Search NASA⌕ Search

SEARCH · Search NASA

Results for “pattern separation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tethered from the Head and from the Tail: The Structure of Hydroxyl-Functionalized Ionic Liquids

Ionic liquids with special functionalities are synthesized with the specific purpose of creating new patterns of interaction in the condensed phase. This Letter discusses the case of alcohol-functionalized ILs, the so-called HFILs, which are part of the larger cohort of task-specific ionic liquids. We find that this small chemical modification can cause massive changes in the liquid landscape when the cationic tails are longer. For prototypical ionic liquids, larger alkyl tails act as separators of charge networks, but in the case of HFILs these become physical charge network linkers. The OH functionality adds a large repertoire of interactions and correlations that were mostly unavailable to traditional ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Carrier density oscillation in the photoexcited semiconductor

Abstract The perturbation of a semiconductor from the thermodynamic equilibrium often leads to the display of non-linear dynamics and formation of spatiotemporal patterns due to the spontaneous generation of competing processes. Here, we use scanning ultrafast electron microscopy to show that the transport of hot carriers in the strongly excited semiconductor slows down by turning into an oscillatory process; this is evidenced by the expansions and contractions in the second moment of the distribution. We attribute such a response to the electric field generated by the spatial separation of photo-excited electrons and holes under intrinsic and photo-induced fields; we then introduce a transport model that mimics the experimental observation. Our finding provides a direct imaging evidence for the electrostatic oscillation of hot carriers in the highly excited semiconductor and offers new insights into their dynamics in space and time.

Physics↗
DOE OSTI2018

Centrality fluctuations in heavy-ion collisions

Volume or centrality fluctuations (CF) are one of the main uncertainties for interpreting the centrality dependence of many experimental observables. The CF is constrained by centrality selection based on particle multiplicity in a reference subevent and contributes to observables measured in another subevent. Using a Glauber-based independent source model, we study the influence of CF on several distributions of multiplicity N and eccentricities ε n : p(N), p(ε n ), p(ε n ,ε m ), and p(N,ε n ), where the effects of CF are quantified using multiparticle cumulants of these distributions. In midcentral collisions, a general relation is established between the multiplicity fluctuation and resulting CF in the reference subevent. In ultracentral collisions, where distribution of particle production sources is strongly distorted, we find these cumulants exhibit rich sign-change patterns, due to observable-dependent non-Gaussianity in the underlying distributions. The details of sign-change pattern change with the size of the collision systems. Simultaneous comparison of these different types of cumulants between model prediction and experimental data can be used to constrain the CF and particle production mechanism in heavy-ion collisions. Since the concepts of centrality and CF are expected to fluctuate in the longitudinal direction within a single event, we propose to use the pseudorapidity-separated subevent cumulant method to explore the nature of intraevent fluctuations of centrality and collective dynamics. The subevent method can be applied for any bulk observable that is sensitive to centrality and has the potential to separate different mechanisms for multiplicity and flow fluctuations happening at different timescales. As a result, the forward detector upgrades at the Relativistic Heavy Ion Collider and the Large Hadron Collider will greatly enhance such studies in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Label-free cell-substrate adhesion imaging on plasmonic nanocup arrays

Cell adhesion is a crucial biological and biomedical parameter defining cell differentiation, cell migration, cell survival, and state of disease. Because of its importance in cellular function, several tools have been developed in order to monitor cell adhesion in response to various biochemical and mechanical cues. However, there remains a need to monitor cell adhesion and cell-substrate separation with a method that allows real-time measurements on accessible equipment. In this article, we present a method to monitor cell-substrate separation at the single cell level using a plasmonic extraordinary optical transmission substrate, which has a high sensitivity to refractive index changes at the metal-dielectric interface. We show how refractive index changes can be detected using intensity peaks in color channel histograms from RGB images taken of the device surface with a brightfield microscope. Furthermore, this allows mapping of the nonuniform refractive index pattern of a single cell cultured on the plasmonic substrate and therefore high-throughput detection of cell-substrate adhesion with observations in real time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Simulation of Taylor flow evaporation for bubble-pump applications

