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At least 217 records · Page 12

Towards the Flexibility of HVDC-Interconnected Systems: A Novel Emergency Freqeuncy Response Model

In this paper, we propose a novel multi-time scale emergency frequency response model by unlocking the flexibility of High Voltage Direct Current (HVDC) systems. Unlike assigning power ramping rates for FACTS to regulate frequency in traditional methods, this paper designs a step-change electromagnetic power frequency response (EPFR) scheme, by leveraging the temporal over/under DC voltage capability of HVDC. Wherein the Kullback-Leibler Divergence is adopted to convexify the modified swing equation after integrating the step-change power. Further, to avoid the complicated differential equations, we equivalently reformulate the duration limits of DC voltage deviation into the HVDC decreasing power ramping rates, which participate in the system primary frequency response. Finally, the new steady-state operation level of HVDC is involved with the secondary frequency response. As a result, an improved three-level algorithm is developed to solve the model, wherein the instant step-change, primary, and secondary frequency response are coordinated together. After applying the proposed frequency response scheme on the test system, the EPFR is validated to effectively provide the most instantaneous supports when faced with bulk power loss due to extreme contingencies, and the resilience is ensured within acceptable expenditures.

Jiang, Sufan↗

Modeling of the Advanced Test Reactor Using OpenMC, Cubit and Griffin

In the pursuit of the ability to perform multiphysics simulations of the Advanced Test Reactor, it is crucial to have a fast and highly accurate deterministic model. To achieve this, a contemporary two-step method is employed. The first step involves generating homogenized cross sections using OpenMC, a cutting-edge Monte Carlo neutron transport code. OpenMC offers excellent modular capabilities, allowing for easy component integration and flexibility in incorporating new designs into the model. The second step involves deterministic transport calculations, which are performed using Griffin, a reactor multiphysics application based on the Multiphysics Object-Oriented Simulation Environment. To ensure the accurate spatial resolution and assignment of material cross sections, a Cubit-generated mesh for the Advanced Test Reactor is utilized as an intermediate step between the OpenMC and Griffin models; Griffin utilizes the mesh for its finite element solution, while OpenMC material IDs are written to the mesh file to be used in Griffin material assignments. Additionally, a Python-based script converts the cross sections generated by OpenMC into the ISOXML format required by Griffin. Preliminary comparisons indicate good agreement between the neutron multiplication factors obtained from the standalone OpenMC model and the Griffin model, with differences of less than 50 pcm in the two-dimensional geometry configuration. However, in three-dimensional calculations, an unacceptably large error is found in the Griffin solution. Future work is planned to resolve this discrepancy.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Time-Resolved Probing of the Iodobenzene C-Band Using XUV-Induced Electron Transfer Dynamics

Time-resolved extreme ultraviolet spectroscopy was used to investigate photodissociation within the iodobenzene C-band. The carbon–iodine bond of iodobenzene was photolyzed at 200 nm, and the ensuing dynamics were probed at 10.3 nm (120 eV) over a 4 ps range. Two product channels were observed and subsequently isolated by using a global fitting method. Their onset times and energetics were assigned to distinct electron transfer dynamics initiated following site-selective ionization of the iodine photoproducts, enabling the electronic states of the phenyl fragments to be identified using a classical over-the-barrier model for electron transfer. In combination with previous theoretical work, this allowed the corresponding neutral photochemistry to be assigned to (1) dissociation via the 7B2, 8A2, and 8B1 states to give ground-state phenyl, Ph(X), and spin–orbit excited iodine and (2) dissociation through the 7A1 and 8B2 states to give excited-state phenyl, Ph(A), and ground-state iodine. The branching ratio was determined to be 87 ± 4% Ph(X) and 13 ± 4% Ph(A). Similarly, the corresponding amount of energy deposited into the internal phenyl modes in these channels was determined to be 44 ± 10 and 65 ± 21%, respectively, and upper bounds to the channel rise times were found to be 114 ± 6 and 310 ± 60 fs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Propagation of radio frequency waves through turbulent plasmas

