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At least 91 records · Page 5

An Ultra-microporous Metal-Organic Framework with Exceptional Xe Capacity

Molecular confinement plays a significant effect on trapped gas and solvent molecules. A fundamental understanding of gas adsorption within the porous confinement provides information necessary to design a material with improved selectivity. In this regard, metal organic frameworks (MOFs) adsorbents are ideal candidate materials to study confinement effects for weakly interacting gas molecules such as noble gases. Among the noble gases, Xenon (Xe) has practical applications in the medical, automotive and aerospace industries. In this communication, we report an ultra-microporous nickel-isonicotinate MOF with exceptional Xe uptake and selectivity compared to all benchmark MOF and porous organic cage materials. The selectivity arises because of the near perfect fit of the atomic Xe inside the porous confinement. Notably, at low partial pressure, the Ni-MOF interacts very strongly with Xe compared to the closely related Krypton gas (Kr) and more polarizable CO2. Further 129Xe NMR suggests a broad isotropic chemical shift due to the reduced motion as a result of confinement.

Confinement effects, atomically precise materials,↗

Ambient-Temperature Hydrogen Storage via Vanadium(II)-Dihydrogen Complexation in a Metal-Organic Framework

In this report, the widespread implementation of H 2 as a fuel is currently hindered by the high pressures or cryogenic temperatures required to achieve reasonable storage densities. In contrast, the realization of materials that strongly and reversibly adsorb hydrogen at ambient temperatures and moderate pressures could transform the transportation sector and expand adoption of fuel cells in other applications. To date, however, no adsorbent has been identified that exhibits a binding enthalpy within the optimal range of -15 to -25 kJ/mol for ambient-temperature hydrogen storage. Here, we report the hydrogen adsorption properties of the metal-organic framework (MOF) V 2 Cl 2.8 (btdd) (H 2 btdd, bis(1 H -1,2,3-triazolo[4,5- b ],[4',5'- i ])dibenzo[1,4]dioxin), which features exposed vanadium(II) sites capable of backbonding with weak π acids. Significantly, gas adsorption data reveal that this material binds H 2 with an enthalpy of -21 kJ/mol. This binding energy enables usable hydrogen capacities that exceed that of compressed storage under the same operating conditions. The Kubas-type vanadium(II)-dihydrogen complexation is characterized by a combination of techniques. From powder neutron diffraction data, a V-D 2 (centroid) distance of 1.966(8) Å is obtained, the shortest yet reported for a MOF. Using in situ infrared spectroscopy, the H-H stretch was identified, and it displays a red shift of 242 cm -1 . Electronic structure calculations show that a main contribution to bonding stems from the interaction between the vanadium d π and H 2 σ* orbital. Ultimately, the pursuit of MOFs containing high densities of weakly π-basic metal sites may enable storage capacities under ambient conditions that far surpass those accessible with compressed gas storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorption Studies of Dilute Krypton and Xenon from Nitrogen on SBMOF-1 and Activated Charcoal for Applications in Isotope Harvesting

Adsorptive partitioning of dilute krypton (Kr) and xenon (Xe) onto Stony Brook Metal–Organic Framework (SBMOF-1) and activated charcoal (AC) from carrier nitrogen was experimentally measured at temperatures ranging from 195 to 293 K. For this purpose, a closed-loop system for gas adsorption experiments was developed. From the Kr adsorption measurements, the adsorption equilibrium constant for Kr on SBMOF-1 was calculated, yielding a value for the enthalpy of adsorption of −19 ± 1 kJ·mol –1 . The partition coefficients were utilized to estimate the extraction rates of 76 Kr, 77 Kr, and 122 Xe isotopes during isotope harvesting at the Facility for Rare Isotope Beams (FRIB). We conclude that both materials showed promising results for the extraction of noble gases from FRIB effluents using temperature swing adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Review of the potential and challenges of MOF-based adsorption heat pumps for sustainable cooling and heating in the buildings

Heat pumps are regarded as the most suitable means to meet the future demand of heating and cooling in the building, as they require small input of electrical energy and output high thermal energy. Vapor compression heat pump (VCHP) and transcritical-CO 2 heat pump are the two major heat pump technologies currently dominating the market. However, VCHP system suffers from its fugitive emission of hydrofluorocarbon (HFC) refrigerants, and transcritical-CO 2 system requires high operating pressure (typically 9–13 MPa). For low-to-medium temperature heating and cooling applications thermally driven adsorption heat pump (AHP) provides a better alternative to VCHP and transcritical-CO 2 system as AHP uses natural refrigerants and operates at a much lower pressure. But currently available AHP technology has the limitation of low coefficient of performance (COP). Advances in synthesizing metal-organic frameworks (MOF) with high gas adsorption capacity have created an opportunity to address the problem of low COP of current AHP technology. Here, this article reviews the progress made in the past decade in utilizing MOF and conventional adsorbents with different working fluids in AHP technology and compares their performance. The article also summarizes the key challenges for the MOF-based AHP technology and provides the authors’ perspective to address these challenges.