Single-pressure absorption systems incorporate bubble-pump generators (BPGs) for refrigerant separation and passive fluid circulation. In conventional spot-heated BPGs, heat is transferred over a small area, requiring high source temperatures. Distributed-heated BPGs receive thermal input over most of the component surface, enabling low temperature operation. In this investigation, a Volume-of-Fluid phase-change simulation formulation is developed and validated. Here this approach is applied to the evaporating Taylor flow pattern in distributed-heated BPGs. A 2-D axisymmetric simulation is performed, which yields detailed information about the developing heat transfer and two-phase flow phenomena. Results are used to assess predicted trends and sub-models from a 1-D segmented BPG model. Close agreement is obtained between segmented model and simulation results for bubble rise velocity (5–7% deviation), bubble and slug lengths, void fraction (3%), and hydrodynamic pressure drop (18%). Specifying average Taylor bubble lengths from the simulation as an input to the segmented model reduces hydrodynamic pressure drop deviation to 6%. Simulated flow-evaporation heat transfer coefficients are significantly higher than those predicted using analytic models from the literature. A new flow evaporation heat transfer correlation that accounts for developing slug flow effects is proposed, and yields close agreement with simulation results for heat transfer coefficient (AAD = 11%) and overall heat transfer rate (2%). Overall, this investigation provides validation for a distributed-heated BPG modeling approach, which can enable passive refrigeration for diverse applications.

42 ENGINEERING↗
DOE OSTI2019

Spatial soft sweeps: Patterns of adaptation in populations with long-range dispersal

Adaptation in extended populations often occurs through multiple independent mutations responding in parallel to a common selection pressure. As the mutations spread concurrently through the population, they leave behind characteristic patterns of polymorphism near selected loci—so-called soft sweeps—which remain visible after adaptation is complete. These patterns are well-understood in two limits of the spreading dynamics of beneficial mutations: the panmictic case with complete absence of spatial structure, and spreading via short-ranged or diffusive dispersal events, which tessellates space into distinct compact regions each descended from a unique mutation. However, spreading behaviour in most natural populations is not exclusively panmictic or diffusive, but incorporates both short-range and long-range dispersal events. Here, we characterize the spatial patterns of soft sweeps driven by dispersal events whose jump distances are broadly distributed, using lattice-based simulations and scaling arguments. We find that mutant clones adopt a distinctive structure consisting of compact cores surrounded by fragmented “haloes” which mingle with haloes from other clones. As long-range dispersal becomes more prominent, the progression from diffusive to panmictic behaviour is marked by two transitions separating regimes with differing relative sizes of halo to core. We analyze the implications of the core-halo structure for the statistics of soft sweep detection in small genomic samples from the population, and find opposing effects of long-range dispersal on the expected diversity in global samples compared to local samples from geographic subregions of the range. We also discuss consequences of the standing genetic variation induced by the soft sweep on future adaptation and mixing.

Genetics & Heredity↗
DOE OSTI2017

Characterization and differentiation of rock varnish types from different environments by microanalytical techniques

