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Comprehensive Assessment of the Accuracy of the Ideal Adsorbed Solution Theory for Predicting Binary Adsorption of Gas Mixtures in Porous Materials

Quantifying the adsorption of chemical mixtures in porous adsorbents is critical to developing these materials for useful separation applications. The ideal adsorbed solution theory (IAST) is the most widely applied mixing theory for predicting mixture adsorption using single-component adsorption data, but a perceived lack of experimental data has limited previous efforts to explore the accuracy of IAST in a systematic way. In this paper, we take advantage of a large collection of binary experimental data for gas adsorption that became available recently to tackle this issue. Specifically, we identify more than 400 examples in which binary adsorption data and single-component data are available in the same publication and apply IAST to all these examples. This analysis includes experimental data from 63 gas mixtures of 37 different molecular species and 174 different adsorbents. In addition to being the most systematic evaluation to date of the accuracy of IAST for gas adsorption, these data will be valuable for future efforts to test or develop mixing theories that improve upon IAST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energetics of CO 2 and H 2 O adsorption on alkaline earth metal doped TiO 2

The process of CO 2 and H 2 O adsorption on the surface of nano-oxide semiconductors is important in the overall performance of artificial photosynthesis and other applications. In this study, we explored the thermodynamics of CO 2 and H 2 O adsorption on TiO 2 as a function of surface chemistry. We applied gas adsorption calorimetry to investigate the energetics of adsorption of those molecules on the surface of anatase nanoparticles. In an attempt to increase TiO 2 surface affinity to CO 2 and H 2 O, TiO 2 was doped with alkaline earth metals (MgO, CaO, SrO, and BaO) by manipulating the chemical synthesis. Adsorption studies using diffuse reflectance infrared spectroscopy at different temperatures indicate that due to the segregation of alkaline earth metals on the surface of TiO 2 nanoparticles, both CO 2 and subsequent H2O adsorption amounts could be increased. CO 2 adsorbs in two different manners, forming carbonates which can be removed at temperatures lower than 700 °C, and a more stable linear adsorption that remains even at 700 °C. Additionally to the surface energetic effects, doping also increased specific surface area, resulting in further improvement in net gas adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metal–Organic Frameworks for Per- and Polyfluoroalkyl Substances Treatment in Contaminated Water

Per- and polyfluoroalkyl substances (PFAS) are synthetic pollutants known for their chemical stability, environmental persistence, and toxicological risks. Their widespread use has led to extensive contamination, particularly in aquatic systems. Conventional treatment methods often face challenges such as high energy consumption and the production of secondary pollutants. Metal− organic frameworks (MOFs), with their high surface areas and tunable structures, have emerged as promising materials for PFAS remediation. This review summarizes recent progress in MOF-based PFAS adsorption and degradation, highlighting key frameworks such as MIL, UiO, and ZIF. Mechanistic insights into adsorption behavior and regeneration capabilities are discussed, along with the catalytic performance of MOF composites and postmodified systems in degradation pathways. The review concludes with design strategies for next-generation MOF materials aimed at efficient, sustainable PFAS removal under realistic conditions.

Adsorption↗

Revealing an Intermediate Cu–O/OH Superstructure on Cu(110)

Identifying the atomic structure and formation mechanism of intermediates during chemical transformations is challenging because of their short-lived nature. With a combination of microscopic and spectroscopic measurements and first-principles calculations, herein we report the formation of a metastable intermediate Cu–O/OH superstructure during the reaction of hydrogen with oxygen-covered Cu(110). This superstructure resembles the parent c(6 × 2)-O phase and can be termed as c(6 × 2)-(4O+2OH) with OH groups occupying the missing Cu sites between isolated Cu atoms. Using atomistic calculations, we elucidate the reaction pathways leading to the c(6 × 2)-(4O+2OH) formation via both molecular and dissociative H 2 adsorption. In this work, the results demonstrate the complex surface dynamics resulting from the parallel reaction pathways and may open up the possibility of directing the reaction dynamics by deliberately manipulating transient surface structure and composition.

