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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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At least 37 records · Page 2

High–Capacity Splitting of Mono– and Dibranched Hexane Isomers by a Robust Zinc–Based Metal–Organic Framework

High-efficiency separation of C 6 alkanes, particularly the mono- and dibranched isomers by using porous solids, is of paramount significance in the petrochemical industry and, remains a daunting challenge. In this work, we report the complete separation of linear/monobranched hexanes from their dibranched isomers through selective size-exclusion by a microporous MOF, Zn-tcpt (H3tcpt=2,4,6-tris(4-carboxyphenoxy)-1,3,5-triazine), with a two-fold interpenetrated structure of hms nets. Importantly, its adsorption capacity and selectivity are notably higher than those of the previously reported adsorbents that can split mono- and dibranched alkane isomers. Dynamic breakthrough measurements verify the excellent separation of C 6 alkane isomers by Zn-tcpt, and the size-exclusion based separation mechanism has been confirmed by ab initio materials modeling. Furthermore, the high-efficiency separation of alkane isomers by Zn-tcpt can be attributed to its optimal pore dimensions as well as high porosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature–Programmed Separation of Hexane Isomers by a Porous Calcium Chloranilate Metal–Organic Framework

The full separation of alkane isomers as a function of different degrees of branching remains a daunting challenge due to its stringent requirement with respect to pore dimensions of the adsorbents. In this work, we report a novel microporous coordination network built on calcium (II) and chloranilate. The compound has a flexible framework and exhibits temperature-dependent adsorption behavior toward hexane isomers. At 30 °C, it accommodates substantial amounts of linear and monobranched hexanes but fully excludes their dibranched isomer, and at elevated temperatures such as 150 °C, it acts as a splitter for linear and branched alkanes. Its capability of efficient discrimination of hexane isomers as a function of branching is verified by experimental breakthrough measurements. Furthermore, ab initio calculations have uncovered the underlying selective size-exclusion separation mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Separating Xylene Isomers with a Calcium Metal–Organic Framework

Here, the purification of p-xylene (pX) from its xylene isomers represents a challenging but important industrial process. Herein, we report the efficient separation of pX from its ortho- and meta- isomers by a microporous calcium-based metal–organic framework material (HIAM-203) with a flexible skeleton. At 30 °C, all three isomers are accommodated but the adsorption kinetics of o-xylene (oX) and m-xylene (mX) are substantially slower than that of pX, and at an elevated temperature of 120 °C, oX and mX are fully excluded while pX can be adsorbed. Multicomponent column breakthrough measurements and vapor-phase/liquid-phase adsorption experiments have demonstrated the capability of HIAM-203 for efficient separation of xylene isomers. Ab initio calculations have provided useful information for understanding the adsorption mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Diazo Linker Ligand Promotes Flexibility and Induced Fit Binding in a Microporous Copper Coordination Network

Abstract Flexible organic linkers represent an intuitive and effective strategy to design flexible metal–organic materials. We report herein a systematic study concerning the effect of varying the central bond of mixed pyridyl‐benzoate linkers, L, upon the flexibility of three isostructuralkddtopology microporous coordination networks (CNs) of formula ML 2 :X‐kdd‐1‐Cu,1= L = (E)‐4‐(pyridin‐4‐yldiazenyl)benzoate;X‐kdd‐2‐Cu,2= L = (E)‐4‐(2‐(pyridin‐4‐yl)vinyl)benzoate; the previously reportedX‐kdd‐3‐Cu,3= L = 4‐(pyridin‐4‐ylethynyl)benzoate. As revealed by single crystal x‐ray diffraction (SCXRD) and gas sorption studies,X‐kdd‐1‐Cu, exhibited gate‐opening during CO 2 and hydrocarbon (C2 and C8) sorption experiments whereas the other two CNs did not. Insight into these phase transformations was gained from in situ variable‐pressure and variable temperature powder X‐ray diffraction (PXRD), SCXRD, and modeling. Rotation of ligand1around the diazo bond, torsion angle changes between phenyl and carboxylate moieties, and deformation of the Cu‐based rod building blocks enabled activatedX‐kdd‐1‐Cuto form new phases with C8 isomers and CH 2 Cl 2 , CH 2 Cl 2 inducing contraction of the activated phase. Computational studies suggest that1enables flexibility thanks to its lower barrier of deformation versus2or3. This study teaches that diazo moieties could offer a general strategy to enhance the flexibility of CNs.