We investigated rock varnishes collected from several locations and environments worldwide by a wide range of microanalytical techniques. These techniques were selected to address the challenges posed by the chemical and structural complexity within the micrometer- to nanometer-sized structures in these geological materials. Femtosecond laser ablation-inductively coupled plasma-mass spectrometry (fs LA-ICP-MS), scanning transmission X-ray microscopy-near edge X-ray adsorption fine structure spectroscopy (STXM-NEXAFS) in combination with scanning electron microscopy (SEM) of focused ion beam (FIB) ultra-thin (100–200 nm) sections, conventional and polarization microscopy, as well as electron paramagnetic resonance (EPR) measurements were used to obtain information about these rock varnishes. Rock varnishes from different environments, which cannot readily be distinguished based on their macroscopic appearance, differ significantly in their constituent elemental mass fractions, e.g., of Mn, Fe, Ni, Co, Ba, and Pb, and their rare earth element (REE) patterns. Structural characteristics such as the particle sizes of embedded dust grains, internal structures such as layers of Mn-, Fe-, and Ca -rich material, and structures such as cavities varied between varnishes from different environments and regions in the world. The EPR spectra were consistent with aged biogenic Mn oxides in all samples, but showed subtle differences between samples of different origin. Our observations allow us to separate rock varnishes into different types, with differences that might be indicators of distinct geneses. Five different types of rock varnish could be distinguished, Type I–V, of which only Type I might be used as potential paleoclimate archive. Each varnish type has specific characteristics in terms of their elemental composition, element distribution, and structures. The combination of element ratios (Mn/Ba, Al/Ni, Mn/REY, Mn/Ce, Mn/Pb, La N /Yb N , and Ce/Ce*), total REE contents, and structures can be used to separate the different types of rock varnish from each other.

58 GEOSCIENCES↗
DOE OSTI2021

Selecting XFEL single-particle snapshots by geometric machine learning

A promising new route for structural biology is single-particle imaging with an X-ray Free-Electron Laser (XFEL). This method has the advantage that the samples do not require crystallization and can be examined at room temperature. However, high-resolution structures can only be obtained from a sufficiently large number of diffraction patterns of individual molecules, so-called single particles. Here, we present a method that allows for efficient identification of single particles in very large XFEL datasets, operates at low signal levels, and is tolerant to background. This method uses supervised Geometric Machine Learning (GML) to extract low-dimensional feature vectors from a training dataset, fuse test datasets into the feature space of training datasets, and separate the data into binary distributions of “single particles” and “non-single particles.” As a proof of principle, we tested simulated and experimental datasets of the Coliphage PR772 virus. We created a training dataset and classified three types of test datasets: First, a noise-free simulated test dataset, which gave near perfect separation. Second, simulated test datasets that were modified to reflect different levels of photon counts and background noise. These modified datasets were used to quantify the predictive limits of our approach. Third, an experimental dataset collected at the Stanford Linear Accelerator Center. The single-particle identification for this experimental dataset was compared with previously published results and it was found that GML covers a wide photon-count range, outperforming other single-particle identification methods. Moreover, a major advantage of GML is its ability to retrieve single particles in the presence of structural variability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Artifact identification in X-ray diffraction data using machine learning methods

In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Semiconductor-compatible topological digital alloys

Recently, GeSn alloys have attracted much interest for direct-gap infrared photonics and as potential topological materials which are compatible with the semiconductor industry. However, for photonics, the high-Sn content required leads to low detectivity, associated with poor material quality, and the (>35 %) Sn required for topological properties have been out of reach experimentally. Here, we demonstrate that by patterning the Sn distribution within Ge, the electronic properties have a far greater tunability than is possible with the random alloy. For the GeSn δ-digital alloy (DA) formed by confining Sn atoms in atomic layer(s) along the [111] direction of Ge, we show that ∼ 10 % Sn can lead to a triple-point semimetal. These findings are understood in terms of Sn ordering causing spatial separation of Sn and Ge band edges, leading to band inversion. This mechanism can also lead to a weak topological insulator, Weyl semimetal, and enables tunable direct bandgaps down to 2 meV, covering the entire infrared range. This DA induced topological properties are also identified in compound semiconductors, such as InAs 1-x Sb x , showing the general applicability of the DA design for realizing topological properties on conventional semiconductor platforms. Furthermore, our findings not only point to a new class of currently unexplored topological systems accessible by epitaxy, but also establish the promise of low-Sn GeSn DAs for application as infrared laser diodes and photodetectors in Si photonic integrated circuits and infrared image sensors.