The practical and economic viability of tokamak fusion reactors depends, in a significant way, on the efficiency of radio frequency (RF) waves to deliver energy and momentum to the plasma in the core of the reactor. The RF electromagnetic waves, excited by antenna structures placed near the wall of a tokamak, have to propagate through the turbulent edge plasma along their path to the core of the fusion device. In present day experiments, the radial width of the edge region and scrape-off layer is of the order of a few centimeters. In ITER, and in future fusion reactors, this width will be of the order of tens of centimeters. Any effects on RF waves due to plasma turbulence have to be properly understood in order to optimize the delivery of RF energy and momentum into the core. This paper is on a multi-pronged, theoretical and computational, approach that is being pursued to quantify the effect of edge plasma turbulence on the propagation of RF waves. The theoretical and analytical models are based on solutions of the Faraday-Ampere equation in a magnetized plasma and on the Kirchhoff tangent plane approximation. An effective medium approach has been developed so as to approximate the permittivity of a turbulent plasma by analytical expressions. The computations are being carried out with a newly developed code ScaRF that is based on the finite difference finite domain technique for solving Maxwell's equations. The plasma permittivity can be assigned as desired. The code is being used to validate the analytical and theoretical models and to evaluate their limitations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A machine-learning-driven data labeling pipeline for scientific analysis in MLExchange

This study introduces a novel labeling pipeline to accelerate the labeling process of scientific data sets by using artificial intelligence (AI)-guided tagging techniques. This pipeline includes a set of interconnected web-based graphical user interfaces (GUIs), where Data Clinic and MLCoach enable the preparation of machine learning (ML) models for data reduction and classification, respectively, while Label Maker is used for label assignment. Throughout this pipeline, data can be accessed through a direct connection to a file system or through Tiled for access through Hypertext Transfer Protocol (HTTP). Our experimental results present three use cases where this labeling pipeline has been instrumental for the study of large X-ray scattering data sets in the area of pattern recognition, the remote analysis of resonant soft X-ray scattering data and the fine-tuning process of foundation models. These use cases highlight the labeling capabilities of this pipeline, including the ability to label large data sets in a short period of time, to perform remote data analysis while minimizing data movement and to enhance the fine-tuning process of complex ML models with human involvement.

Chavez, Tanny (ORCID:0000000193172896)↗

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗

Development of a Griffin model of the advanced test reactor

In the pursuit of a higher fidelity deterministic simulation capability of the Advanced Test Reactor, it is important to have a fast yet accurate deterministic neutronics model. Here, to achieve this, we employed an advanced two-step method. The first step involves generating homogenized cross sections using OpenMC, a cutting-edge Monte Carlo neutron transport code. OpenMC offers excellent modular capabilities, allowing for easy component integration and flexibility in incorporating new designs into the model. The second step involves deterministic transport calculations, which are performed using Griffin, a reactor physics application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE). To ensure the accurate spatial resolution and assignment of material cross sections, a Cubit-generated mesh for the Advanced Test Reactor is utilized as an intermediate step between the OpenMC and Griffin models; Griffin utilizes the mesh for its finite element solution, while OpenMC material identifications are written to the mesh file to be used in Griffin material assignments. Additionally, a Python-based script converts the cross sections generated by OpenMC into the ISOXML format required by Griffin. Initial comparisons using the Griffin diffusion solver indicated good agreement between the neutron multiplication factors obtained from the standalone OpenMC model and the Griffin model, with differences of less than 10 pcm in the 2D geometry configuration; it was later determined that this agreement was likely due to compensating effect and was more likely on the order of –700 pcm relative to the OpenMC solution. However, in three-dimensional calculations, an unacceptably large error (almost 8,000 pcm) was found in the Griffin solution with the diffusion solver. Subsequent calculations using Griffin’s discrete ordinates solver demonstrated substantially improved agreement, within 116 pcm of the OpenMC solution used to generate the cross sections for Griffin. Building on this capability, future work will seek to perform more detailed validation calculations. The ultimate goal is to evaluate both transient and multiphysics simulations of the reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Autocorrelation and Multifractal Detrended Fluctuation Analyses Reveal Superdiffusive Mass Transport in Solvent-Filled Nanoporous Media

