Do Residual Solvent Molecules Always Hinder Gas Sorption in Metal–Organic Frameworks?

The nature and magnitude of effects of residual solvent on gas uptake and selectivity in metal–organic frameworks (MOFs) have been systematically studied using high-throughput Monte Carlo simulations in the Grand Canonical ensemble. We focus on the uptake and separation of the essential CO2 and CH4 gases, which are pertinent to biogas upgrading and other common industrial processes and represent distinct types of interaction with the host MOF structures. We demonstrate that in circumstances where the residual solvent has a significant effect, CO2 uptake and selectivity in a curated data set of MOFs are likely to be affected negatively by its presence, while CH4 uptake may be affected either positively or negatively with a preference for positive effects. Both negative and positive residual solvent effects become greater at a higher pressure. Chemical, physical, and geometrical origins of the residual solvent effect have also been discussed. The relationship between various geometrical properties of MOFs and the extent of the residual solvent effect has been assessed, showing the greatest impact on MOFs with a pore diameter of around 5 Å. These results inform whether the presence of residual solvent is likely to be useful or detrimental in a MOF for a given application

Machine learning insights into predicting biogas separation in metal-organic frameworks

Breakthroughs in efficient use of biogas fuel depend on successful separation of carbon dioxide/methane streams and identification of appropriate separation materials. In this work, machine learning models are trained to predict biogas separation properties of metal-organic frameworks (MOFs). Training data are obtained using grand canonical Monte Carlo simulations of experimental MOFs which have been carefully curated to ensure data quality and structural viability. The models show excellent performance in predicting gas uptake and classifying MOFs according to the trade-off between gas uptake and selectivity, with R2 values consistently above 0.9 for the validation set. We make prospective predictions on an independent external set of hypothetical MOFs, and examine these predictions in comparison to the results of grand canonical Monte Carlo calculations. The best-performing trained models correctly filter out over 90% of low-performing unseen MOFs, illustrating their applicability to other MOF datasets

Understanding the Electron Beam Resilience of Two-Dimensional Conjugated Metal–Organic Frameworks

Knowledge of the atomic structure of layer-stacked two-dimensional conjugated metal–organic frameworks (2D c-MOFs) is an essential prerequisite for establishing their structure–property correlation. For this, atomic resolution imaging is often the method of choice. In this paper, we gain a better understanding of the main properties contributing to the electron beam resilience and the achievable resolution in the high-resolution TEM images of 2D c-MOFs, which include chemical composition, density, and conductivity of the c-MOF structures. As a result, sub-angstrom resolution of 0.95 Å has been achieved for the most stable 2D c-MOF of the considered structures, Cu3(BHT) (BHT = benzenehexathiol), at an accelerating voltage of 80 kV in a spherical and chromatic aberration-corrected TEM. Complex damage mechanisms induced in Cu3(BHT) by the elastic interactions with the e-beam have been explained using detailed ab initio molecular dynamics calculations. Experimental and calculated knock-on damage thresholds are in good agreement

Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo

Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

Advanced computational modelling of metal organic frameworks and their performance

The performance of metal organic frameworks (MOFs) in applications relevant to modern technological challenges is assessed using selected computational modelling methods. This class of materials has gained significant attention in recent years thanks to its ability to display advanced properties, including high surface area and tunability. This work discusses MOFs and the computational techniques which may be used to obtain useful information about them in the context of modern advanced materials and methods. There are several areas to which MOFs may be applied, and much of the focus of this work is on their use for gas storage and separation. The ability of selected MOFs to perform the difficult separation of xenon and krypton is examined by modelling uptake of the two gases using grand canonical Monte Carlo (GCMC) simulations. Similar simulations are applied in a high-throughput manner to identify MOFs which may be promising for gas separations important to upgrading biogas fuel streams, considering both total gas uptake and appropriate selectivity. The results of these simulations are used to train machine learning models which may be used to make efficient predictions of biogas upgrading ability. Gas uptake in MOFs may be affected by a number of specifics relating to structure and conditions; an important example of this, the effect of residual solvent on uptake, is assessed via a high-throughput GCMC study. The ability to reliably obtain high-quality images of MOF structures and visualise the processes they undergo is highly desirable. Transmission electron microscopy is a route to achieve this, but can be hampered by electron beam damage. Beam damage in selected 2D MOFs is modelled and analysed using ab initio molecular dynamics. Additionally, a classical many-body potential is used to model energetic favourability of metal cluster geometries, and the performance of the potential carefully assessed. A part of the rich context of advanced materials in which MOFs sit, metal clusters are another class of materials for which behaviour under imaging electron radiation is important. Valuable conclusions may be drawn as a result of the computational modelling applied in this work. Several conclusions are discussed, including identification of MOFs which may be useful for relevant applications, identification of relationships between performance and other MOF properties, discussion of likely pathways for damage to materials, and discussion of the quality of different methods and models for particular applications

Advanced computational modelling of metal organic frameworks and their performance

