Creating Hyperthin Membranes for Gas Separations
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The separation of ethane (C 2 H 6 ) and ethylene (C 2 H 4 ) represents a crucial process for the production of polymer-grade C 2 H 4 , and adsorptive separation holds enormous promise for this industrially important but challenging task. Furthermore we report a new hydrogen-bonded organic frameworks (HIAM-102) with suitable channel and superhydrophobicity for preferential adsorption of C 2 H 6 over C 2 H 4 . HIAM-102 shows a C 2 H 6 /C 2 H 4 IAST selectivity of 1.9 and C 2 H 6 uptake of 48.25 cm 3 /g at 1 bar and 298 K. Benefitted from the hydrophobic pore surface, it can well-separate C 2 H 6 and C 2 H 4 under highly humid conditions as confirmed by experimental column breakthrough measurements. Computational calculations provide additional support for the experimental observations that the nonpolar channel of HIAM-102 interact favorably with C 2 H 6 over C 2 H 4 .
Cyclometalated and polypyridyl complexes of d6 metals are promising photoredox catalysts, using light to drive reactions with high kinetic or thermodynamic barriers via the generation of reactive radical intermediates. However, while tuning of their redox potentials, absorption energy, excited-state lifetime and quantum yield are well-known criteria for modifying activity, other factors could be important. Here we show that dynamic ion-pair reorganization controls the reactivity of a photoredox catalyst, [Ir[dF(CF3)ppy]2(dtbpy)]X. Time-resolved dielectric-loss experiments show how counter-ion identity influences excited-state charge distribution, evincing large differences in both the ground- and excited-state dipole moment depending on whether X is a small associating anion (PF6-) that forms a contact-ion pair versus a large one that either dissociates or forms a solvent-separated pair (BArF4-). These differences correlate with the reactivity of the photocatalyst toward both reductive and oxidative electron transfer, amounting to a 4-fold change in selectivity toward oxidation versus reduction. These results suggest that ion pairing could be an underappreciated factor that modulates reactivity in ionic photoredox catalysts.
Oxygen plasma treatment of polydimethylsiloxane (PDMS) induces an ultrathin polyorganosilica (POSi) layer (<10 nm) on top of a PDMS membrane, leading to excellent H 2 /gas separation properties and providing a rapid and scalable way to fabricate robust silica membranes compared with conventional high-temperature and time-consuming sol-gel methods. Here, we thoroughly investigate POSi membranes derived from poly (dimethylsiloxane-co-methylhydroxidesiloxane) (poly (DMS-co-MHOS)) containing -SiOH groups that can be more easily converted to silica networks than the -SiCH 3 in PDMS. Further, the effect of the polysiloxane structure and plasma treatment conditions (including plasma generating powers, oxygen flowrate, chamber pressure, and treatment time) on the silica chemistry, structure, and H 2 /CO 2 separation properties are systematically determined to derive structure/property relationships. An optimized membrane exhibits H 2 permeance of 880 GPU and H 2 /CO 2 selectivity of 67 at 150 °C, superior to state-of-the-art polymeric membranes. The membrane retains H 2 /CO 2 selectivity as high as 46 when challenged with simulated syngas containing 2.8 mol% water vapor at 150 °C, demonstrating the potential of these POSi membranes for practical applications.
Graphitic carbon nitride (C 3 N 4 ) has been widely explored as a photoactive support for single-atom catalysts (SACs). In this paper, three different π-rich aromatic dianhydrides are employed to introduce molecular quantized trap states into the conduction band of C 3 N 4 to facilitate efficient charge-separation and to promote an enhanced photocatalytic CO 2 reduction response. These modified C 3 N 4 materials have been characterized structurally and spectroscopically for use as the support for Co-based SACs. In photocatalytic CO 2 reduction studies, the Co SAC on naphthalene dianhydride doped C 3 N 4 exhibited the highest activity and selectivity towards CO production among the Co SACs tested in this work. The observed improvement in photocatalytic CO 2 -to-CO conversion activity correlates with trends in photoinduced charge separation, as revealed by photoluminescence spectroscopy.
