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At least 127 records · Page 7

Simulated Moving Bed Process for CO 2 Capture from Humid Postcombustion Flue Gases Using MUF-16

Simulated moving bed (SMB) designs are increasingly being adapted for the separation of multicomponent gaseous mixtures. In this work, we develop a modified SMB process for capturing CO 2 from humid postcombustion flue gas using MUF-16 (MUF = Massey University Framework). MUF-16 shows excellent selectivity for CO 2 over N 2 , moderate heats of adsorption for CO 2 and H 2 O, and no competitive sorption of CO 2 over water at relative humidities relevant to postcombustion capture. We utilize these characteristics to propose a continuous process that uses N 2 from the feed as the desorbent for the water, eliminating the need for a separate desiccant bed and allowing for localized heating during desorption for H 2 O-saturated MOF beds. Single-component isotherms, single-column breakthrough experiments, and SO 2 stability tests suggest the excellent suitability of MUF-16 to this separation via the proposed SMB design.

CO2 capture from humid flue gas↗

A customized MOF-polymer composite for rapid gold extraction from water matrices

With the fast-growing accumulation of electronic waste and rising demand for rare metals, it is compelling to develop technologies that can promotionally recover targeted metals, like gold, from waste, a process referred to as urban mining. Thus, there is increasing interest in the design of materials to achieve rapid, selective gold capture while maintaining high adsorption capacity, especially in complex aqueous-based matrices. Here, a highly porous metal-organic framework (MOF)–polymer composite, BUT-33–poly(para-phenylenediamine) (PpPD), is assessed for gold extraction from several matrices including river water, seawater, and leaching solutions from CPUs. BUT-33–PpPD exhibits a record-breaking extraction rate, with high Au3+ removal efficiency (>99%) within seconds (less than 45 s), a competitive capacity (1600 mg/g), high selectivity, long-term stability, and recycling ability. Furthermore, the high porosity and redox adsorption mechanism were shown to be underlying reasons for the material’s excellent performance. Given the accumulation of recovered metallic gold nanoparticles inside, the material was also efficiently applied as a catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling of Multicomponent Trace Contaminant Adsorption on Activated Carbon

Modeling of multicomponent trace contaminant adsorption on activated carbon for spacecraft life support applications presents challenges due to the very low contaminant concentrations in cabin air coupled with very strong adsorption of heavier components such as cyclic polydimethylsiloxanes. Both gas-phase and solid-phase micropore mass transfer resistances can be important, and competitive interactions between adsorbed components can result in behavior such as roll-up where lighter components displaced by heavier components have a higher concentration at the outlet than at the inlet. This paper describes the further development of a dynamic trace contaminant adsorption model based on Ideal Adsorbed Solution Theory (IAST). Alternative 1-dimensional and 2-dimensional versions of the model are described with different mass transfer resistance and driving force assumptions. Optimization of solution methods for speed and stability is also described. Mass balance equations are scaled to provide sensitivity over the wide range of component concentrations in cabin air. Model parameters are estimated from isotherm and breakthrough test data on single adsorbate and binary adsorbate systems. Multicomponent results are compared against predictions of a heritage model used extensively by NASA for trace contaminant control system (TCCS) carbon bed sizing. Finally, efforts to implement the model in a second software platform for wider access are described.

Kevin E Lange↗

Selectively Reducing Nitrate into NH 3 in Neutral Media by PdCu Single-Atom Alloy Electrocatalysis

Electrocatalytic nitrate reduction reaction (NO 3 – RR) technology provides a promising solution to recover the nitrate nutrition from wastewater through catalyzing nitrate reduction into value-added NH 3 . However, the selectivity and efficiency of electrocatalysts are frustrated due to the imbalance of *H adsorption (for NO 3 hydrogenation) and unavoidable adjacent *H self-coupling on active sites, resulting in competitive hydrogen evolution reaction (HER). Here, we report a PdCu single-atom alloy (SAA) catalyst that allows isolated Pd sites to produce *H for the hydrogenation process of *NO 3 on neighboring Cu sites, which can restrain the *H self-coupling through extending the distance between two *H and thus effectively suppress competitive HER. Consequently, the PdCu SAA catalyst exhibits an ultrahigh NH 3 Faraday efficiency (FE) of 97.1% with a yield of 15.4 μmol cm –2 h –1 from the electrocatalytic NO 3 – RR in the neutral electrolyte, outperforming most of the reported catalysts. In conclusion, single-crystal experiments and theoretical calculations further prove that the introduction of atomic Pd on the Cu (100) surface could serve as the main active site and greatly decrease the energy barrier of the rate-determining step (RDS) on Cu from ΔG = 0.39 eV (*NOO → *NOOH) to ΔG = 0.10 eV of *NOH → *NHOH on PdCu SAA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystallization-assisted water adsorption in amorphous molecular adsorbents