3D topological semimetal↗
DOE OSTI2021

Boost of the Bio-memristor Performance for Artificial Electronic Synapses by Surface Reconstruction

Biomaterial-based memristors (bio-memristors) are often adopted to emulate biological synapse functions and applied to construct neural computing networks in brain-inspired chip systems. However, the randomness of conductive filament formation in bio-memristors inhibits their switching performance by causing the dispersion of the device-switching parameters. In this case, a facile porous silk fibroin (p-SF) memristor was obtained through a protein surface reconstruction strategy, in which the size of the hole can be adjusted by the density of hybrid nanoseeds. Here, the porous SF memristors exhibit greatly enhanced electrical characteristics, including uniform I-V cycles, centralized distribution of the switching voltages, and both high and low resistances, compared to devices without pores. The results of three-dimensional (3D) simulations based on classical density functional theory (cDFT) suggest that the reconstructed pores in the SF layers guide the formation and fracture of Ag filaments under an electric field and enhance the overall conductivity by separating Ag + ion and electron diffusion pathways. Ag + ions are predicted to preferentially diffuse through pores, whereas electrons diffuse through the SF network. Interestingly, the device conductance can be bidirectionally modulated gradually by positive and negative voltages, can faithfully simulate short-term and long-term plasticity, and can even realize the triplet-spike-timing-dependent plasticity (triplet-STDP) rule, which can be used for pattern recognition in biological systems. The simulation results reveal that a memristor network of this type has an accuracy of ~95.78% in memory learning and the capability of pattern learning. This work provides a facile technology route to improve the performance of bionic-material memristors.

36 MATERIALS SCIENCE↗
DOE OSTI2016

WE-FG-207B-09: Experimental Assessment of Noise and Spatial Resolution in Virtual Non-Contrast Dual-Energy CT Images Across Multiple Patient Sizes and CT Systems

Purpose: To investigate the noise and spatial resolution properties of virtual non-contrast (VNC) dual-energy CT images compared to true non-contrast (TNC) images across multiple patient sizes and CT systems. Methods: Torso-shaped water phantoms with lateral widths of 25, 30, 35, 40 and 45 cm and a high resolution bar pattern phantom (Catphan CTP528) were scanned using 2nd and 3rd generation dual-source CT systems (Scanner A: Somatom Definition Flash, Scanner B: Somatom Force, Siemens Healthcare) in dual-energy scan mode with the same radiation dose for a given phantom size. Tube potentials of 80/Sn140 and 100/Sn140 on Scanner A and 80/Sn150, 90/Sn150 and 100/Sn150 on Scanner B were evaluated to examine the impact of spectral separation. Images were reconstructed using a medium sharp quantitative kernel (Qr40), 1.0-mm thickness, 1.0-mm interval and 20 cm field of view. Mixed images served as TNC images. VNC images were created using commercial software (Virtual Unenhanced, Syngo VIA Version VA30, Siemens Healthcare). The noise power spectrum (NPS), area under the NPS, peak frequency of the NPS and image noise were measured for every phantom size and tube potential combination in TNC and VNC images. Results were compared within and between CT systems. Results: Minimal shift in NPS peak frequencies was observed in VNC images compared to TNC for NPS having pronounced peaks. Image noise and area under the NPS were higher in VNC images compared to TNC images across all tube potentials and for scanner A compared to scanner B. Limiting spatial resolution was deemed to be identical between VNC and TNC images. Conclusion: Quantitative assessment of image quality in VNC images demonstrated higher noise but equivalent spatial resolution compared to TNC images. Decreased noise was observed in the 3rd generation dual-source CT system for tube potential pairs having greater spectral separation. Dr. McCollough receives research support from Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Dispersion of high oxygen permeability ionomers in water-propanol solutions