Chemistry↗

Optimizing the Composite Cathode Microstructure in All‐Solid‐State Batteries by Structure‐Resolved Simulations

Abstract All‐solid‐state batteries are considered as an enabler for applications requiring high energy and power density. However, they still fall short of their theoretical potential due to various limitations. One issue is poor charge transport kinetics resulting from both material inherit limitations and non‐optimized design. Therefore, a better understanding of the relevant properties of the cathode microstructure is necessary to improve cell performance. In this article, we identify optimization potentials of the composite cathode by structure‐resolved electrochemical 3D‐simulations. In our simulation study, we investigate the influence of cathode active material fraction, density, particle size, and active material properties on cell performance. Special focus is set on the impact of grain boundaries on the cathode design. Based on our simulation results, we can predict target values for cell manufacturing and reveal promising optimization strategies for an improved cathode design.

25 ENERGY STORAGE↗

Precise Pore Engineering of fcu–Type Y–MOFs for One–Step C 2 H 4 Purification from Ternary C 2 H 6 /C 2 H 4 /C 2 H 2 Mixtures

The purification of C 2 H 4 from C 2 H 6 /C 2 H 4 /C 2 H 2 mixtures is of great significance in the chemical industry for C 2 H 4 production but remains a daunting task. Guided by powerful reticular chemistry principles, herein a systematic study is carried out to engineer pore dimensions and pore functionality of fcu-type Y-based metal–organic frameworks (Y-MOFs) through the construction of a series of eight new structures using linear dicarboxylate linkers with different length and functional groups. This study illustrates how delicate changes in pore size and pore surface chemistry can effectively influence the adsorption preference of C 2 H 6 , C 2 H 4 , and C 2 H 2 by the MOFs. Importantly, clear relations between pore size/pore surface polarity and C 2 adsorption selectivities of this series of MOFs are established. In particular, HIAM-326 built on a linker decorated with trifluoromethoxy group shows notably preferential adsorption of C 2 H 6 and C 2 H 2 over C 2 H 4 , with balanced C 2 H 2 /C 2 H 4 and C 2 H 6 /C 2 H 4 selectivities. Furthermore, this endows the compound with the capability of one-step purification of C 2 H 4 from C 2 H 6 /C 2 H 4 /C 2 H 2 ternary mixtures, which is validated by breakthrough measurements where high purity C 2 H 4 (99.9%+) can be obtained directly from the separation column. Its adsorption thermodynamics and underlying selective adsorption mechanisms are further revealed by ab initio calculations.

36 MATERIALS SCIENCE↗

Effect of Entropic Constraints on the Thermodynamics of Molecular Adsorption in Nano‐Porous Materials

Abstract Gas separation is a critical industrial process that consumes a significant amount of energy due to the widely used techniques that are currently employed. Adsorptive materials—such as metal–organic frameworks (MOFs)—show promise as an energy‐efficient alternative. Of particular current interest are novel, temperature‐dependent separation processes in MOFs, such as the recently reported separation of ternary isomeric hydrocarbon mixtures within one and the same material. However, the mechanisms of these highly desirable separations remain poorly understood. Herein, through a combination of ab initio simulations and statistical mechanics, it is shown that the temperature dependence is the result of a constraint on the guest molecule's entropic degrees of freedom when loaded into the MOF, caused by the fortuitous tight fitting of the guest inside the pore. While the framework applies to all molecular adsorption in porous media, it is essential for the description of large molecules in small pores, which is demonstrated here using the separation of C6 isomers in Ca(H 2 tcpb) as a test case. The developed framework and analysis not only reveal the reason why separation occurs but also predict the temperatures at which it takes place, thus opening the door to newly designed MOFs with tailor‐made precision.

