Search NASA⌕ Search

SEARCH · Search NASA

Results for “faster”

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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Manganese Oxidation during Vegetation Burning

Redox recycling of manganese (Mn) plays a key role in organic matter decomposition and nutrient cycling in terrestrial vegetated ecosystems, and it is expected to be changed by fires. This study revealed how Mn is oxidized during vegetation burning, by characterizing the chemical speciation of Mn in fire ash from wildland fires and laboratory burning and evaluating the factors governing its average oxidation state (AOS) and speciation. Manganese in wildland fire ash from different ecosystems showed variable AOS that ranges from 2.5 to 3.3. Laboratory burning experiments showed that Mn oxidation was primarily controlled by fire thermal intensity (temperature × duration) and burning completeness. As heating time increased from 5 min to 5 h at 550 and 700 °C, Mn AOS in the lab-burned vegetation ash increased from 2.7 to 4.0 and the oxidation rate was faster at higher temperature. Diverse Mn species can present in wildland fire ash and differ structurally from biogenic Mn oxides. The oxidized Mn species enable fire ash to mediate oxidative degradation of catechol, demonstrating its potential in mediating organic matter decomposition. This study revealed a new paradigm of Mn redox recycling, as compared to the microbe-mediated Mn redox cycling in the absence of fires.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Sustainable H 2 -Rich Syngas Production via Microwave-Assisted vs Conventional Catalysis of Pinewood

Catalytic gasification of biomass is a promising method for producing hydrogen-rich syngas, which is a valuable resource for cleanenergy applications. In this study, microwave-assisted biomass gasification was compared with conventional thermally driven biomass gasification using pinewood as the biomass without the use of external gasifying agents (such as air, steam, and CO 2 ), under non-catalytic and catalytic conditions. The catalysts consisted of either an iron or a nickel catalyst, and the pinewood used as biomass contained 42% oxygen. This comparative analysis explores the differences in reaction chemistry, product yields, and the role of key reactions such as the water gas shift (WGS) reaction, Boudouard reaction, etc. The gas-phase and liquid-phase products were analyzed using online gas chromatography, and the fresh and spent catalysts were analyzed using X-ray diffraction (XRD) techniques. It was found that microwave-assisted gasification offers advantages in terms of enhanced reaction efficiency, catalyst stability, and hydrogen yield. For the microwave-assisted reaction, the gas yield reached 87%, the char yield was 12.1%, and the tar yield was less than 1% (0.793%) at 550 °C. In contrast, thermal-assisted gasification using the same catalyst produced a gas yield of 85.796%, char yield of 11.438%, and higher tar yield of 2.8% at 900 °C. The higher microwave-assisted performance was attributed to faster heating and better control over reaction conditions, higher reaction rates, and more favorable conditions for hydrogen production.

biomass↗
DOE OSTI2024

A DFT Comparison of C–C Reductive Coupling from Terminal Cyanido and Cyaphido Complexes of Nickel

The density functional theory study of the thermal C–C reductive coupling from terminal cyanido and hypothetical cyaphido complexes of [Ni(dmpe)] (dmpe = 1,2-bis(dimethylphosphino)ethane) revealed the key reaction intermediate in the reductive C–CP coupling being a σ-CC complex unlike an η 2 -aryl complex in the Ni C–CN system, as already observed in our previous studies. The reaction in THF is endothermic by 4.9 kcal/mol for cyanido with a 32.0 kcal/mol activation barrier and exothermic by 28.5 kcal/mol for cyaphido with an 11.3 kcal/mol activation barrier. To compare our results with the existing experimental data, we chose mesityl as the aryl group and also studied the CP reaction with [Pt(dmpe)] and [Pt(dmpm)] (dmpe = 1,2-bis(dimethylphosphino)methane) fragments. Our findings are consistent with the thermodynamically uphill photolytic C–CP bond activation in phosphaalkynes with Pt and a faster thermal back-reaction with [Pt(dmpe)] compared to that of [Pt(dmpm)]. Furthermore, based on the natural population analysis, when the polarity of the C–C bond is inverted, the sign of ΔG° is also inverted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

MechBERT: Language Models for Extracting Chemical and Property Relationships about Mechanical Stress and Strain