The performance of metal organic frameworks (MOFs) in applications relevant to modern technological challenges is assessed using selected computational modelling methods. This class of materials has gained significant attention in recent years thanks to its ability to display advanced properties, including high surface area and tunability. This work discusses MOFs and the computational techniques which may be used to obtain useful information about them in the context of modern advanced materials and methods. There are several areas to which MOFs may be applied, and much of the focus of this work is on their use for gas storage and separation. The ability of selected MOFs to perform the difficult separation of xenon and krypton is examined by modelling uptake of the two gases using grand canonical Monte Carlo (GCMC) simulations. Similar simulations are applied in a high-throughput manner to identify MOFs which may be promising for gas separations important to upgrading biogas fuel streams, considering both total gas uptake and appropriate selectivity. The results of these simulations are used to train machine learning models which may be used to make efficient predictions of biogas upgrading ability. Gas uptake in MOFs may be affected by a number of specifics relating to structure and conditions; an important example of this, the effect of residual solvent on uptake, is assessed via a high-throughput GCMC study. The ability to reliably obtain high-quality images of MOF structures and visualise the processes they undergo is highly desirable. Transmission electron microscopy is a route to achieve this, but can be hampered by electron beam damage. Beam damage in selected 2D MOFs is modelled and analysed using ab initio molecular dynamics. Additionally, a classical many-body potential is used to model energetic favourability of metal cluster geometries, and the performance of the potential carefully assessed. A part of the rich context of advanced materials in which MOFs sit, metal clusters are another class of materials for which behaviour under imaging electron radiation is important. Valuable conclusions may be drawn as a result of the computational modelling applied in this work. Several conclusions are discussed, including identification of MOFs which may be useful for relevant applications, identification of relationships between performance and other MOF properties, discussion of likely pathways for damage to materials, and discussion of the quality of different methods and models for particular applications

Computational Predictions for Effective Separation of Xenon/Krypton Gas Mixtures in the MFM Family of Metal-Organic Frameworks

This study shows that a range of separation applications for the MFM family of metal-organic frameworks (MOFs) can be expanded to include effective separations of Xe/Kr binary gas mixtures. The MFM family of copper paddlewheel-based, isoreticular MOFs has shown previously an excellent performance for CO2/CH4 and CO2/N2 gas separations. The proposed new function aids the development of this MOF series into a multiuse functional material. Xe/Kr separation is a critical step in production of the noble gases from air and in revalorizing xenon isotopes produced by a nuclear reactor. A complete analysis of Xe and Kr uptake and selectivity is presented, which also includes predictions of binding affinity of the guest atoms

Fission gas released from molten salt reactor fuel:the case of noble gas short life radioisotopes for radiopharmaceutical application

The present study explores the potential of fission gas (Kr and Xe short life radioisotopes) released from a molten salt reactor, the separation of these noble gases using specific absorbents under well fixed conditions and the utilisation of these radioisotopes for radio-diagnostics. During operation, a molten salt reactor produces noble gas radioisotopes that bubble out from the liquid fuel and that can be sampled and treated for radiopharmaceutical applications including as tools for diagnostics using γ radioisotopes and/or potentially in radiotherapy for specific viral diseases using β− emitters. Among them 133Xe is currently used for lung diagnostics thanks to its 132.9 ​keV γ. The use of 85Kr for diagnostics is also examined. Its 514 ​keV γ could be used for scintigraphy. However 133Xe utilisation imply also its β− (Emean ​≈ ​100 ​keV) whose mean free pathway of 100 ​nm in biological tissue or in water is much smaller than the mean pathway of the 95Kr β−. Emphasis is placed on 133Xe because of its potential dual ability of imaging and as a suggested therapeutic tool of viral lung diseases

Exploring the feasibility of a clinical proton beam with an adaptive aperture for pre-clinical research

OBJECTIVE: To investigate whether the Mevion S250i with HYPERSCAN clinical proton system could be used for pre-clinical research with millimetric beams. METHODS: The nozzle of the proton beam line, consisting of an energy modulation system (EMS) and an adaptive aperture (AA), was modelled with the TOPAS Monte Carlo Simulation Toolkit. With the EMS, the 230 MeV beam nominal range can be decreased in multiples of 2.1 mm. Monte Carlo dose calculations were performed in a mouse lung tumour CT image. The AA allows fields as small as 5 x 1 mm(2) to be used for irradiation. The best plans to give 2 Gy to the tumour were derived from a set of discrete energies allowed by the EMS, different field sizes and beam directions. The final proton plans were compared to a precision photon irradiation plan. Treatment times were also assessed. RESULTS: Seven different proton beam plans were investigated, with a good coverage to the tumour (D95 > 1.95 Gy, D5 < 2.3 Gy) and with potentially less damage to the organs at risk than the photon plan. For very small fields and low energies, the number of protons arriving to the target drops to 1-3%, nevertheless the treatment times would be below 5 s. CONCLUSION: The proton plans made in this study, collimated by an AA, could be used for animal irradiation. ADVANCES IN KNOWLEDGE: This is one of the first study to demonstrate the feasibility of pre-clinical research with a clinical proton beam with an adaptive aperture used to create small fields