There is a growing interest in high oxygen permeability ionomers (HOPI) for better-performing proton exchange membrane fuel cell (PEMFC) catalyst layers. In this study, we used small-angle x-ray scattering (SAXS) to analyze dispersions of two types of perfluorinated sulfonic acid (PFSA) ionomers and a HOPI in water and propanol solvents, at concentrations between 1 wt% and 15 wt%. HOPI dispersions exhibited the interference peak typical of ionomers; by separately fitting the peak and higher- q regions with several models, we demonstrated that HOPI aggregates have a closer average spacing than conventional PFSA ionomers, and smaller aggregate size when assuming a cylindrical geometry. By measuring conventional PFSA ionomers with two side chain lengths and several equivalent weights, we showed that these side chain parameters alone did not explain the differences in aggregate spacing or size. In addition, the pattern was present whether samples were prepared in a 50/50 water/propanol or a more propanol-rich mixture. As such, the structural differences of HOPI could be due to its different backbone monomer. A better understanding of the influence of the HOPI chemistry on dispersion properties could help explain the ink structure and drying characteristics of HOPI observed in prior work. Future study of ionomer-catalyst mixtures, such as measuring ionomer adsorption to carbon, would help elucidate the role of ionomer from ink formulation to the cast electrode.

Aquivion↗
DOE OSTI2026

Ecological and genomic variation in ectomycorrhizal fungal exploration types

Ectomycorrhizal fungi (EMF) produce mycelia with variable extension and complexity, which can be classified according to soil ‘exploration types’ (ETs). ETs have received attention as one of the few mycorrhizal trait frameworks, but without an empirical classification of ET functional diversity and environmental preferences, understanding and interpreting EMF biogeographic patterns has been difficult. We conducted a synthesis combining: comparative EMF genomics to describe functional divergence in decomposition and nutrient cycling genes across ETs; and EMF trait distribution modeling across continental Europe, pairing soil and root EMF surveys to establish biogeographic ET niche profiles. We demonstrate a signature of ETs encoded in EMF genomes, which is independent from phylogeny and linked to biomass production strategies. EMF ET relative abundances were separated by soil, root, and dominant tree leaf type habitats and exhibited unique correlations with forest biotic (e.g. plant productivity and plant pathogen densities) and abiotic (e.g. nitrogen deposition and soil pH) conditions. These findings support a theory that EMF niche partitioning can be partially explained by extraradical mycelial traits, with underlying variation in ET biogeography likely arising from distinct decomposition and nutrient cycling potentials. We also identify important limitations to this trait framework and provide a guided outlook for future research.

biogeography↗
DOE OSTI2016

Localized reactive flow in carbonate rocks: Core-flood experiments and network simulations

We conducted four core-flood experiments on samples of a micritic, reef limestone from Abu Dhabi under conditions of constant flow rate. The pore fluid was water in equilibrium with CO 2 , which, because of its lowered pH, is chemically reactive with the limestone. Flow rates were between 0.03 and 0.1 mL/min. The difference between up and downstream pore pressures dropped to final values <<1 MPa over periods of 3–18 h. Scanning electron microscope and microtomography imaging of the starting material showed that the limestone is mostly calcite and lacks connected macroporosity and that the prevailing pores are few microns large. During each experiment, a wormhole formed by localized dissolution, an observation consistent with the decreases in pressure head between the up and downstream reservoirs. Moreover, we numerically modeled the changes in permeability during the experiments. We devised a network approach that separated the pore space into competing subnetworks of pipes. Thus, the problem was framed as a competition of flow of the reactive fluid among the adversary subnetworks. The precondition for localization within certain time is that the leading subnetwork rapidly becomes more transmissible than its competitors. This novel model successfully simulated features of the shape of the wormhole as it grew from few to about 100 µm, matched the pressure history patterns, and yielded the correct order of magnitude of the breakthrough time. Finally, we systematically studied the impact of changing the statistical parameters of the subnetworks. Larger mean radius and spatial correlation of the leading subnetwork led to faster localization.