30 DIRECT ENERGY CONVERSION↗

Synthesis of Ionic Ultramicroporous Polymers for Selective Separation of Acetylene from Ethylene

The design of highly stable and efficient porous materials is essential for developing breakthrough hydrocarbon separation methods based on physisorption to replace currently used energy-intensive distillation/absorption technologies. Efforts to develop advanced porous materials such as zeolites, coordination frameworks, and organic polymers have met with limited success. Here, a new class of ionic ultramicroporous polymers (IUPs) with high-density inorganic anions and narrowly distributed ultramicroporosity is reported, which are synthesized by a facile free-radical polymerization using branched and amphiphilic ionic compounds as reactive monomers. A covalent and ionic dual-crosslinking strategy is proposed to manipulate the pore structure of amorphous polymers at the ultramicroporous scale. The IUPs exhibit exceptional selectivity (286.1–474.4) for separating acetylene from ethylene along with high thermal and water stability, collaboratively demonstrated by gas adsorption isotherms and experimental breakthrough curves. Modeling studies unveil the specific binding sites for acetylene capture as well as the interconnected ultramicroporosity for size sieving. Finally, the porosity-engineering protocol used in this work can also be extended to the design of other ultramicroporous materials for the challenging separation of other key gas constituents.

36 MATERIALS SCIENCE↗

Identifying High-Performance Metal–Organic Frameworks for Low-Temperature Oxygen Recovery from Helium by Computational Screening

Metal–organic frameworks (MOFs) are an important class of porous crystalline materials for applications ranging from gas adsorption and separation to catalysis. There are thousands of potential MOFs available for separation applications. Here, we developed a computational approach to screen MOFs for the separation of oxygen–helium mixtures at low temperatures (100–200 K), conditions that were motivated by issues associated with propulsion in space-based settings. We used detailed molecular simulations for a small number of MOFs to develop screening methods that were then used to estimate the optimum temperatures for separations using pressure swing adsorption for 2932 MOFs from the CoRE MOF database and the swing capacity and oxygen–helium selectivity at these temperatures. We used the stability of the best-performing structures in the presence of moisture as a means to provide a short list of high-performance materials. In addition to identifying specific materials for oxygen–helium separations, this approach could prove useful for selecting adsorbents for other gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser-induced graphene gas sensors for environmental monitoring

Artemesia tridentatais a foundational plant taxon in western North America and an important medicinal plant threatened by climate change. Low-cost fabrication of sensors is critical for developing large-area sensor networks for understanding and monitoring a range of environmental conditions. However, the availability of materials and manufacturing processes is still in the early stages, limiting the capacity to develop cost-effective sensors at a large scale. In this study, we demonstrate the fabrication of low-cost flexible sensors using laser-induced graphene (LIG); a graphitic material synthesized using a 450-nm wavelength bench top laser patterned onto polyimide substrates. We demonstrate the effect of the intensity and focus of the incident beam on the morphology and electrical properties of the synthesized material. Raman analyses of the synthesized LIG show a defect-rich graphene with a crystallite size in the tens of nanometers. This shows that the high level of disorder within the LIG structure, along with the porous nature of the material provide a good surface for gas adsorption. The initial characterization of the material has shown an analyte response represented by a change in resistance of up to 5% in the presence of volatile organic compounds (VOCs) that are emitted and detected byArtemisiaspecies. Bend testing up to 100 cycles provides evidence that these sensors will remain resilient when deployed across the landscapes to assess VOC signaling in plant communities. The versatile low-cost laser writing technique highlights the promise of low-cost and scalable fabrication of LIG sensors for gas sensor monitoring.