Efficient and stable water adsorbents are essential for removing moisture from natural gas and olefins during their production. Industrial desiccants such as alumina and zeolites require high regeneration temperatures, while metal-organic frameworks often suffer from limited long-term stability and reusability. Here, we introduce a new type of molecular desiccants (M-PyC) that, in principle, can be reused indefinitely. These simple molecular coordination complexes undergo fully reversible phase transitions between crystalline and amorphous states through the decoordination (bond breaking) and recoordination (bond reforming) of water molecules. They exhibit high water uptake (30 wt%) and superb selectivity, excluding hydrocarbons entirely. Their effectiveness for dehydration, combined with low regeneration temperature, fast desorption kinetics, low-cost and green synthesis, easy scalability to kilogram quantities, and essentially unlimited recyclability, makes them truly competitive dehydration agents for industrial separations. The use of amorphous molecular adsorbents, where crystallinity and porosity are no longer stringent requirements, and the adsorption-desorption process entirely under ambient air, offers a conceptually different approach to adsorption-based separation science and potentially realistic solution to the long-standing challenge of sustained stability in coordinate-bonded adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fine-Tuning Microporosity of Crystalline Vanadomolybdate Frameworks for Selective Adsorptive Separation of Kr from Xe

Selective adsorptive capture and separation of chemically inert krypton (Kr) and xenon (Xe) noble gases with very low ppmv concentrations in air and industrial off-gases constitute an important technological challenge. Here, using a synergistic combination of experiment and theory, the microporous crystalline vanadomolybdates (MoVO x ) as highly selective Kr sorbents are studied in detail. By varying the Mo/V ratios, we show for the first time that their one-dimensional (1D) pores can be fine-tuned for the size-selective adsorption of Kr over the larger Xe with selectivities reaching >100. Using extensive electronic structure calculations and grand canonical Monte Carlo simulations, the competition between Kr uptake with CO 2 and N 2 was also investigated. As most materials reported so far are selective toward the larger, more polarizable Xe than Kr, this work constitutes an important step toward robust Kr-selective sorbent materials. Furthermore this work highlights the potential use of porous crystalline transition metal oxides as energy-efficient and selective noble gas capture sorbents for industrial applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Molecular Structure and Thermodynamics of CO 2 and Water Adsorption on Mica

The adsorption of CO 2 and water on clay surfaces plays a key role in applications, such as gas storage in saline aquifers and depleted hydrocarbon reservoirs, but is not yet fully understood. Here, we study the adsorption of CO 2 and water vapor using Grand Canonical Monte Carlo and molecular dynamics simulations. At a bulk pressure of 100 bar, pure CO 2 adsorbs strongly on mica and forms extensive layers next to it. CO 2 adsorption is lowered substantially if introducing water vapor above mica and is largely eliminated when the relative humidity (RH) approaches about 60%. When pure water vapor is introduced above a mica surface, a subnanometer thick liquid water film develops on it to form apparent liquid–solid and liquid–vapor interfaces simultaneously. Using the identification of truly interfacial molecules (ITIM) analysis, we delineate how individual water layers develop in this film as RH increases. We highlight that the water film is spatially heterogeneous and the true liquid–vapor interface emerges only at an RH of 60–80%. Introducing 100 bar of CO 2 into the water vapor above the mica surface modulates water adsorption nonlinearly: at RH = 0.01%, the water adsorption is reduced by ∼30%; as RH increases, the reduction is weakened, and eventually, enhancement of water adsorption by about 7% occurs at RH = 90%. These variations are attributed to the interplay of film thinning by high-pressure CO 2 , competition of mica surface sites by CO 2 molecules, and energetic and entropic stabilization of interfacial water by CO 2 molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Discovery of Complex Binding and Reaction Mechanisms from Ternary Gases in Rare Earth Metal–Organic Frameworks

Understanding the selectivity of metal–organic frameworks (MOFs) to complex acid gas streams will enable their use in industrial applications. In this study, ab initio molecular dynamic simulations (AIMD) were used to simulate ternary gas mixtures (H 2 O-NO 2 -SO 2 ) in rare earth 2,5-dihydroxyterephthalic acid (RE-DOBDC) MOFs. Stronger H 2 O gas-metal binding arose from thermal vibrations in the MOF sterically hindering access of SO 2 and NO 2 molecules to the metal sites. Gas-gas and gas-linker interactions within the MOF framework resulted in the formation of multiple secondary gas species including HONO, HNO 2 , NOSO, and HNO 3 ⁻. Four gas adsorption sites were identified along with a new de-protonation reaction mechanism not observable through experiment. This study not only provides valuable information on competitive gas binding energies in the MOF, but it also provides important chemical insights into transient chemical reactions and mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reactor scale simulations of ALD and ALE: Ideal and non-ideal self-limited processes in a cylindrical and a 300 mm wafer cross-flow reactor