Fluorescence fluctuation spectroscopy experiments were conducted to better understand the complex mass transport dynamics of organic molecules in liquid-filled nanoporous media. Anodic aluminum oxide (AAO) membranes incorporating 10 and 20 nm diameter cylindrical pores were employed as model materials. Nile red (NR) dye was used as a fluorescent tracer. The dye was dissolved separately in ethanol and toluene at a concentration of 20 nM and used to fill the membrane nanopores. Confocal fluorescence microscopy was employed to capture photon intensity time series data reflecting apparent diffusion of the dye within the pores. Autocorrelation of these data revealed that NR diffusion within the membranes occurred over a broad range of time scales. The autocorrelation decays were fit to a model for one-dimensional diffusion incorporating both fast and slow components having apparent diffusion coefficients, D f and D s , differing by a factor of ∼100. The fast mechanism was attributed to hindered bulk-like diffusion in the central pore cavity, while slow diffusion likely involved absorption of the dye to the pore surfaces. Unfortunately, important evidence of diffusion anomalies is lost in the broad autocorrelation decays obtained. The method of multifractal detrended fluctuation analysis (MF-DFA) was applied to the same data as a means to overcome this limitation. MF-DFA revealed that time series acquired from within the nanopores were multifractal and exhibited evidence of anomalous superdiffusion, likely resulting from the participation of a desorption-mediated diffusion mechanism. Monte Carlo simulations of time series modeling desorption-mediated diffusion in cylindrical nanopores provided support for this assignment. Here, the new knowledge gained affords an improved understanding of hydrocarbon dynamics within nanoporous oil and gas shales.

Diffusion↗

Direct Evidence for a Sequential Electron Transfer–Proton Transfer Mechanism in the PCET Reduction of a Metal Hydroxide Catalyst

Here, the proton-coupled electron transfer (PCET) mechanism for the reaction M ox -OH + e − + H + → M red -OH 2 was de-termined through kinetic resolution of the independent electron transfer (ET) and proton transfer (PT) steps. The reaction of interest was triggered by visible light excitation of [Ru II (tpy)(bpy′)H 2 O] 2+ , Ru II -OH 2 , where tpy is 2,2′:6′,2″-terpyridine and bpy′ is 4,4′-diaminopropylsilatrane-2,2′-bipyridine, anchored to In 2 O 3 :Sn (ITO) thin films in aqueous solutions. Interfacial kinetics for the PCET reduction reaction were quantified by nanosecond transient absorption spectroscopy as a function of solution pH and applied potential. Data acquired from pH = 5-10 revealed a stepwise electron-transfer proton-transfer (ET-PT) mechanism, while kinetic measurements made below the pK a (Ru III -OH/OH 2 ) = 1.3 were used to study the analogous interfacial reaction where electron transfer was the only mechanistic step. Analysis of this data with a recently reported multi-channel kinetic model was used to construct a PCET zone diagram and supported the assignment of an ET-PT mechanism from pH = 5-10. Ultimately, this study represents a unique example amongst M ox -OH/M red -OH 2 reactivity where the protona-tion and oxidation state of the intermediate was kinetically and spectrally resolved to firmly establish the PCET mechanism.