36 MATERIALS SCIENCE↗

Combining Theory and Experiment to Map the Atomic-Level Structure–Energy Pathways of Adsorbate-Mediated Phase Changes in a Cooperatively Flexible Metal–Organic Framework

An important subclass of metal–organic frameworks (MOFs) exhibits cooperative flexibility, wherein individual crystallites undergo global structural phase changes in response to external stimuli. Where cooperative flexibility results in reversible changes between crystalline states of distinct accessible porosity, these frameworks can exhibit rare yet desirable behaviors that cannot be explained by local dynamics alone. Yet, the chemical and structural origins of cooperative flexibility and how frameworks undergo these reversible phase changes at the atomic level remain poorly understood. Deliberate design for specific applications is therefore exceedingly difficult, and there is great impetus to develop a fundamental understanding of this phenomenon. Here, an effective and widely accessible computational approach is developed, which is designed to provide microscopic resolution via direct comparison to experimental data along the desorption-guided pathway. The strategy is applied to explain the desorption-induced phase change in an experimentally well-characterized framework, CdIF-13 (sod-Cd(benzimidazolate)2), where experiment alone was unable to resolve the atomistically detailed phase change landscape. Our findings reveal that the cooperative phase change pathways are adsorbate dependent with thermodynamics of intermediate structural states dictated by a nuanced interplay of ligand orientation, skeletal symmetry, and modes of surface adsorption. The results reveal that this isotropically flexible framework is “chaperoned” through a complex energy landscape by specific adsorbates, revealed by the reported computational approach with atomic-level insight and validated by experimentally determined structures. Thus, this work facilitates both understanding and future design of flexible materials for applications in gas storage, transport, delivery, and separation technologies.

03 NATURAL GAS↗

Correction to “Toward Chemical Accuracy for Chemi- and Physisorption with an Efficient Density Functional”

In the original manuscript, the value of parameter c was not explicitly provided. We wish to clarify that c was refitted to the hydrogen atom exchange energy, using the updated value of κ. With the updated κ = 0.2501, the optimized value of the parameter is c = 0.391596228. These values supersede any implicit assumptions about c in the original manuscript, and readers are encouraged to use these parameters for reproducing the results presented therein.

Adsorption↗

Multifunctional transitional metal-based phosphide nanoparticles towards improved polysulfide confinement and redox kinetics for highly stable lithium-sulfur batteries

The shuttle effect and the sluggish redox kinetics of lithium polysulfides (LiPSs) are the major issues impeding the practical applications of lithium-sulfur batteries (LSBs). Herein, a highly-efficient Ni 2 P electrocatalyst supported on N, P co-doped graphene (Ni 2 P@NPG) is developed via a simple “recrystallization-self-assembly” method to address the above issues. Here, the ultrafine Ni 2 P nanoparticles ensure abundant adsorption-diffusion-conversion interfaces for accelerating LiPSs transformation and Li 2 S deposition, which extremely decreases the accumulation of LiPSs in the electrolyte and therefore prevents the migration of LiPSs. Their superior catalytic performance is demonstrated by reduced Gibbs free energy changes of rate-limiting step based on the systematic theoretical calculations and the reduced shuttle effect is tested by the three-dimensional reconstructions of Raman depth profiles. Benefiting from these synergistic effects, the LSBs with Ni 2 P@NPG modified separators present a superior cycling performance with an average capacity decay rate of 0.048 % per cycle at 1C around the 400 cycles and a high-rate capacity of 731 mAh/g at 2C. Even with a high-sulfur loading of 3.53 mg cm –2 , the cell can still contain a reversible capacity of 809 mAh/g at 0.2C with a remarkable columbic efficiency of 98.4 %.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In situ molecular imaging of ion clusters reveals the acid gas capture capacity and mechanism of water-lean ionic liquids