58 GEOSCIENCES↗
DOE OSTI2017

Centrifugal‐driven, reduced‐dimension, planar chromatography

Abstract A fundamental problem with efficiency in capillary action driven planar chromatography results from diminishing flow rates as development proceeds, giving rise to molecular diffusion related band dispersion for most sample types. Overpressure and electrokinetic means to speed flow have been used successfully in TLC. We explore the use of centrifugal force (CF) to drive flow for reduced‐dimension planar platforms (ultra‐TLC, low micrometer features, and nano‐TLC, nanoscale features). The silicon wafer platforms have two forms of continuous 2D arrays created by either photolithography or metal dewetting followed by deep reactive ion etching and coated with porous SiO 2 . The flow pattern is unusual with co‐planar flows above and within the arrays. The effects of parameters such as spin rate, solvent type, and surface character on flow rates is established and can be substantially greater than capillary action flow. Using fluorescent dyes, we investigate retardation factors and chromatographic plate height; the latter falls in the low to sub‐micrometer range. To the best of our knowledge, we demonstrate the first analytical separations performed in pillar arrays using CF to augment solvent flow.

Strickhouser, Rachel B.↗
DOE OSTI2026

Constraining the Aerosol Effects on Deep Convective Clouds by Considering the Coupling Between Clouds and the Planetary Boundary Layer

Several mechanisms have been proposed for the aerosol invigoration effect. Although their principles are well established, their actual magnitudes and roles in cloud development remain uncertain and debatable. This uncertainty partly stems from observational-based studies, in which it has been challenging to separate the co-variability between aerosols and meteorology. Addressing this problem requires large data samples. To this end, this study employs the Atmospheric Radiation Measurement data set expanding to 16 years (some up to 17 years, compared to 10 years in previous work) in the U.S. Southern Great Plains. It also conducts a more careful and rigorous analysis to isolate the influences of convective available potential energy (CAPE) and synoptic patterns to address a previously raised concern. We incorporated a new key process affecting aerosol-cloud interaction: cloud-surface coupling. The state/degree of the coupling relationship turns out to play an important role in the invigoration effect. Our analysis reinforces earlier findings of a robust positive relationship between cloud thickness and aerosol loading across CAPE percentiles—but only under cloud-surface coupled conditions. The increase in cloud thickness with aerosol loading is most pronounced in coupled clouds with high CAPE and bases below 1 km. Coupled clouds with bases below 1 km thicken between 1 and 4 km, depending on the CAPE percentile. Decoupled clouds show no such systematic changes. Synoptic patterns also lead to different strengths of the invigoration effect. Clean and polluted air masses are predominantly associated with northerly and southerly winds, respectively, with a stronger invigoration effect in cleaner air masses.

Geosciences↗
DOE OSTI2022

Metal-hydrogen-pi-bonded organic frameworks

We report the synthesis and characterization of a new series of permanently porous, three-dimensional metal–organic frameworks (MOFs), M-HAF-2 (M = Fe, Ga, or In), constructed from tetratopic, hydroxamate-based, chelating linkers. Here, the structure of M-HAF-2 was determined by three-dimensional electron diffraction (3D ED), revealing a unique interpenetrated hcb-a net topology. This unusual topology is enabled by the presence of free hydroxamic acid groups, which lead to the formation of a diverse network of cooperative interactions comprising metal–hydroxamate coordination interactions at single metal nodes, staggered π–π interactions between linkers, and H-bonding interactions between metal-coordinated and free hydroxamate groups. Such extensive, multimodal interconnectivity is reminiscent of the complex, noncovalent interaction networks of proteins and endows M-HAF-2 frameworks with high thermal and chemical stability and allows them to readily undergo postsynthetic metal ion exchange (PSE) between trivalent metal ions. We demonstrate that M-HAF-2 can serve as versatile porous materials for ionic separations, aided by one-dimensional channels lined by continuously π-stacked aromatic groups and H-bonding hydroxamate functionalities. As an addition to the small group of hydroxamic acid-based MOFs, M-HAF-2 represents a structural merger between MOFs and hydrogen-bonded organic frameworks (HOFs) and illustrates the utility of non-canonical metal-coordinating functionalities in the discovery of new bonding and topological patterns in reticular materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