Language models are transforming materials-aware naturallanguage processing by enabling the extraction of dynamic, context-rich information from unstructured text, thus, moving beyond the limitations of traditional information-extraction methods. Moreover, small language models are on the rise because some of them can perform better than large language models (LLMs) when given domain-specific questionanswer tasks, especially about an application area that relies on a highly specialized vernacular, such as materials science. We therefore present a new class of MechBERT language models for understanding mechanical stress and strain in materials. These employ Bidirectional Encoder Representations for transformer (BERT) architectures. We showcase four MechBERT models, all of which were pretrained on a corpus of documents that are textually rich in chemicals and their stress–strain properties and were fine-tuned on question-answering tasks. We evaluated the level of performance of our models on domain-specific as well as general English-language question-answer tasks and also explored the influence of the size and type of BERT architectures on model performance. We find that our MechBERT models outperform BERT-based models of the same size and maintain relevancy better than much larger BERT-based models when tasked with domain-specific question-answering tasks within the stress–strain engineering sector. These small language models also enable much faster processing and require a much smaller fraction of data to pretrain them, affording them greater operational efficiency and energy sustainability than LLMs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2025

Deciphering the Scattering of Mechanically Driven Polymers Using Deep Learning

Here, we present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compressed into a three-dimensional latent space using a Variational Autoencoder (VAE), and two converter networks establish a bidirectional mapping between the polymer parameters (bending modulus, stretching force, and steady shear) and the scattering functions. The training data are generated using off-lattice Monte Carlo simulations to avoid the orientational bias inherent in lattice models, ensuring robust sampling of polymer conformations. The feasibility of this bidirectional mapping is demonstrated by the organized distribution of polymer parameters in the latent space. By integrating the converter networks with the VAE, we obtain a generator that produces scattering functions from given polymer parameters and an inferrer that directly extracts polymer parameters from scattering data. While the generator can be utilized in a traditional least-squares fitting procedure, the inferrer produces comparable results in a single pass and operates 3 orders of magnitude faster. This approach offers a scalable automated tool for polymer scattering analysis and provides a promising foundation for extending the method to other scattering models, experimental validation, and the study of time-dependent scattering data.

Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2025

Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units

Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes. Performance improvements of 5–10x in total application runtime were observed in LASSCF calculations for multimetallic catalyst systems up to 1200 AOs and an active space of (22e,40o) using up to four NVIDIA A100 GPUs. Furthermore, written with performance portability in mind, a comparable performance is also observed in early runs on the Aurora exascale system using Intel Max Series GPUs.

Algorithms↗
DOE OSTI2025

Accelerating Instanton Theory with the Line Integral Nudged Elastic Band Method and Gaussian Process Regression

Quantum tunneling plays a fundamental role in many chemical reactions, particularly proton transfer processes. Ring polymer instanton theory offers a practical framework for computing tunneling rates in complex molecular systems. However, applying the ring polymer instanton method with a potential energy surface generated on-the-fly using electronic structure calculations can be computationally demanding. Here, in this work, we present a new efficient implementation of the ring polymer instanton method by combining the Line Integral Nudged Elastic Band (LI-NEB) approach with Gaussian Process Regression (GPR). We benchmarked this method on prototypical ground-state proton transfer systems, including the benchmark gas-phase hydrogen abstraction reaction H + CH 4 → H 2 + CH 3 , malonaldehyde, and Z-3-amino-propenal (aminopropenal). Our results show that this approach is an order of magnitude faster than traditional instanton algorithms while maintaining excellent agreement with their tunneling rates. This development opens the door to studying proton transfer in larger systems with improved efficiency.

chemical physics↗
DOE OSTI2025

A Theory of Ultrafast Charge Transfer Relaxation with Non-Innocent Solvent Molecules

