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At least 37 records · Page 2

K 3 Ir 2 O 6 and K 16.3 Ir 8 O 30 , Low-Dimensional Iridates with Infinite IrO 6 Chains

A previously unreported 1D iridate, K 3 Ir 2 O 6 , has been grown by a flux method in O 2 -rich environment and its crystal structure determined via single crystal structural analysis. It exhibits straight chains of face-sharing [IrO 6 ] octahedra, which are arranged along the crystallographic c axis, separated by nonmagnetic K ions. No magnetic transitions are observed during measured range, and the material is electrically insulating. Potentially interesting electronic behavior for K 3 Ir 2 O 6 is supported by electronic structure calculations. A structurally related material, K 16.3 Ir 8 O 30 , which displays similar fundamental geometric units but in a different spatial arrangement – zigzag chains based on edge and face sharing [IrO 6 ] octahedra, is also reported. Both materials are of interest for probing the properties of a 1D system with strong spin-orbit coupling

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Hierarchical Composites Patterned via 3D Printed Cellular Fluidics

Additive manufacturing of freeform structures containing multiple materials with deterministic spatial arrangement and interactions remains a challenge for most 3D printing processes, due to complex fabrication tool requirements and limitations in printability of some material classes. Here, in this paper, a versatile method is reported to produce architected composites using the concept of cellular fluidics, in which lattices of unit cells are used as templating scaffolds to guide flowable infill materials in a programmed spatial pattern, upon which they are cured in place to produce a deterministically ordered multimaterial solid. The lattice design relies on the unit cell size, type, strut diameter, surface wetting, and distribution of cellular structures to control liquid flow and retention. Individual unit cells are tuned to achieve reliable infilling and combined into higher-order architectures to achieve multiscale composite materials with disparate mechanical properties, including those considered non-printable. Lattice design considerations for leveraging capillary phenomena and demonstrate several methods of patterning polymers in 3D-printed cellular fluidic structures are presented. The concept of tuning the compressive response of an architected composite using a flexible-elastomer as the lattice and a stiff-epoxy as the infill material is illustrated.

36 MATERIALS SCIENCE↗

Evaluation of preservation protocols for oxygen-sensitive minerals within laminated aquatic sediments

Laminated sediments can record seasonal changes in sedimentation of material from anoxic waters, including minerals of the redox-sensitive elements Fe, Mn, and S that form under varying oxygen levels, mineral saturation conditions, and from microbial metabolism. However, preserving the oxygen-sensitive minerals for identification is challenging when preservation of the spatial arrangement of laminae is also required. In this study, we compare methods for embedding sedimentary materials from anoxic waters and sediments from Brownie Lake, Minnesota, USA for analysis of the speciation for Fe, Mn, and S using synchrotron-based X-ray absorption near edge spectroscopy (XANES). We found that acetone dehydration and resin replacement in a 100% N 2 glovebox successfully preserved the speciation of Fe and Mn minerals within laminated sediments. However, acetone removed some sulfur species from sediments, and epoxies contained sulfur species, which challenged identification of native sulfur species. Results from this study will aid researchers who are interested in spatial analysis of oxygen sensitive sediments, soils, or microbial mats in choosing a preservation method.

58 GEOSCIENCES↗

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗

Multiscale spatial analysis of fracture arrangement and pattern reconstruction using Ripley's K-function

This work presents novel multiscale spatial data analytics using Ripley's K-function, as a measure of spatial interaction, to study one-dimensional arrangement of fractures. Fracture spatial arrangements are classified into clustered, anticlustered, or indistinguishable from random by testing statistical significance of the calculated Ripley's K-function. Characterizations of fracture arrangements are performed as a function of length scale and position. Analysis of the K-function along the study interval identifies where fracture clustering and anticlustering occur. Here, a simulation technique is also introduced here to statistically reconstruct spatial arrangements and to generate fracture realizations that are spatially similar to the fractures observed in the field. With this simulation technique, one can also fill spatial gaps in fracture measurements where data are absent, unreliable, or unused. Synthetic as well as field-measured 1D fracture datasets are used for testing and demonstration. Methods introduced in this work can be readily applied to fracture datasets observed in outcrops, borehole image logs, and cores.

