strands where swapped to promote dimerization. Based on our electron microscopy data, we propose a refined pseudo-atomic model of the Mdm12/Mmm1 complex that agrees with our crystallographic and small-angle X-ray scattering (SAXS) solution data. - Highlights: • We solved a 4.1 Å resolution crystal structure of Mdm12, the soluble subunit of ERMES. • The two Mdm12 apo monomers differ in the conformation of their N-terminal β-strands. • We reconstituted and crystallized two distinct Mdm12/Mmm1 complexes. • SAXS analysis of the complexes agrees with our previous electron microscopy data. • The structure suggests a head-to-tail association in the Mdm12/Mmm1 complex.

60 APPLIED LIFE SCIENCES↗

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↗

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↗