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Structure–Transport Relationships of Water–Organic Solvent Co-transport in Carbon Molecular Sieve (CMS) Membranes
We explore the effects of the carbon molecular sieve (CMS) microstructure on the separation performance and transport mechanism of water–organic mixtures. Specifically, we utilize PIM-1 dense films and integrally skinned asymmetric hollow fiber membranes as polymer precursors for the CMS materials. The PIM-1 membranes were pyrolyzed under several different pyrolysis atmospheres (argon, carbon dioxide, and diluted hydrogen gas) and at multiple pyrolysis temperatures. Detailed gas physisorption measurements reveal that membranes pyrolyzed under 4% H 2 and CO 2 had broadened ultramicropore distributions (pore diameter <7 Å) compared to Ar pyrolysis, and pyrolysis under CO 2 increased ultramicropore volume and broadened micropore distributions at increased pyrolysis temperatures. Gravimetric water and p-xylene sorption and diffusion measurements reveal that the PIM-1-derived CMS materials are more hydrophilic than other CMS materials that have been previously studied, which leads to sorption-diffusion estimations showing water-selective permeation. Water permeation in the vapor phase, pervaporation, and liquid-phase hydraulic permeation reveal that the isobaric permeation modes (vapor permeation and pervaporation) are reasonably well predicted by the sorption-diffusion model, whereas the hydraulic permeation mode is significantly underpredicted (>250×). Conversely, the permeation of p-xylene is well predicted by the sorption-diffusion model in all cases. The collection of pore size analysis, vapor sorption and diffusion, and permeation in different modalities creates a picture of a combined transport mechanism in which water–under high transmembrane pressures–permeates via a Poiseuille-style mechanism, whereas p-xylene solutes in the mixture permeate via sorption-diffusion.
Correction for “Structure–Transport Relationships of Water–Organic Solvent Co-transport in Carbon Molecular Sieve (CMS) Membranes”
There were two important typos identified in the reported units of water flux under reverse osmosis conditions.
Relationship among the Crystal Structure, Texture, and Macroscopic Properties of Tetragonal (Pb,La)(Zr,Ti)O 3 Ferroelectrics Investigated by In Situ High-Energy Synchrotron Diffraction
In situ diffraction investigations have played an important role in experimentally revealing the mechanism of piezoelectric and ferroelectric properties. In this study, a pure tetragonal ferroelectric ceramic of La-doped PbZr 0.5 Ti 0.5 O 3 (LaPZT50) was investigated to eliminate the complex influence of phase coexistence. The electric field evolutions of the crystal structure, domain switching, and lattice deformation of the tetragonal phase have been revealed by in situ high-energy synchrotron X-ray diffraction. Furthermore, we found that the crystal structure of LaPZT50 is quite stable, showing a negligible change in the Pb–O bond length, unit cell volume, and spontaneous polarization upon application of an in situ external electric field. Importantly, the maximum macroscopic polarization of tetragonal LaPZT50 is defined by the 111-oriented grains. As determined by the intensity difference, the switching of non-180° domains plays a more significant role in contributing to the macroscopic strain than lattice deformation. These results further imply that the phase coexistence around the morphotropic phase boundary facilitates domain wall motion in the tetragonal phase and improves the ferroelectric and piezoelectric properties.
Small-Molecule Models of Hydrogen-Evolving MX 2 (M = Mo, W; X = S, Se) Bulk Solids: Composition–Activity Relationships
Triangular metal chalcogenide clusters of the form [M 3 Q 7 L 3 ]An (M = Mo or W; Q = S or Se; L = i Bu 2 NCS 2 – , (CF 3 CH 2 ) 2 NCS 2 – , i Bu 2 NCSe 2 – , or i Bu 2 PS 2 – ; An = Cl – or I – ) have been investigated as molecular analogues of layered metal dichalcogenide (MX 2 ) H 2 -evolution catalysts. These clusters have been evaluated for their relative H 2 -evolving ability under a common photolysis protocol implementing [Ru(bpy) 3 ] 2+ as chromophore and Et 3 N as sacrificial electron donor. With M constant as Mo and with constant supporting ligand, clusters with an all-sulfide core enable greater H 2 -TON than clusters with an all-selenide core. A more active catalyst is produced by [Mo 3 S 7 (S 2 CN i Bu 2 ) 3 ] + I – than its W 3 analogue with the same core sulfide composition and supporting dithiocarbamate ligands. Dichalcogenocarbamate ligands provide more active catalysts than dialkyldithiophosphate ligated clusters, and within the dichalcogenocarbamate set, greater H 2 -turnovers correlate with more-electron-donating ligands (i.e., i Bu 2 NCS 2 – > (CF 3 CH 2 ) 2 NCS 2 – > i Bu 2 NCSe 2 – ). Cluster cations with Cl – as counteranion are very similar in activity H 2 -evolving levels to identical clusters with I – , ruling out any significant interfering effect by I – upon the electron transfer relay between Et 3 N and catalyst. In the aggregate, observations are consistent with a mechanism for H 2 evolution that involves reductive extrusion of H 2 from a metal hydride intermediate.
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.
Derivatives as Potent and Selective Pan-phosphatidylinositol 5-Phosphate 4-Kinase Inhibitors
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Discovery, Structure?Activity Relationships, and In Vivo Evaluation of Novel Aryl Amides as Brain Pe
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Structure?Activity Relationship of USP5 Inhibitors
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Synthesis, Optimization, and Structure?Activity Relationships of Imidazo[1,2-a]pyrimidines as Inhibi
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Structure–Activity Relationship Studies of Venglustat on NTMT1 Inhibition
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Structure–Activity Relationship of a Pyrrole Based Series of PfPKG Inhibitors as Anti-Malarials
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Multicomponent Synthesis, Binding Mode, and Structure?Activity Relationship of Selective Histone Dea
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