Gas Separation Membrane Module Modeling: A Comprehensive Review.

Membrane gas separation processes have been developed for diverse gas separation applications that include nitrogen production from air and CO capture from point sources. Membrane process design requires the development of stable and robust mathematical models that can accurately quantify the performance of the membrane modules used in the process. The literature related to modeling membrane gas separation modules and model use in membrane gas separation process simulators is reviewed in this paper.

Implementation of a Core-Shell Design Approach for Constructing MOFs for CO Capture.

Adsorption-based capture of CO from flue gas and from air requires materials that have a high affinity for CO and can resist water molecules that competitively bind to adsorption sites. Here, we present a core-shell metal-organic framework (MOF) design strategy where the core MOF is designed to selectively adsorb CO, and the shell MOF is designed to block HO diffusion into the core. To implement and test this strategy, we used the zirconium (Zr)-based UiO MOF platform because of its relative structural rigidity and chemical stability.

Designing optimal core-shell MOFs for direct air capture.

Metal-organic frameworks (MOFs), along with other novel adsorbents, are frequently proposed as candidate materials to selectively adsorb CO for carbon capture processes. However, adsorbents designed to strongly bind CO nearly always bind HO strongly (sometimes even more so). Given that water is present in significant quantities in the inlet streams of most carbon capture processes, a method that avoids HO competition for the CO binding sites would be technologically valuable.

Hollow Fiber Membrane Contactors for Post-Combustion Carbon Capture: A Review of Modeling Approaches.

Hollow fiber membrane contactors (HFMCs) can effectively separate CO2 from post-combustion flue gas by providing a high contact surface area between the flue gas and a liquid solvent. Accurate models of carbon capture HFMCs are necessary to understand the underlying transport processes and optimize HFMC designs. There are various methods for modeling HFMCs in 1D, 2D, or 3D.

Evaluating the Performance of Micro-Encapsulated CO Sorbents during CO Absorption and Regeneration Cycling.

We encapsulated six solvents with novel physical and chemical properties for CO sorption within gas-permeable polymer shells, creating Micro-Encapsulated CO Sorbents (MECS), to improve the CO absorption kinetics and handling of the solvents for postcombustion CO capture from flue gas. The solvents were sodium carbonate (NaCO) solution, uncatalyzed and with two different promoters, two ionic liquid (IL) solvents, and one CO-binding organic liquid (COBOL). We subjected each of the six MECS to multiple CO absorption and regeneration cycles and measured the working CO absorption capacity as a function of time to identify promising candidate MECS for large-scale carbon capture.

Assessment of NER solutions against the first and second CALBC Silver Standard Corpus.

Background: Competitions in text mining have been used to measure the performance of automatic text processing solutions against a manually annotated gold standard corpus (GSC). The preparation of the GSC is time-consuming and costly and the final corpus consists at the most of a few thousand documents annotated with a limited set of semantic groups. To overcome these shortcomings, the CALBC project partners (PPs) have produced a large-scale annotated biomedical corpus with four different semantic groups through the harmonisation of annotations from automatic text mining solutions, the first version of the Silver Standard Corpus (SSC-I).

Precise charm to strange mass ratio and light quark masses from full lattice QCD.

By using a single formalism to handle charm, strange, and light valence quarks in full lattice QCD for the first time, we are able to determine ratios of quark masses to 1%. For m(c)/m(s) we obtain 11.85(16), an order of magnitude more precise than the current PDG average.