Charge transfer↗

Spin-coupling topology in the copper hexamer compounds A 2 Cu 3 O(SO 4 ) 3 ( A =Na, K)

The compounds A 2 Cu 3 O(SO 4 ) 3 (A=Na,K) are characterized by copper hexamers that are weakly coupled to realize antiferromagnetic order below TN≈3K. They constitute quantum spin systems with S=1 triplet ground states. In this work, we investigated the energy-level splittings of the copper hexamers by inelastic neutron scattering experiments covering the entire range of the magnetic excitation spectra. Additionally, the observed transitions are governed by very unusual selection rules that we ascribe to the underlying spin-coupling topology. This is rationalized by model calculations that allow an unambiguous interpretation of the magnetic excitations concerning both the peak assignments and the nature of the spin-coupling parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Identification of new marker genes from plant single‐cell RNA‐seq data using interpretable machine learning methods

Summary An essential step in the analysis of single‐cell RNA sequencing data is to classify cells into specific cell types using marker genes. In this study, we have developed a machine learning pipeline called single‐cell predictive marker (SPmarker) to identify novel cell‐type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning models to select marker genes. We have demonstrated that our method can: assign cell types based on cells that were labelled using published methods; project cell types identified by trajectory analysis from one data set to other data sets; and assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, the new marker genes have more orthologous genes identifiable in the corresponding rice single‐cell clusters. The new root hair marker genes also include 172 genes with orthologs expressed in root hair cells in five non‐ Arabidopsis species, which expands the number of marker genes for this cell type by 35–154%. Our results represent a new approach to identifying cell‐type marker genes from scRNA‐seq data and pave the way for cross‐species mapping of scRNA‐seq data in plants.

54 ENVIRONMENTAL SCIENCES↗

1999 Puget Sound Household Travel Survey

The 1999 Puget Sound Household Travel Survey was conducted between July and November. NuStats Research and Consulting conducted the survey on behalf of the Puget Sound Regional Council. The purpose of the study was to provide data to continue developing and refining the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the Puget Sound region. The study area consists of King, Kitsap, Pierce, and Snohomish counties. The resultant dataset will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. The study had household members 16 years old or older keep track of travel for a 48-hour period. A total of 9,028 households were recruited to participate in the study. Of these, 6,000 households (66.5%) completed travel diaries, and the information was retrieved from all household members regardless of age. An “attitude” survey about transportation and land use issues was also mailed to household members 16 years old or older.

1Hz data↗

1998/99 Thurston County Household Travel Study

The survey was conducted under the auspices of the Thurston Regional Planning Council, and it was funded through a state grant awarded to Intercity Transit of Olympia, Washington. Data collection was from September 1998 through March 1999. The purpose of the study was to provide data for the continuing development and refinement of the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the southern Puget Sound region of Washington. The resultant data set will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. Participating households were assigned specific “travel days” to record their travel over a 48-hour period. A total of 2,465 households were recruited to participate in the study. Of these, 1,537 households completed travel diaries, and the information was retrieved from 3,653 household members regardless of age. Households member made 25,278 total trips during their 48-hour diary period.

1Hz data↗

Wild Isolates of Neurospora crassa Reveal Three Conidiophore Architectural Phenotypes

The vegetative life cycle in the model filamentous fungus, Neurospora crassa, relies on the development of conidiophores to produce new spores. Environmental, temporal, and genetic components of conidiophore development have been well characterized; however, little is known about their morphological variation. We explored conidiophore architectural variation in a natural population using a wild population collection of 21 strains from Louisiana, United States of America (USA). Our work reveals three novel architectural phenotypes, Wild Type, Bulky, and Wrap, and shows their maintenance throughout the duration of conidiophore development. Furthermore, we present a novel image-classifier using a convolutional neural network specifically developed to assign conidiophore architectural phenotypes in a high-throughput manner. To estimate an inheritance model for this discrete complex trait, crosses between strains of each phenotype were conducted, and conidiophores of subsequent progeny were characterized using the trained classifier. Our model suggests that conidiophore architecture is controlled by at least two genes and has a heritability of 0.23. Additionally, we quantified the number of conidia produced by each conidiophore type and their dispersion distance, suggesting that conidiophore architectural phenotype may impact N. crassa colonization capacity.