Chemistry↗

Exploitation of Pore Structure for Increased CO 2 Selectivity in Type 3 Porous Liquids

CO 2 capture requires materials with high adsorption selectivity and an industrial ease of implementation. To address these needs, a new class of porous materials was recently developed that combines the fluidity of solvents with the porosity of solids. Type 3 porous liquids (PLs) composed of solvents and metal–organic frameworks (MOFs) offer a promising alternative to current liquid carbon capture methods due to the inherent tunability of the nanoporous MOFs. However, the effects of MOF structural features and solvent properties on CO 2 –MOF interactions within PLs are not well understood. Herein experimental and computational data of CO 2 gas adsorption isotherms were used to elucidate both solvent and pore structure influences on ZIF-based PLs. The roles of the pore structure including solvent size exclusion, structural environment, and MOF porosity on PL CO 2 uptake were examined. A comparison of the pore structure and pore aperture was performed using ZIF-8, ZIF-L, and amorphous-ZIF-8. Adsorption experiments here have verified our previously proposed solvent size design principle for ZIF-based PLs (1.8× ZIF pore aperture). Furthermore, the CO 2 adsorption isotherms of the ZIF-based PLs indicated that judicious selection of the pore environment allows for an increase in CO 2 selectivity greater than expected from the individual PL components or their combination. This nonlinear increase in the CO 2 selectivity is an emergent behavior resulting from the complex mixture of components specific to the ZIF-L + 2'-hydroxyacetophenone-based PL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗

Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery

We present our research where attention mechanism is extensively applied to various aspects of graph neural net- works for predicting materials properties. As a result, surrogate models can not only replace costly simulations for materials screening but also formulate hypotheses and insights to guide further design exploration. We predict formation energy of the Materials Project and gas adsorption of crystalline adsorbents, and demonstrate the superior performance of our graph neural networks. Moreover, attention reveals important substructures that the machine learning models deem important for a material to achieve desired target properties. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of state-of-the-art models some of which were built with hundreds of features at much higher computational cost. We show that sophisticated neural networks can obviate the need for elaborate feature engineering. Our approach can be more broadly applied to optimize gas capture processes at industrial scale.

Cong, Guojing↗

Size-Dependent Energy of Ni Nanoparticles on Graphene Films on Ni(111) and Adhesion Energetics by Adsorption Calorimetry

The use of carbon supports for late transition-metal nanoparticle catalysts has grown substantially in recent years due to efforts to develop electrocatalysts for clean energy applications and catalysts for new aqueous-phase biomass-related conversions and due to the evolution of new carbon materials with unique properties (e.g., graphene, carbon nanotubes, and so forth). However, much less is known about the bonding energetics of catalytic metal nanoparticles on carbon supports in comparison with oxide supports, which are more common for thermal catalysis. Here, we report the growth morphology and heats of adsorption of Ni vapor deposited onto graphene/Ni(111) at 300 K and 100 K using metal vapor single-crystal adsorption calorimetry and He + low-energy ion scattering (LEIS). These results provide the Ni chemical potential versus particle size, and the Ni/graphene adhesion energy. LEIS intensities suggest that Ni grows as flat-topped face-centered cubic islands with a nearly constant thickness of ~1.5 nm when deposited at 300 K. At 100 K, Ni grows as smaller nanoparticles, well modeled as hemispherical hexagonal close-packed nanoparticles with a density of ~2 × 10 16 particles/m 2 . The Ni chemical potential as a function of average particle diameter in the 0.5 to 4 nm range at 100 K was determined from the heats of Ni gas adsorption. Further, by fitting the measured chemical potential as a function of diameter, we determined an adhesion energy of 3.6 J/m 2 for large Ni particles on graphene/Ni(111). This adhesion energy is in good agreement with previous scanning tunneling microscopy and density functional theory investigations of Ni/graphene/Ni(111).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Graphitic Aza-Fused π-Conjugated Networks: Construction, Engineering, and Task-Specific Applications

2D π-conjugated networks linked by aza-fused units represent a pivotal category of graphitic materials with stacked nanosheet architectures. Extensive efforts have been directed at their fabrication and application since the discovery of covalent triazine frameworks (CTFs). Besides the triazine cores, tricycloquinazoline and hexaazatriphenylene linkages are further introduced to tailor the structures and properties. Diverse related materials have been developed rapidly, and a thorough outlook is necessitated to unveil the structure–property–application relationships across multiple subcategories, which is pivotal to guide the design and fabrication toward enhanced task-specific performance. Herein, the structure types and development of related materials including CTFs, covalent quinazoline networks, and hexaazatriphenylene networks, are introduced. Advanced synthetic strategies coupled with characterization techniques provide powerful tools to engineer the properties and tune the associated behaviors in corresponding applications. Case studies in the areas of gas adsorption, membrane-based separation, thermo-/electro-/photocatalysis, and energy storage are then addressed, focusing on the correlation between structure/property engineering and optimization of the corresponding performance, particularly the preferred features and strategies in each specific field. In the last section, the underlying challenges and opportunities in construction and application of this emerging and promising material category are discussed.