Here, we have developed a simulation tool to model self-limited processes such as atomic layer deposition (ALD) and atomic layer etching inside reactors of arbitrary geometry as well the output of in situ quartz crystal microbalance and mass spectrometry. We have applied this model to two standard types of cross-flow reactors: a cylindrical tube reactor and a model 300 mm wafer reactor, and explored both ideal and nonideal self-limited kinetics. The model results are in agreement with experimental results and analytic expressions obtained using a simple plug-flow model for the cylindrical tube reactor. We also extended the simulations to consider two nonideal self-limited processes: soft-saturating processes characterized by a slow reaction pathway and processes where surface by-products can compete with the precursor for the same pool of adsorption sites. Our results show that it is possible to have a self-limited process with saturated yet inhomogeneous growth profiles due to the competition of reactor by-products. This is in agreement with experimental observations for titanium dioxide ALD from titanium tetraisopropoxide and titanium tetrachloride precursors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

On the Effect of Dust Particles on Global Cloud Condensation Nuclei and Cloud Droplet Number

Aerosol-cloud interaction studies to date consider aerosol with a substantial fraction of soluble material as the sole source of cloud condensation nuclei (CCN). Emerging evidence suggests that mineral dust can act as good CCN through water adsorption onto the surface of particles. This study provides a first assessment of the contribution of insoluble dust to global CCN and cloud droplet number concentration (CDNC). Simulations are carried out with the NASA Global Modeling Initiative chemical transport model with an online aerosol simulation, considering emissions from fossil fuel, biomass burning, marine, and dust sources. CDNC is calculated online and explicitly considers the competition of soluble and insoluble CCN for water vapor. The predicted annual average contribution of insoluble mineral dust to CCN and CDNC in cloud-forming areas is up to 40 and 23.8%, respectively. Sensitivity tests suggest that uncertainties in dust size distribution and water adsorption parameters modulate the contribution of mineral dust to CDNC by 23 and 56%, respectively. Coating of dust by hygroscopic salts during the atmospheric aging causes a twofold enhancement of the dust contribution to CCN; the aged dust, however, can substantially deplete in-cloud supersaturation during the initial stages of cloud formation and can eventually reduce CDNC. Considering the hydrophilicity from adsorption and hygroscopicity from solute is required to comprehensively capture the dust-warm cloud interactions. The framework presented here addresses this need and can be easily integrated in atmospheric models.

Karydis, V. A.↗

Designing Sites in Heterogeneous Catalysis: Are We Reaching Selectivities Competitive With Those of Homogeneous Catalysts?

A critical review of different prominent nanotechnologies adapted to catalysis is provided, with focus on how they contribute to the improvement of selectivity in heterogeneous catalysis. Ways to modify catalytic sites range from the use of the reversible or irreversible adsorption of molecular modifiers to the immobilization or tethering of homogeneous catalysts and the development of well-defined catalytic sites on solid surfaces. The latter covers methods for the dispersion of single-atom sites within solid supports as well as the use of complex nanostructures, and it includes the post-modification of materials via processes such as silylation and atomic layer deposition. All these methodologies exhibit both advantages and limitations, but all offer new avenues for the design of catalysts for specific applications. Because of the high cost of most nanotechnologies and the fact that the resulting materials may exhibit limited thermal or chemical stability, they may be best aimed at improving the selective synthesis of high value-added chemicals, to be incorporated in organic synthesis schemes, but other applications are being explored as well to address problems in energy production, for instance, and to design greener chemical processes. Finally, the details of each of these approaches are discussed, and representative examples are provided. We conclude with some general remarks on the future of this field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogen Storage with Aluminum Formate, ALF: Experimental, Computational, and Technoeconomic Studies

Long-duration storage of hydrogen is necessary for coupling renewable H 2 with stationary fuel cell power applications. In this work, aluminum formate (ALF), which adopts the ReO 3 -type structure, is shown to have remarkable H 2 storage performance at non-cryogenic (>120 K) temperatures and low pressures. The most promising performance of ALF is found between 120 K and 160 K and at 10 bar to 20 bar. The study illustrates H 2 adsorption performance of ALF over the 77 K to 296 K temperature range using gas isotherms, in situ neutron powder diffraction, and DFT calculations, as well as technoeconomic analysis (TEA), illustrating ALF’s competitive performance for long-duration storage versus compressed hydrogen and leading metal–organic frameworks. In the TEA, it is shown that ALF’s storage capacity, when combined with a temperature/pressure swing process, has advantages versus compressed H 2 at a fraction of the pressure (15 bar versus 350 bar). In conclusion, given ALF’s performance in the 10 bar to 20 bar regime under moderate cooling, it is particularly promising for use in safe storage systems serving fuel cells.