58 GEOSCIENCES↗

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗

Anomalous Spin‐Optical Helical Effect in Ti‐Based Kagome Metal

The kagome lattice stands as a rich platform for hosting a wide array of correlated quantum phenomena, ranging from charge density waves and superconductivity to electron nematicity and loop current states. Direct detection of loop currents in kagome systems has remained a formidable challenge due to their intricate spatial arrangements and the weak magnetic field signatures they produce, and this has made their identification experimentally subtle. This has left their existence and underlying mechanisms a topic of intense debate. In this work, we uncover signatures compatible with loop currents: spin handedness-selective signals that surpass conventional dichroic, spin, and spin-dichroic responses. We observe this phenomenon in the kagome metal CsTi 3 ⁢Bi 5 and we call it the anomalous spin-optical helical effect. This effect arises from the coupling of light's helicity with spin-orbital electron correlations, thereby providing an indirect yet sensitive approach to probe loop-current–related electronic correlations in quantum materials. Our discovery not only enriches the debate surrounding loop currents but also offers new experimental strategies to exploit the electronic phases of quantum materials via light–matter interaction.

anomalous spin-optical helical effect↗

Oblique Packing and Tunable Excitonic Coupling in DNA‐Templated Squaraine Rotaxane Dimer Aggregates

Abstract When molecules are aggregated such that their excited states form delocalized excitons, their spatial arrangement, or packing, can be coarsely controlled by templating and finely controlled by chemical substitution; however, challenges remain in controlling their packing on intermediate length scales. Here, we use an approach based on mechanically interlocked molecules to promote an elusive oblique packing arrangement in a series of three squaraine rotaxane dimers. We template the squaraine rotaxane dimers using DNA and observe two excitonically split bands of near‐equal intensity in their absorption spectra – a distinct signature of oblique packing, validated by theoretical modeling of the experimental results. Additional fine control of packing is demonstrated by fluorinating the macrocycle of the rotaxane, which promotes denser packing and stronger excitonic interactions.

36 MATERIALS SCIENCE↗

Molecular basis for higher affinity of SARS-CoV-2 spike RBD for human ACE2 receptor

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused substantially more infections, deaths, and economic disruptions than the 2002-2003 SARSCoV. The key to understanding SARS-CoV-2's higher infectivity lies partly in its host receptor recognition mechanism. Experiments show that the human angiotensin converting enzyme 2 (ACE2) protein, which serves as the primary receptor for both CoVs, binds to the receptor binding domain (RBD) of CoV-2's spike protein stronger than SARS-CoV's spike RBD. The molecular basis for this difference in binding affinity, however, remains unexplained from X-ray structures. To go beyond insights gained from X-ray structures and investigate the role of thermal fluctuations in structure, we employ all-atom molecular dynamics simulations. Microseconds-long simulations reveal that while CoV and CoV-2 spike-ACE2 interfaces have similar conformational binding modes, CoV-2 spike interacts with ACE2 via a larger combinatorics of polar contacts, and on average, makes 45% more polar contacts. Correlation analysis and thermodynamic calculations indicate that these differences in the density and dynamics of polar contacts arise from differences in spatial arrangements of interfacial residues, and dynamical coupling between interfacial and non-interfacial residues. Furthermore, these results recommend that ongoing efforts to design spike-ACE2 peptide blockers will benefit from incorporating dynamical information as well as allosteric coupling effects.

59 BASIC BIOLOGICAL SCIENCES↗

Computationally Efficient Multiscale Neural Networks Applied to Fluid Flow in Complex 3D Porous Media

Abstract The permeability of complex porous materials is of interest to many engineering disciplines. This quantity can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as the simulation domains become less porous or more heterogeneous. Semi-analytical models that rely on averaged structural properties (i.e., porosity and tortuosity) have been proposed, but these features only partly summarize the domain, resulting in limited applicability. On the other hand, data-driven machine learning approaches have shown great promise for building more general models by virtue of accounting for the spatial arrangement of the domains’ solid boundaries. However, prior approaches building on the convolutional neural network (ConvNet) literature concerning 2D image recognition problems do not scale well to the large 3D domains required to obtain a representative elementary volume (REV). As such, most prior work focused on homogeneous samples, where a small REV entails that the global nature of fluid flow could be mostly neglected, and accordingly, the memory bottleneck of addressing 3D domains with ConvNets was side-stepped. Therefore, important geometries such as fractures and vuggy domains could not be modeled properly. In this work, we address this limitation with a general multiscale deep learning model that is able to learn from porous media simulation data. By using a coupled set of neural networks that view the domain on different scales, we enable the evaluation of large ( $$>512^3$$ > 512 3 ) images in approximately one second on a single graphics processing unit. This model architecture opens up the possibility of modeling domain sizes that would not be feasible using traditional direct simulation tools on a desktop computer. We validate our method with a laminar fluid flow case using vuggy samples and fractures. As a result of viewing the entire domain at once, our model is able to perform accurate prediction on domains exhibiting a large degree of heterogeneity. We expect the methodology to be applicable to many other transport problems where complex geometries play a central role.