36 MATERIALS SCIENCE↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Fricke, Sophia N.↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring Gas Transport and Sorption in Large Intact Geologic Specimens via the Piezometric Method

Uptake of noble gases into heterogeneous geologic core samples was measured using a piezometric methodology. In addition to measuring accessible porosity—as with gas pycnometry—by monitoring the rate of pressure decay, this method can also be used to estimate the gas effective diffusivity in the sample. In contrast to previous applications of this method, where milligram quantities of fractured grains are characterized, here approximately kilogram core samples were left intact when tested. In doing so, a more representative sample of the heterogeneous field geology is provided. Additionally, alteration of the pore structure and connectivity during sample preparation is avoided. Furthermore, to scale the piezometric method from milligrams to kilograms, the system was designed to operate at medium vacuum (1 to 100 Pa) to restrict transport in pores less than approximately 60 µm to large Knudsen numbers. To test the system performance, two samples of interest were selected: a rhyolitic welded tuff from Blue Canyon Dome at the Energetic Materials Research and Testing Center and a zeolitized non-welded rhyolitic tuff from the Nevada National Security Site. Three noble gases were utilized in this test series; Argon and xenon as they are of direct interest to nuclear monitoring efforts and helium as it is a weakly adsorbing reference standard. Additionally, mercury intrusion porosimetry measurements were made on subsamples of the core to compare the observed porosity by the two methods and to discuss gas transport rates in the context of the measured pore distribution.

58 GEOSCIENCES↗

Multifunctional Prussian blue analogue magnets: Emerging opportunities

There is a surge of interest to expand the search for entirely new classes of molecular magnets as the emergence of information storage and quantum computing devices. Prussian blue analogues as a family of molecular magnets are especially attracting wide attention due to their large number of derivatives with a range of magnetic ordering temperature from cryogenic to high temperature. Furthermore, this review presents Prussian blue analogues as multifunctional molecular magnets, which involves the development of molecular magnet syntheses and crystal structures, and magnetic properties under external stimuli. In addition, the porous network structures and vacancy order of Prussian blue analogues present a wide capability to interact with water molecules and gas adsorption. External stimuli, such as thermal, pressure, electric and magnetic field and photoexcitation, play an important role in controlling the hidden states and cooperative phenomena of high temperature molecular magnets based on Prussian blue analogues.

36 MATERIALS SCIENCE↗

Metal–organic frameworks based on multicarboxylate linkers

When designing metal–organic frameworks (MOFs), linker design is one of the most important factors in constructing a wide variety of structures. Judicious choice of linker size, geometry, and connectivity can create diverse structures and topologies, which can aid in the quest to design MOFs with both high stability and permanent porosity. Multi-connected linkers have become a focus in the MOF community, as high connectivity can improve stability and tunability of frameworks. In particular, multicarboxylate ligands have been reported extensively in the literature to construct stable MOFs with versatile pore environments, which can be termed as metal-multicarboxylate frameworks (MMCFs). These structures have great application potential in gas adsorption and separation, catalysis, and sensing. In this work, we review the literature on multicarboxylate linkers (n COOH ≥ 3) in MOF systems and their applications, with specific emphasis on how high linker connectivity affects properties of MOFs such as topology, porosity, stability, and functionality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An emerging class of carbon materials: Synthesis and applications of carbon flowers

Porous carbon materials are widely applied in energy storage, gas adsorption, and catalysis applications because of their advantageous properties, such as high surface areas, tunable surface properties, chemical stability, high conductivity, and low cost. Recently, a flower-shaped carbon material, referred to as carbon flowers (CFs), has received attention as an emerging porous carbon material because of its unique shape. In this review, we summarize the synthetic strategies, characterization techniques, and formation mechanisms of CFs from various precursors. We also review the applications of CFs and their pros and cons. Last, we discuss challenges and perspectives for future development of CFs.

36 MATERIALS SCIENCE↗