59 BASIC BIOLOGICAL SCIENCES↗

Improved $^{95}\mathrm{Mo}$ neutron resonance parameters and astrophysical reaction rates

We report improved 95 Mo neutron resonance parameters and reaction rates are important for nuclear astrophysics, testing nuclear models, and nuclear criticality safety. However, despite many previous neutron-capture and total cross-section measurements on this nuclide, there still is much room for improvement as well as several discrepancies. For example, there are very few firm resonance spin and parity assignments; average resonance parameters are available only for each parity, the currently recommended astrophysical reaction rate results in disagreements between stellar models and meteoric isotopic anomalies, and there are substantial disagreements in the neutron-capture cross section at low energies important for nuclear criticality safety. To obtain an improved set of neutron resonance parameters and astrophysical reaction rates for 95 Mo. High-resolution neutron-capture and transmission data were measured at the Oak Ridge Electron Linear Accelerator (ORELA) using highly isotopically enriched 95 Mo samples. The neutron-capture apparatus, data reduction, and analysis were improved so that information contained in the γ-ray cascade following neutron capture were used to assign resonance J π values. Following this, simultaneous analysis of the new neutron-capture and transmission data was used to obtain resonance energies, gamma widths, and neutron widths and their uncertainties to a maximum energy of 10 keV. Accurate neutron-capture cross sections also were obtained for the unresolved resonance region to a maximum energy of 500 keV and, together with the new resonance parameters, used to calculate the astrophysical reaction rates in the temperature range from 5 to 30 keV. A vastly improved set of 95Mo neutron resonance parameters and an astrophysical reaction rate accurate to about 3% were obtained. Firm J π assignments were determined for 261 of the 314 observed resonances. This is a very large improvement over the previously published 32 firm J π assignments for 108 resonances. Also, the number of resonances having both firm J π assignments and Γ γ values was increased by almost a factor of 24—from 11 to 261. Neutron- and total-radiation-width distributions and average resonance spacings, average total radiation widths, and neutron strength functions were obtained for the six different s- and p-wave possibilities. Parameters for the lowest s-wave resonance, which is most important for criticality benchmarks, were obtained with high accuracy. Simple modification of the neutron-capture apparatus and expansion and improvement of data analysis techniques led to a large increase in firm J π assignments for 95 Mo neutron resonances. The resulting astrophysical reaction rate is 20%–30% larger than the currently recommended rate at s-process temperatures, which should lead to better agreement between stellar models and meteoric isotopic anomalies. The neutron-capture cross section at low energies is substantially larger than recommended in the latest evaluation, which is problematical for criticality benchmarks. The average resonance spacing as a function of spin and parity is significantly different from current models. The total-radiation-width distributions are significantly broader than predicted by theory and show significant departures from the expected Gaussian shapes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Contaminant Migration Modeling to Support the In Situ Decommissioning of Hardened Nuclear Facilities - 20215