08 HYDROGEN↗

Hydrogen Storage with Aluminum Formate, ALF: Experimental, Computational, and Technoeconomic Studies

Long-duration storage of hydrogen is necessary for coupling renewable H2 with stationary fuel cell power applications. In this presentation, I will discuss how aluminum formate, Al(HCOO)3 (ALF), which adopts an ReO3-type structure, is shown to have remarkable H2 storage performance at non-cryogenic (> 120 K) temperatures and low pressures. The most promising performance of ALF is found between 120 K and 160 K and at 10 bar to 20 bar. The talk will cover and illustrate the H2 adsorption performance of ALF over the 77 K to 296 K temperature range using gas isotherms, in situ neutron powder diffraction, and DFT calculations, as well as technoeconomic analysis (TEA), illustrating ALF’s competitive performance for long-duration storage versus compressed hydrogen and leading metal–organic frameworks. In the TEA, it is shown that ALF’s storage capacity, when combined with a temperature/pressure swing process, has advantages versus compressed H2 at a fraction of the pressure (15 bar versus 350 bar). Given ALF’s performance in the 10 bar to 20 bar regime under moderate cooling, it is particularly promising for use in safe storage systems serving fuel cells, and is currently the only MOF that works in this moderate temperature range/ low pressure regime to be cost competitive with compressed H2 gas for large scale H2 storage.[1]

Chemistry↗

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗

Comparative life-cycle assessments and techno-economic analysis of renewable natural gas production pathways from biogas

Renewable natural gas (RNG) offers a promising pathway for decarbonizing hard-to-abate sectors. This study shows that, relative to conventional upgrading technologies (i.e., membrane separation and pressure swing adsorption), the catalytic methanation reaction (CMR) at water resource recovery facilities doubles RNG output. When consuming lowcarbon hydrogen, the CMR reduces operational energy use and global warming potential. Techno-economic analysis indicates that the CMR is not yet competitive but will become viable if hydrogen reaches $1/kg. Heat integration and hydrogen cost are key drivers of overall performance.

03 NATURAL GAS↗

Aryl Diazonium-Assisted Amidoximation of MXene for Boosting Water Stability and Uranyl Sequestration via Electrochemical Sorption

Despite that two-dimensional transition metal carbides and carbonitrides (MXenes) are burgeoning candidates for remediation of environmental pollutants, the construction of robust functionalized MXene nanosheets with a high affinity for target heavy metal ions and radionuclides remains a challenge. Here we report the successful placement of amidoxime chelating groups on Ti 3 C 2 T x MXene surface by diazonium salt grafting. The introduction of amidoxime functional groups significantly enhances the selectivity of Ti 3 C 2 T x nanosheets for uranyl ions and also greatly improves their stability in aqueous solution, enabling efficient, rapid, and recyclable uranium extraction from aqueous solutions containing competitive metal ions. Benefiting from the excellent conductivity of MXenes, the amidoxime functionalized Ti 3 C 2 T x nanosheets show outstanding electrochemical performance such that when loaded on carbon cloth the application of an electric field increases the uranium adsorption capacity from 294 to 626 mg/g, outperforming all organic electrochemical sorption materials reported previously. Finally, the present work provides an effective strategy to functionalize MXene nanosheets with fundamental implications for the design of MXene-based selective electrosorption electrode materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification

It is critical that machine learning (ML) model predictions be trustworthy for high-throughput catalyst discovery approaches. Uncertainty quantification (UQ) methods allow estimation of the trustworthiness of an ML model, but these methods have not been well explored in the field of heterogeneous catalysis. Herein, we investigate different UQ methods applied to a crystal graph convolutional neural network to predict adsorption energies of molecules on alloys from the Open Catalyst 2020 dataset, the largest existing heterogeneous catalyst dataset. We apply three UQ methods to the adsorption energy predictions, namely k-fold ensembling, Monte Carlo dropout, and evidential regression. The effectiveness of each UQ method is assessed based on accuracy, sharpness, dispersion, calibration, and tightness. Evidential regression is demonstrated to be a powerful approach for rapidly obtaining tunable, competitively trustworthy UQ estimates for heterogeneous catalysis applications when using neural networks. Recalibration of model uncertainties is shown to be essential in practical screening applications of catalysts using uncertainties.

36 MATERIALS SCIENCE↗