Chemistry↗

Alpha-alpha scattering in the Multiverse

We investigate the phase shifts of low-energy α-α scattering under variations of the fundamental parameters of the Standard Model, namely the light quark mass, the electromagnetic fine-structure constant as well as the QCD θ-angle. As a first step, we recalculate α-α scattering in our Universe utilizing various improvements in the adiabatic projection method, which leads to an improved, parameter-free prediction of the S- and D-wave phase shifts for laboratory energies below 10 MeV. We find that positive shifts in the pion mass have a small effect on the S-wave phase shift, whereas lowering the pion mass adds some repulsion in the two-alpha system. The effect on the D-wave phase shift turns out to be more pronounced as signaled by the D-wave resonance parameters. Variations of the fine-structure constant have almost no effect on the low-energy α-α phase shifts. We further show that up-to-and-including next-to-leading order in the chiral expansion, variations of these phase shifts with respect to the QCD θ-angle can be expressed in terms of the θ-dependent pion mass.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Predicting Fluid Flow Regime, Permeability, and Diffusivity in Mudrocks from Multiscale Pore Characterisation

In geoenergy applications, mudrocks prevent fluids to leak from temporary (H 2 , CH 4 ) or permanent (CO 2 , radioactive waste) storage/disposal sites and serve as a source and reservoir for unconventional oil and gas. Understanding transport properties integrated with dominant fluid flow mechanisms in mudrocks is essential to better predict the performance of mudrocks within these applications. In this study, small-angle neutron scattering (SANS) experiments were conducted on 71 samples from 13 different sets of mudrocks across the globe to capture the pore structure of nearly the full pore size spectrum (2 nm–5 μm). We develop fractal models to predict transport properties (permeability and diffusivity) based on the SANS-derived pore size distributions. The results indicate that transport phenomena in mudrocks are intrinsically pore size-dependent. Depending on hydrostatic pore pressures, transition flow develops in micropores, slip flow in meso- and macropores, and continuum flow in larger macropores. Fluid flow regimes progress towards larger pore sizes during reservoir depletion or smaller pore sizes during fluid storage, so when pressure is decreased or increased, respectively. Capturing the heterogeneity of mudrocks by considering fractal dimension and tortuosity fractal dimension for defined pore size ranges, fractal models integrate apparent permeability with slip flow, Darcy permeability with continuum flow, and gas diffusivity with diffusion flow in the matrix. This new model of pore size-dependent transport and integrated transport properties using fractal models yields a systematic approach that can also inform multiscale multi-physics models to better understand fluid flow and transport phenomena in mudrocks on the reservoir and basin scale.

36 MATERIALS SCIENCE↗

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗

The effect of pore structure in ethane-selective metal-organic frameworks for ethylene purification

Separation of ethylene from ethane is of great importance in petrochemical industry. Adsorptive separation making use of porous materials such as metal-organic frameworks (MOFs) is an energy efficient technology compared to the conventional cryogenic distillation. However, preferential adsorption of ethylene over ethane represents the major current challenge. Here we demonstrate how pore structure can significantly alter the adsorption selectivity in two isoreticular Zr-MOFs. A simple ligand functionalization in UiO-66 yields smaller/better matching pore for ethane, and weaker interaction with ethylene, greatly enhancing ethane/ethylene selectivity in MOF-801. Ab initio calculations combined with in situ infrared spectroscopic analysis unveil the nature of host-guest interactions and differences in the overall binding energies. Polymer-grade ethylene (99.9%) can be produced directly from ethane/ethylene mixture in a single step. Having well-balanced adsorption capacity and selectivity, low-cost synthesis and easy scalability MOF-801 stands out as a promising ethane-selective adsorbent for one-step ethylene purification under ambient conditions.

36 MATERIALS SCIENCE↗

Isostatic pressing of multilayer pouch cells and its implications for battery manufacturing

Here, we report a comprehensive investigation into the impact of isostatic pressure (ISP) processing on multilayer pouch cells. The study compares baseline electrodes fabricated using conventional manufacturing processes with isostatically pressed counterparts under varying conditions. Extensive characterization is carried out to assess the differences between baseline cells and those that underwent the isostatic pressing process. The electrochemical performance of the isostatically pressed cathodes was evaluated through impedance spectroscopy and galvanostatic charge-discharge tests. The results indicated that ISP led to notable improvements in porosity, adhesion, and rate performance compared to the baseline cathodes. This work elucidates the microstructural changes induced by ISP in lithium-ion battery cathodes and highlights the technology’s promise for advancing battery manufacturing. The findings contribute to a better understanding of how ISP can be effectively integrated into cell assembly, fostering the development of more efficient and scalable battery manufacturing techniques for current Li-ion and solid-state batteries.

25 ENERGY STORAGE↗

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