The decommissioning of hardened nuclear facilities provides a unique challenge in balancing current worker dose with exposure to future receptors and media. In situ decommissioning (ISD) is a cost-effective and safe option for the closure of such facilities but requires a detailed understanding of the threat that radioactive and hazardous constituents remaining in the facilities pose to groundwater and surrounding surface water. The Savannah River Site (SRS) extensively employs contaminant migration models within the decommissioning process to develop site-specific removal, grouting, and monitoring strategies in support of safe and effective final end states of nuclear facilities. This work discusses the use of contaminant migration modeling in the ISD process at SRS, including specific examples from the closure of P-Reactor and R-Reactor, Building 235-F, F-Canyon and F/H Laboratory Complex. Migration models developed during the closure of P-Reactor and R-Reactor were divided into four source areas: the reactor vessel, the process area, the disassembly basin, and the purification wing. Each source area was assigned a specific inventory and migration pathway and was then subject to varying hypothetical removal, capping, and grouting schemes. Modeling indicated that groundwater Maximum Concentration Limits (MCLs) might be exceeded if no action was taken for eleven and ten constituents of concern (COCs) at P-Reactor and R-Reactor, respectively. These exceedances could occur in as few as 200 to 500 years. Alternatively, the migration modeling demonstrated that the selected ISD actions reduced contaminant mobility which allowed for significant radioactive decay and resulted in fewer predicted exceedances of groundwater MCLs (five COCs for P-Reactor; eight COCs for R-Reactor). In response to the modeling results for P-Reactor and R-Reactor, effectiveness monitoring programs were developed to target contaminants, specific to each reactor, that may migrate to groundwater. Contaminant migration modeling also revealed that roof collapse was a large factor in the release of COCs to the environment, giving rise to roof improvements, and an inspection and vegetation control program to ensure roof stability over time. Contaminant migration modeling is also aiding in the closure planning for hardened facilities in F Area. Building 235-F housed the Actinide Billet Line, which produced Np-237 billets for irradiation in SRS reactors, and the Plutonium Fuel Form (PuFF) facility that produced Pu-238 heat sources for the space program. As a result of these missions, areas within Building 235-F contain considerable residual amounts of both Pu-238 and Np-237. Contaminant migration modeling of Building 235-F was originally performed in 2012 to identify the feasibility of ISD and the amount of radioactive material removal required to prevent the exceedance of groundwater MCLs. The original model indicated that a 60% reduction in the PuFF facility Pu-238 inventory could keep groundwater concentrations below standards, while Np-237 did not pose a threat to groundwater. However, updates to the model with an emphasis on source impact pathways revealed that, due to the orientation of the source areas relative to groundwater flow, no amount of reasonable removal of Pu-238 would keep groundwater concentrations below MCLs and that Np-237 could be a large contributor to localized MCL exceedances. With this insight, the refined 2019 model is being used to assist in the development of grouting plans specific to each facility source area, where bentonite may be utilized to slow the migration of Pu-238 and its daughter products from the PuFF facility and a reducing grout may decrease Np-237 transport by ensuring the nuclide remains in the less mobile +IV oxidation state. The beginning phases of contaminant migration modeling are underway for F-Canyon and associated facilities using lessons learned from the Reactors and Building 235-F. A contaminant migration pathway, similar to the pathway used for the reactor vessels, is being developed for the hot and warm canyons. The F-Canyon inventories are being spatially refined to identify specific and localized source zones, comparable to Building 235-F, that may impact groundwater. Contaminant migration modeling provides vital input within the ISD process, from facility investigation to post closure effectiveness monitoring, making it a valuable tool in the development of safe and effective end states for hardened nuclear facilities at SRS. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Improving gas adsorption modeling for MOFs by local calibration of Hubbard U parameters

While computational screening with density functional theory (DFT) is frequently employed for the screening of metal–organic frameworks (MOFs) for gas separation and storage, commonly applied generalized gradient approximations (GGAs) exhibit self-interaction errors, which hinder the predictions of adsorption energies. We investigate the Hubbard U parameter to augment DFT calculations for full periodic MOFs, targeting a more precise modeling of gas molecule–MOF interactions, specifically for N2, CO2, and O2. We introduce a calibration scheme for the U parameter, which is tailored for each MOF, by leveraging higher-level calculations on the secondary building unit (SBU) of the MOF. When applied to the full periodic MOF, the U parameter calibrated against hybrid HSE06 calculations of SBUs successfully reproduces hybrid-quality calculations of the adsorption energy of the periodic MOF. The mean absolute deviation of adsorption energies reduces from 0.13 eV for a standard GGA treatment to 0.06 eV with the calibrated U, demonstrating the utility of the calibration procedure when applied to the full MOF structure. Furthermore, attempting to use coupled cluster singles and doubles with perturbative triples calculations of isolated SBUs for this calibration procedure shows varying degrees of success in predicting the experimental heat of adsorption. It improves accuracy for N2 adsorption for cases of overbinding, whereas its impact on CO2 is minimal, and ambiguities in spin state assignment hinder consistent improvements of O2 adsorption. Our findings emphasize the limitations of cluster models and advocate the use of full periodic MOF systems with a calibrated U parameter, providing a more comprehensive understanding of gas adsorption in MOFs.

Chemistry↗