Water-lean solvents are a promising technology for capturing acid gases like carbon dioxide (CO 2 ). In situ liquid time-of-flight secondary ionization mass spectroscopy (ToF-SIMS) is used to study a representative solvent N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (2-EEMPA) with different CO 2 loadings to reveal the complex solvent structure upon CO 2 capture. Characteristic peaks of 2-EEMPA, such as m/z – 215 C 11 H 23 N 2 O 2 – (deprotonated 2-EEMPA) and m/z + 217 C 11 H 25 N 2 O 2 + (protonated 2-EEMPA), are detected due to acid gas uptake. Also, solvent molecules and carboxylate ion pairs, such as m/z – 259 C 12 H 23 N 2 O 4 – [(deprotonated 2-EEMPA∙∙∙CO 2 )] and m/z + 261 C 12 H 25 N 2 O 4 + (protonated 2-EEMPA∙∙∙CO 2 ), are observed. Interestingly, more than one CO 2 molecule can be captured per each solvent molecule as evidenced in SIMS mass spectra, for example, m/z – 321 C 13 H 25 N 2 O 7 – [(deprotonated 2-EEMPA)∙∙∙2CO 2 ∙∙∙H 2 O], m/z + 305 C 13 H 25 N 2 O 4 + [(protonated 2-EEMPA)∙∙∙2CO 2 ], m/z – 389 C 17 H 29 N 2 O 8 – [(deprotonated 2-EEMPA)∙∙∙3CO 2 ∙∙∙3CH 2 ], and m/z + 373 C 16 H 25 N 2 O 8 + [(protonated 2-EEMPA)∙∙∙3CO 2 ∙∙∙2C]. However, the monomer of 2-EEMPA and CO 2 seems to be most prevalent. Furthermore, solvent clusters are detected in loaded solvents, for instance m/z + 433 C 22 H 49 N 4 O 4 + [(2-EEMPA)2∙∙∙H] and m/z + 646 [(2-EEMPA) 3 -2H], while capturing CO 2 at different amounts. Relative abundance of cluster ions provides a semi-qualitative venue to assess the free energies of gas capture energetics, indicating the relative stability trend within the same solvent system, previously impossible. These observed ion clusters are verified with molecular modeling, where dimer, trimer, and cluster ions are validated for their presence either due to weak molecular interactions or hydrogen bonds. In situ molecular imaging of ionic liquids and molecular modeling reveals that the acid gas capture mechanism by ionic liquids includes both physical adsorption and chemical bonding with multiple reaction pathways, engaging cluster formation and alteration of solvent structures.

Acid gas capture↗

Exploring the Influence of Linker Substitution and Ratios on Cooperative Framework Flexibility through the Mixed-Linker Approach

Cooperatively flexible metal–organic frameworks that exhibit step-shaped, or Type V-like, adsorption–desorption profiles can lower requisite pressure–temperature swings and thus energy input, necessary for an array of gas storage, delivery, and separations applications. However, such benefits are lost if the pressure threshold of the adsorption and desorption steps at a given temperature does not match the conditions dictated by the application, such as H 2 storage and delivery or olefin–paraffin separations. Unfortunately, the discovery of cooperatively flexible frameworks remains wholly serendipitous and de novo design remains impossible. Accordingly, there is a great need to further our understanding of flexibility such that we can intuitively derivatize known frameworks and, ultimately, design entirely new ones to meet the requisite conditions of energy-consumptive processes. In this work, we demonstrate that the mixed-linker, or multivariate, approach is a powerful tool for the derivation of a known flexible framework, with variances in linker substitution and ratio giving rise to a family wherein significant changes to the step-shaped adsorption–desorption profiles for multiple adsorbates are observed. Specifically, we report 12 isostructural mixed-linker derivatives of CdIF-13 (sod–Cd(benzimidazolate) 2 ) with six point-modified benzimidazole linkers spontaneously synthesized through prototypical solvothermal conditions. Furthermore, each is shown by PXRD to exhibit similar reversible flexibility to CdIF-13 and by TGA and DSC to be similarly thermally stable. Isothermal gas adsorption measurements with N 2 at 77 K, CO 2 at 195 K, and propane at 298 K demonstrate the wide-ranging, adsorbate-dependent effects of linker substitution and ratio, including dramatic reductions in the adsorption threshold pressure, evolution of multiple steps, and complete absence of observable adsorption. Aided by prior crystallographic characterization of CdIF-13, the observed trends were analyzed in an attempt to resolve the influence of linker substitution and ratios on structural behavior. In total, this work illustrates how the mixed-linker approach enables the synthesis and study of a large catalog of functionally modified frameworks, which can help identify the variables that influence flexibility and sorption behavior.