36 MATERIALS SCIENCE↗

High compressive energy absorption and shape recovery behavior of additively manufactured textile-inspired cylindrical braided metamaterials

Mechanical metamaterials (MMs) are engineered structures with unique mechanical properties that arise from their unique spatial arrangement or lattice-like structure. The most commonly designed MMs such as honeycomb and re-entrant auxetics are prone to failure at the sharp corners and weak joints due to the increased stress concentration under deformation. To mitigate this challenge, braided MM structures involving intertwining threads of nylon—forming curved unit cells—have been studied. These textile-inspired cylindrical braided metamaterials (CBMMs) with contrasting unit cells, namely diamond and regular CBMMs, were fabricated by 3D printing. The layer-by-layer deposited structure built by fused filament fabrication delivered an assembly of overlapped threads that are fused at the contact point. To understand deformation behavior of these MMs, finite element models were developed for various load scenarios including quasi-static compression, cyclic and creep loads at room temperature. Stress distribution, deformation mechanisms, and failure modes were analyzed and validated by experiments to analyze the geometries and associated performance. The diamond CBMMs showed stress softening at 30 % compressive strain, withstanding a load of ∼440 N, whereas the regular CBMMs at 50 % strain experienced ∼250 N. The diamond CBMMs delivered higher creep resistance under sustained load and better energy absorption under cyclic loading than the regular CBMMs. The latter, however, exhibited 94 % shape recovery in contrast to 88 % recovery in former prototype during their first cyclic load. In conclusion, this study helps design mechanical lightweight devices that endure significant sustained load and exhibit enhanced energy absorption and shape recovery characteristics in cyclic loading.

Creep↗

Single molecule insights into interfacial molecular recognition for model electrochemical DNA biosensors

Electrochemical sensors that use surface-immobilized DNA to bind analytes and transduce the binding into electrochemical signals, have the potential for rapid, specific, and sensitive detection of bioanalytes via a compact and portable platform. However, accessing the structure of these surfaces/interfaces at the relevant spatial scale (< 10 nm), which determines the interfacial interactions and ultimately sensing performance, remains an unsolved challenge. Here, we review studies that have used high resolution atomic force microscope imaging and spatial statistical analysis tools to understand crowding interactions between thiolated DNA probes immobilized on gold electrodes and how such interactions impact target binding. We also review related studies that attempt to control the nanoscale spatial arrangement of the immobilized recognition elements to optimize sensing performance. Furthermore, these efforts have led to new advances in understanding of the structure-function relationships of DNA-based electrochemical biosensors to move the field toward rational engineering of these biosensing interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In Situ 29 Si solid-state NMR study of grafting of organoalkoxysilanes to mesoporous silica nanoparticles

We report that since the catalytic activity and the stability of silica-bound organometallic complexes are affected by their interactions with hydroxyl groups on the surface, isolated hydroxyls are often created prior to the introduction of catalytic species. Here, we investigate a method to remove the indigenous hydroxyls and create new isolated hydroxyls by grafting organo-trimethoxysilane (R-TMS) to generate a silicon T 2 site, (≡SiO-) 2 SiR(-OH). We used in situ 29 Si solid-state NMR experiments to monitor the evolution of T n sites, (≡SiO - ) n SiR(-OH) 3-n (n = 1, 2, 3). The study indicates that i) the grafting proceeds in a consecutive manner as T 1 → T 2 → T 3 , and ii) the kinetics depend on the type of functional groups in the silane. However, the rates of T 1 formation and T 2 → T 3 conversion are also controlled to a significant extent by the entropy loss associated to the initial silane binding and the spatial arrangement of surface hydroxyls, respectively. The grafting of R-TMS with a basic functional group leads to a lower concentration of T 1 sites. The nucleophilicity of the functional group facilitates the grafting process by lowering the enthalpy barrier, while the T 1 formation rate is more influenced by the entropy barrier than the T 1 → T 2 conversion rate. Thus, the basic functional group promotes the T 1 → T 2 conversion more than the T 1 formation, resulting in a lower concentration of T 1 sites.