In this work we revisit the photodynamics of tetracyanoethylene-hexamethylbenzene (TCNE- HMB), the molecular complex studied by Hochstrasser et al. [J. Chem. Phys. 100, 4797–4810, 1994] that has long challenged the applicability of Marcus’s theory of elec- tron transfer for predicting photochemical reactions. Using a novel black-box electronic structure algorithm (time-dependent density functional theory with one double, TD- DFT-1D) to efficiently run molecular dynamics that can treat charge recombination, we run ab initio surface hopping molecular dynamics and confirm that, for a polar solvent, charge recombination rates can be incredibly fast (indeed faster than the sol- vent relaxation time); for non-polar solvents, the rate is much slower. We demonstrate that, although Marcus theory cannot be directly applied, these nonequilibrium (and sometimes incredibly fast) photoexcited dynamics can be effectively explained within a two-state model without any evidence of a transition through a conical intersection. Most importantly, for this paradigmatic model system, we are able to identify two nuclear coordinates of interest (rather than the single coordinate predicted by Marcus or a full set of internal quantum modes studied by Bixon and Jortner): the solvent relaxation in the first shell (that strongly modulates the energies of the charge trans- fer state and differentiates time scales for relaxation) and a nuclear displacement in the TCNE-HMB complex arising from a handful of vibrations that induces non-Born Oppenheimer motion and eventually facilitates an abrupt electronic transition to the ground state. Altogether, these findings suggest a tractable generalization of Marcus theory for future simulations of photochemistry with non-innocent solvent environ- ments in the spirit of a Hamiltonian suggested by Stuchebrukhov (J. Chem. Phys. 107, 3821, 1997).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Overset-Grid Method with Smooth Orbital Partitioning for Molecular Scattering Calculations

To solve molecular photoionization and electron scattering problems, we use an overset-grid representation of electronic continuum functions, which has an extended central spherical grid that overlaps small spherical grids (subgrids) centered on each atom of a polyatomic molecule. Here, in this work, we present an improved algorithm that smoothly partitions the total wave function between the central grid and the atomic subgrids. The smooth partitioning allows one to use approximately one-fourth the number of partial waves on the central grid compared to our previous implementation with switching functions. The resulting numerical method for treating electron scattering and photoionization of polyatomic molecules combines the accuracy and flexibility of pure numerical grid representations with the rapid convergence of hybrid combinations of atom-centered basis-set expansions and grid methods. The overset-grid representation is implemented using the complex Kohn variational principle for scattering and photoionization amplitudes. The faster convergence with respect to the number of central grid partial waves is demonstrated and accuracy is verified by comparisons with the previous implementation and with far more computationally demanding single-center numerical expansions in electron-molecule scattering and photoionization calculations on the neon dimer (Ne 2 ) system, carbon tetrafluoride (CF 4 ) molecule, and the pyridine (C 5 H 5 N) molecule in the static-exchange approximation.

Molecules↗
DOE OSTI2026

Hierarchical Reinforcement Learning of a Short-Range Bond-Order Potential for Silica: Analytic Embedding of Coordination with Classical Efficiency

Reinforcement learning (RL) has recently emerged as a data-efficient strategy to parametrize short-range interatomic potentials. Building on our past RL optimization of pairwise silica models, we extend the framework to a bond-order (Tersoff-type) potential that provides an analytic embedding of local coordination through a three-body term. A hierarchical RL workflow combining continuous-action Monte Carlo Tree Search and property-based rewards efficiently explores the 26-dimensional parameter space, sequentially optimizing lattice parameters, densities, angles, and cohesive energies of 21 silica polymorphs. The resulting models, Q-Tersoff and ML-Tersoff, reproduce the energetic ordering of low-energy phases and capture the angular correlations and amorphous structure factors of silica with improved fidelity over pairwise force fields, while remaining orders of magnitude faster than high-dimensional machine-learned potentials. Both models underperform for elastic constants and high-energy frameworks, delineating the limits of the current analytic form. The approach establishes a general and interpretable route to angle-aware, short-range potentials that bridge physics-based and machine-learned descriptions of silicate materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rationally Designed, Short-Acting RPE65 Inhibitors for Visual Cycle-Associated Retinopathies

Abstract The visual cycle is a metabolic pathway essential for visual function. The bisretinoid byproducts of this pathway can induce retinal toxicity, as occurs in Stargardt disease type 1 (STGD1). Emixustat, which inhibits bisretinoid production, is a visual cycle modulator (VCM) that targets RPE65. However, it causes visual impairment due to its unfavorable duration of action. Here, we report ester-containing analogs of emixustat that are susceptible to hydrolytic clearance and function as short-acting VCMs. We show that the esterase-mediated metabolism of these compounds can be tuned while maintaining high-affinity RPE65 targeting. Compounds 6 (EYE-002) and 7 (EYE-003) containing diethyl acetate and valproate esters, respectively, allowed faster recovery of visual cycle function compared to emixustat. These molecules protected against retinal degeneration in mouse models of photic retinopathy and STGD1. These data demonstrate that shorter attenuation of the visual cycle can therapeutically intervene in retinal diseases with fewer visual side effects compared to emixustat.