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Insights into Supported Subnanometer Catalysts Exposed to CO via Machine-Learning-Enabled Multiscale Modeling

Subnanometer catalysts offer high noble metal utilization and superior performance for several reactions. However, understanding their structures and properties on an atomic scale under working conditions is challenging due to the large configurational space. Here, we introduce an efficient multiscale framework to predict their stability exposed to an adsorbate. The framework integrates a comprehensive toolset including density functional theory (DFT) calculations, cluster expansion, machine learning, and structure optimization. The end-to-end machine-learning workflow guides DFT data generation and enables significant computational acceleration. We demonstrate the approach for CO-adsorbed Pdn (n = 1–55) clusters on CeO 2 (111). Simulation results reveal that CO can facilitate restructuring by stabilizing smaller planar structures and bilayer structures of specific intermediate sizes, consistent with experimental reports. Metal–support interactions, preferential CO adsorption, and metal nuclearity and structure control catalyst stability. As a result, the framework allows automatic discovery of stable catalyst structures and a systematic strategy to exploit properties in the subnanometer scale.

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Modified Energy Span Analysis Reveals Heterogeneous Catalytic Kinetics

Mechanistic modeling is a cornerstone of catalyst development generally conducted with microkinetic models or density functional theory-based energy profiles. We extend the energy span model of homogeneous catalysis to heterogeneous systems by introducing the modified energy span analysis (MESA) model by implementing collision theory and gas-phase concentration effects. We determine analytically turnover frequencies, coverages, rate-determining steps, apparent activation energies, and reaction orders in agreement with microkinetic and kinetic Monte Carlo simulations. The model applies to discrete catalyst state systems, including single-atom catalysts, homogeneous systems, and microporous materials. A generalizable rate expression is derived for reactor modeling or mechanistic insights from solely experimentally measured reaction orders. Here, we illustrate MESA on three published mechanisms and reveal unexpected phenomena absent in traditional energy span profiles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride

Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. Finally, the application of the workflow to zinc telluride, a promising CO 2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.

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gRASPA

GPU Monte Carlo Simulation Code with a taste of RASPA We present enhancements in Monte Carlo simulation speed and functionality within an open-source code, gRASPA, which uses graphical processing units (GPUs) to achieve significant performance improvements compared to serial, CPU implementations of Monte Carlo. The code supports a wide range of Monte Carlo simulations, including canonical ensemble (NVT), grand canonical, NVT Gibbs, Widom test particle insertions, and continuous-fractional component Monte Carlo. Implementation of grand canonical transition matrix Monte Carlo (GC-TMMC) and a novel feature to allow different moves for the different components of metal-organic framework (MOF) structures exemplify the capabilities of gRASPA for precise free energy calculations and enhanced adsorption studies, respectively. The introduction of a High-Throughput Computing (HTC) mode permits many Monte Carlo simulations on a single GPU device for accelerated materials discovery. The code can incorporate machine learning (ML) potentials. The open-source nature of gRASPA promotes reproducibility and openness in science, and users may add features to the code and optimize it for their own purposes. The code is written in CUDA/C++ and SYCL/C++ to support different GPU vendors. The gRASPA code is publicly available at https://github.com/snurr-group/gRASPA.

Li, Zhao [Purdue/Northwestern/Notre Dame Universit↗

Theoretical Investigations on the Plasmon-Mediated Dissociation of Small Molecules in the Presence of Silver Atomic Wires

Plasmonic nanoparticles can promote bond activation in adsorbed molecules under relatively benign conditions via excitation of the nanoparticle’s plasmon resonance. As the plasmon resonance often falls within the visible light region, plasmonic nanomaterials are a promising class of catalysts. However, the exact mechanisms through which plasmonic nanoparticles activate the bonds of nearby molecules are still unclear. Herein, we evaluate Ag 8 –X 2 (X = N, H) model systems via real-time time-dependent density functional theory (RT-TDDFT), linear response time-dependent density functional theory (LR-TDDFT), and Ehrenfest dynamics in order to better understand the bond activation processes of N 2 and H 2 facilitated by the presence of the atomic silver wire under excitation at the plasmon resonance energies. We find that dissociation is possible for both small molecules at high electric field strength. Activation of each adsorbate is symmetry- and electric field-dependent, and H 2 activates at lower electric field strengths than N 2 . Furthermore, this work serves as a step toward understanding the complex time-dependent electron and electron–nuclear dynamics between plasmonic nanowires and adsorbed small molecules.