36 MATERIALS SCIENCE↗

Digital polycrystalline microstructure generation using diffusion probabilistic models

Accurate micromechanical simulation of polycrystalline materials requires a realistic digital representation of the grain scale microstructure. Here, this work demonstrates the use of a generative diffusion probabilistic model for synthesizing single phase polycrystalline realizations. The model performs well and is capable of producing realistic microstructures consisting of not just simple equiaxed structures but also structures exhibiting more complex spatial arrangements. Masked microstructure generation reveals that the model is context aware of morphological descriptors which may be encoded in the latent space. Training on more diverse data sets, with scaled up architectures, may enable development of future models capable of synthesizing even more complex microstructural features.

36 MATERIALS SCIENCE↗

Processing-dependent chemical ordering in Cu 3 Au characterized via non-destructive Bragg coherent diffraction imaging

Of current importance for alloy design is controlling chemical ordering through processing routes to optimize an alloy's mechanical properties for a desired application. However, characterization of chemical ordering remains an ongoing challenge, particularly when nondestructive characterization is needed. Here, in this study, Bragg coherent diffraction imaging is used to reconstruct morphology and lattice displacement in model Cu 3 Au nanocrystals that have undergone different heat treatments to produce variation in chemical ordering. The magnitudes and distributions of the scattering amplitudes (proportional to electron density) and lattice strains within these crystals are then analyzed to correlate them to the expected amount of chemical ordering present. Nanocrystals with increased amounts of ordering are found to generally have less extreme strains present and reduced strain distribution widths. In addition, statistical correlations are found between the spatial arrangement of scattering amplitude and lattice strains.

Warren, Nathaniel [Pennsylvania State Univ., Unive↗

A new measurement of amine steric hindrance – N exposure

Here, a new measurement of steric hindrance effect of amines, N exposure, is proposed. N exposure outperforms traditional parameters as it is independent of group-specific parame-ters and accounts for the spatial arrangements of pendant groups. Such a measurement can facilitate the screening of sterically hindered amines for carbon capture with improved CO 2 loading capacities. Along with this study, a script is provided to quantify the N exposure for other amine molecules of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Roles of Alkali Metals and Ionic Networks in Directing the Formation of Anionic Metal–Organic Frameworks

Integrating different types of fundamental chemical interactions to direct the self-assembly processes and to control the dimension of the network formed by each type of interactions is a promising strategy to develop advanced functional materials. Here, the ionic interaction of alkali metals (Na, K, Cs) towards multi-functional 2,2’-disulfo-4,4’-oxydibenzoic acid is utilized in two solvent systems, aqueous-amide and uro-amide, to synthesize six novel anionic framework materials with dramatically different features and dimensionalities: (Na 3 [Zn 4 O(L 4- ) 3 (e-murea)(H 2 O) 3 ](H 2 N(CH 3 ) 2 +) 3 (CPM-s1), [Zn 4 O(L 4- ) 3 (DMF)]((NH 2 (CH 3 ) 2 +) 6 ) (CPM-s2), Na 6 [(Zn 2 OH 2 ) 3 (L 3- ) 6 ](H 2 O) 3 (CPM-s3), K 3 [Zn 2 (L 4- ) 2 ](H 2 N(CH 3 ) 2 +)(e-murea) 2 (H 2 O) 3 (CPM-s4), K 4 [Zn(L 3- ) 2 ](H 2 O) 2 (CPM-s5), and Cs 6 [Zn(L 4- ) 2 ](H 2 O) 2 (CPM-s6), L 4- = 2,2’-disulfo-4,4’-oxydibenzoate, DMF = N,N-dimethylformamide, e-murea = 1,3-dimethyl-1-2-imidazolidinone). In CPM-s1 to CPM-s6, the alkali-sulfonate ionic bonding networks transformed from 0D clusters with Na + to 1D chains and 2D sheets with K + , and 3D network with Cs + . These vastly differing ionic domains influenced the coordination modes and spatial arrangements of the metal-carboxylate linkers, which consequently, directed the dimensionality of the coordination networks from 3D with Na + to 1D with Cs + . CPM-s1 and CPM-s2, made from tetrameric Zn 4 O clusters are rare examples of anionic MOF-5-type structures. CPM-s3 features an unprecedented hexameric Zn 6 cluster. Even though a large portion of the charge-balancing cations in these materials would hamper hydrogen bonding networks, some of them still exhibit very high ionic conductivity (e.g. 1.25 x 10 -3 S cm -1 in CPM-s3), suggesting the potential of these materials as solid-state electrolytes.

36 MATERIALS SCIENCE↗