Pharmacology & Pharmacy↗
DOE OSTI2025

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Functional Connectivity of Red Chlorophylls in Cyanobacterial Photosystem I Revealed by Fluence-Dependent Transient Absorption

External stressors modulate the oligomerization state of photosystem I (PSI) in cyanobacteria. The number of red chlorophylls (Chls), pigments lower in energy than the P700 reaction center, depends on the oligomerization state of PSI. Here, we use ultrafast transient absorption spectroscopy to interrogate the effective connectivity of the red Chls in excitonic energy pathways in trimeric PSI in native thylakoid membranes of the model cyanobacterium Synechocystis sp. PCC 6803, including emergent dynamics, as red Chls increase in number and proximity. Fluence-dependent dynamics indicate singlet–singlet annihilation within energetically connected red Chl sites in the PSI antenna but not within bulk Chl sites on the picosecond time scale. These data support picosecond energy transfer between energetically connected red Chl sites as the physical basis of singlet–singlet annihilation. The time scale of this energy transfer is faster than predicted by Förster resonance energy transfer calculations, raising questions about the physical mechanism of the process. Our results indicate distinct strategies to steer excitations through the PSI antenna; the red Chls present a shallow reservoir that direct excitations away from P 700 , extending the time to trapping by the reaction center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The Impact of Carotenoid Energy Levels on the Exciton Dynamics and Singlet–Triplet Annihilation in Isolated Bacterial Light-Harvesting 2 Complexes

The light-harvesting 2 (LH2) complex of purple phototrophic bacteria plays a critical role in absorbing solar energy and distributing the excitation energy. Exciton dynamics within LH2 complexes are controlled by the structural arrangement and energy levels of the bacteriochlorophyll (BChl) and carotenoid (Car) pigments. However, there is still debate over the competing light-harvesting versus energy-dissipation pathways. In this work, we compared five variants of the LH2 complex from genetically modified strains of Rhodobacter sphaeroides, all containing the same BChls but different Cars with increasing conjugation: zeta-carotene (N = 7; LH2 Zeta ), neurosporene (N = 9; LH2 Neu ), spheroidene (N = 10; LH2 Spher ), lycopene (N = 11; LH2 Lyco ), and spirilloxanthin (N = 13; LH2 Spir ). Absorption measurements confirmed that the Car excited-state energy decreased with increasing conjugation. Similarly, fluorescence spectra showed that the B850 BChl emission peak had an increasing red shift from LH2 Zeta →(LH2 Neu /LH2 Spher )→LH2 Lyco →LH2 Spir . In contrast, time-resolved fluorescence and ultrafast transient absorption (fs-TA) revealed similar excited-state lifetimes (∼1 ns) for all complexes except LH2 Spir (∼0.7 ns). From fs-TA analysis, an additional ∼7 ps nonradiative dissipation step from B850 BChl was observed for LH2 Zeta . Further, singlet− singlet and singlet−triplet annihilation studies showed a ∼50% average fluorescence lifetime reduction in LH2Zeta at high laser power and high repetition rate, compared to ∼10−15% reductions in LH2 Neu /LH2 Spher /LH2 Lyco and minimal lifetime change in LH2 Spir . In LH2 Zeta , the fastest decay component (<50 ps) became prominent at high repetition rates, consistent with strong singlet−triplet annihilation. Nanosecond TA measurements revealed long-lived (>40 μs) BChl triplet states in LH2 Zeta and signs of damage caused by singlet oxygen, whereas other LH2s showed faster triplet quenching (∼18 ns) by Cars. These findings highlight a key design principle of LH2 complexes: the Car triplet energy must be significantly lower than the BChl triplet energy to efficiently quench BChl triplets that otherwise act as potent “trap states,” causing exciton annihilation in laser-based experiments or photodamage in native membranes.