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Structure and Stability of Pristine and Carboxylate-Covered Anatase TiO 2 (001) in Aqueous Environment

The interactions of carboxylic acids and water with TiO 2 surfaces are important in applications ranging from solar cells to biomedical devices. Here we focus on the aqueous interface with the minority (001) surface of anatase TiO 2 (A-001) and the behavior of adsorbed formic and acetic acid monolayers at this interface. We investigated the structure and stability of the pristine reconstructed and formic/acetic acid covered A-001 surfaces in contact with water using density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations. The (1 × 4) reconstruction of the pristine surface is found to be stable in aqueous environment, within the time scale of our simulation. Here, carboxylic acids adsorb in deprotonated bidentate (BD) form on A-001, with the dissociated proton transferred to a surface oxygen to form a bridging hydroxyl. Of the two possible configurations, BD bridging and BD straddling, of the adsorbed species, the latter is found to rapidly transform to a monodentate structure during our simulations. Further investigation of mixed acetate–formate monolayers on A-001 in water indicates that also BD bridging species can become unstable at the boundaries between formate and acetate-covered regions, transforming to a monodentate form that does not prevent water adsorption on the TiO 2 surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative Study on the Machine Learning-Based Prediction of Adsorption Energies for Ring and Chain Species on Metal Catalyst Surfaces

Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.

Adsorption↗

Electrocatalytic Reduction of CO 2 to CO over Ag(110) and Cu(211) Modeled by Grand-Canonical Density Functional Theory

We report the results of modeling CO 2 reduction (CO 2 R) to CO over Ag(110) and Cu(211) surfaces at different applied potentials using grand-canonical density functional theory (GC-DFT), a method specifically designed to accurately model electrochemical systems. In addition to demonstrating GC-DFT’s ability to accurately model electrochemical processes, we also compare it with the computational hydrogen electrode (CHE) approach. GC-DFT predicts that the geometries of these reacting systems strongly depend on the applied potential and the Helmholtz free energies vary nonlinearly with the applied potential, which contradicts a central assumption of the CHE approach. The CHE approach neglects the change in the number of electrons on the electrode surface at different applied potentials, which reduces its accuracy as the potential changes from the potential of zero charge. Our results further demonstrate that the grand free energies of the reaction intermediates not only depend on the value of the applied potential but also on the metal surface type, adsorption site, and adsorbate. GC-DFT’s ability to predict the effect of the applied potential on adsorbate geometry enables it to evaluate different possible reaction mechanisms at different applied potentials. For instance, GC-DFT predicts that the first step of CO2R likely switches from proton-coupled electron transfer to sequential electron transfer and then proton transfer at more reducing potentials, a result that cannot be determined by the CHE because it assumes that all electron transfers are coupled to proton transfers and neglects the effect of the applied potential on the adsorbate geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NO Degradation on the Anatase TiO 2 (001) Surface in the Presence of Water

Nitric oxide (NO) is known to degrade to nitric acid (HNO 3 ) on anatase TiO2 facets under visible light irradiation in the presence of water. However, the exact role that water plays in this photoreaction is not fully understood. Here, by employing the density functional theory (DFT) and time-dependent density functional tight binding (TD-DFTB), we show the viability of two suggested degradation pathways involving water. Both reaction pathways are triggered by a charge transfer excitation from the NO molecule to the TiO 2 surface. In one of them, NO interacts with dissociated water molecules adsorbed on the surface to form HONO + , whereas for the second pathway, NO is oxidized to NO 2 + by capturing one oxygen atom from the substrate. Both HONO and NO 2 are known byproducts in the photodegradation of NO, which further react with adsorbed water to finally produce HNO 3 . We also demonstrate by means of nudged elastic band calculations that these reactions are unlikely to happen without illumination.

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