Absorption↗
DOE OSTI2026

Insights into Rotational and Translational Dynamics in Mixtures of Ethylene Glycol and Choline Chloride Using Nuclear Magnetic Resonance Techniques

This work examines molecular dynamics and interactions in ethylene glycol–choline chloride (EG–ChCl) mixtures across 0–33 mol % ChCl, spanning the true eutectic region near 17–20 mol % and the commonly used 1:2 formulation. We combine pulsed-field-gradient (PFG) diffusion, fast-field-cycling (FFC) relaxometry, temperature-dependent 13 C T 1 , and nuclear Overhauser effect spectroscopy (NOESY) to disentangle local from macroscopic dynamics. PFG and FFC show that both translational and average rotational motions largely track the strong increase in viscosity with ChCl content, with ethylene glycol consistently diffusing faster than the choline cation and no global dynamical anomaly at the eutectic composition. More subtle, site-specific composition effects nevertheless emerge. The ratio of the diffusion coefficient of the hydroxyl group of choline to the diffusion coefficient of the methyl group of choline displays a shallow minimum in the 17–25 mol % region, indicating a modest change in how the hydroxyl-bearing end of choline samples the underlying translational motion relative to the methyl groups. 13 C T 1 analysis shows that rotational correlation times at 25 °C generally increase with ChCl, reflecting viscosity-coupled slowing, while the CH 2 –N α site exhibits a small but reproducible deviation from this monotonic trend near the eutectic. NOESY spectra at similar compositions reveal enhanced cross-relaxation between EG and choline protons, consistent with increased headgroup–solvent contact density rather than a wholesale structural rearrangement. Overall, our multitechnique study demonstrates that EG–ChCl dynamics are predominantly viscosity-dominated, with the eutectic region acting as a subtle dynamical crossover where specific choline segments become maximally coupled to the hydrogen-bond network. These insights refine the structure–dynamics picture of choline-chloride DESs and provide practical guidance for tuning composition in electrochemical, separation, and catalytic applications.

diffusion↗
DOE OSTI2024

Structure and Dynamics of Aqueous Electrolytes at Quartz (001) and (101) Surfaces

Here, understanding and describing reactivity at mineral-water interfaces such as ion adsorption, the kinetics of dissolution, or surface charge development depends on our ability to improve the accuracy of electrical double layer (EDL) models. While molecular dynamics (MD) simulations are routinely used to investigate the structure and energetics of adsorbed ions comprising the EDL, less attention is paid to their self-diffusion dynamics, which can uniquely inform on coupling to interfacial reactions. Here we use MD to investigate both the organization and diffusion dynamics of water and electrolyte ions (NaCl, KCl, CaCl 2 ) at hydroxylated quartz (001) and (101) surfaces, a comparison which allowed us to assess surface structural effects of corrugation and silanol density. We found that inner- versus outer-sphere complex formation depends on cation size and charge but not necessarily hydration energies. Participation of surface silanols in the hydration spheres of Na + and K + generally indicated their preference for inner-sphere complexation, but this depends strongly on the orientation of the surface considered through its influence over the organization and dynamics of adsorbed water layers. In particular, surface orientation substantially affects the diffusive behavior of the near-surface water. Na + was found to decrease the mobility of water in the first layer, consistent with an increasing frequency of hydrolysis implied by faster quartz dissolution rates observed in experiments via the well known salt effect. Our results are also in good agreement with the observed dissolution rate of quartz vs. surface adsorption strength measure by Dove and Nix. This study sets the stage for a forthcoming paper examining how the dynamics at quartz/electrolyte interfaces are influenced by externally applied electric fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

High-Temperature Water Adsorption Isotherms and Ambient Temperature Water Diffusion Rates on Water Harvesting Metal–Organic Frameworks

Water adsorption isotherms from 25 to 125 °C were measured for three metal−organic frameworks (MOFs), MOF-303, MOF-LA2-1, and MIL-100(Fe), which are frequently studied for water harvesting applications. The results show how the step in the water adsorption isotherm varies as a function of temperature and detail the combination of pressure and temperature necessary to remove adsorbed water. Furthermore, isobaric−isothermal Gibbs ensemble Monte Carlo simulations performed for MOF-303 shed light on the change in occupation numbers of the different known water adsorption sites with increasing temperature. Additionally, the diffusion rates of water through these materials were measured using concentration swing frequency response, and micropore diffusion was identified as the controlling mechanism. The Darken relation was used to show the dependence of the diffusion rate on the concentration and the impact of the adsorption isotherm slope. The adsorption of water on MOF-LA2-1 is faster than that on MIL-100(Fe). These data show that MOF-LA2-1 with its high-water adsorption capacity, quick adsorption rate, and favorable desorption energetics is a leading candidate for atmospheric water harvesting.

Adsorption↗