Current extraction technologies for rare earth elements at ambient conditions are reagent and energy intensive, giving rise to significant quantities of secondary waste streams. Exploration of the removal of common cations from aqueous streams has been undertaken with carbon materials and have shown promising results. However, those promising materials have not been explored extensively for rare earth element capture from aqueous process streams. In this study, a carbon electrode was investigated for the adsorption and immobilization of REE elements from aqueous solutions. Cyclic voltammetry studies of the carbon electrode displayed a pseudocapacitive behavior where it was verified that cation adsorption is accompanied by an electron transfer process. Preliminary tests showed that a current density of 89.1 mA. g -1 , allowed for the pseudocapacitive adsorption (PSA) of Nd 3+ cation without the formation of rare earth hydroxides. Hence, the selective PSA of Nd 3+ was verified in an electrolyte solution with equimolar concentrations of Nd 3+ , Mg 2+ , Li + , Na + and K + , achieving separation factors of 8.6, 1.1, and 10.9 for Nd 3+ /Li + , Nd 3+ /Na + , and Nd 3+ /Mg 2+ , respectively. Analysis of the potential-time curves for the various cations suggests that storage of ions in the electrode involved pore-spacings rather than interlayer spacings and was corroborated by XRD analysis. Specific capacitance as high as >640 F.g -1 for Nd 3+ was also observed for the carbon electrode, with Faradaic efficiencies (FE) of > 20% for Nd 3+ and Mg 2+ , and > 9% for Na + . Furthermore, adsorption capacity of >125 mg g -1 after 4hrs of electrosorption was observed for Nd 3+ . In the presence of the Nd 3+ electrolyte, the electrode achieved increasing storage of Nd 3+ with >94% retention of Nd 3+ with a FE > 20% over 6 cycles between loading and releases in 1 M KCl solution. In conclusion, these preliminary results provide information and some guidance on the selective recovery of rare earth elements, such as Nd, in aqueous streams in the presence of competitive cations employing the use of carbon-based materials.
A collection of atomistic molecular simulations is reported that illustrate the impact of adsorption temperature on species uptake and adsorbate-induced structural rearrangement for amorphous polymers of intrinsic microporosity. Temperature-sensitive structural rearrangement is evaluated by contrasting two methods: standard grand canonical Monte Carlo simulations using a rigid framework approximation and a combined Monte Carlo/molecular dynamics approach that fully incorporates framework flexibility. We report single-component gas phase adsorption isotherms for CH 4 , C 2 H 4 , C 2 H 6 , C 3 H 6 , C 3 H 8 , and CO 2 across a temperature range of 250–400 K for models of an archetypal polymer of intrinsic microporosity, PIM-1. A quadratic model is presented that captures two main mechanisms of temperature-dependent adsorption-induced deformation of PIM-1 up to a relative swelling of 1.15: thermal expansion and an increased propensity to swell as a function of species uptake. Two case studies are reported that highlight the critical role of operating temperature in industrial storage and separation applications. The first study focuses on methane storage and delivery applications using a pressure–temperature swing adsorption application (PTSA). We demonstrate that larger working capacities are accompanied by increased volumetric strain between adsorption–desorption steps. The second case study considers PIM-1 as an adsorbent to separate an exemplar ternary syngas mixture at operating temperatures ranging 300–550 K. Here, a temperature threshold of ~400 K is identified, beyond which adsorption-induced PIM-1 swelling is negligible and the solubility selectivity-loading curve transitions to exhibiting a nearly linear relationship.
Rare-earth element separation processes often rely on a small decrease in ionic radii along the series of elements. Separation processes based on the distinct optical properties of REs remain less explored, although photochemical methods may offer a viable alternative. Accurate selection of the synthetic precursors of a photoswitchable acylhydrazonic ligand led to a system that could quantitatively isomerize (E−to−Z) upon irradiation with commercial LED lights. Coordination of the photoswitch with RE III nitrates (RE = La−Lu except Pm and Y) resulted in the retention of the photoswitching properties observed in solution. The lower binding affinity of the generated Z−isomer with RE III ions yielded the dissociation of the complexes upon irradiation (photodissociation) with the release of RE−nitrates in solution. The rate of the reaction was found to be dependent on the optical properties of the RE III ions, with nonemissive complexes (no 4f excited states) dissociating faster than emissive ones (having accessible 4f excited states). A thorough solid-state characterization of the complexes was performed by using crystallographic and photochemical methods. Ultimately, the accessibility of the 4f excited states of the metals following light irradiation and excitation of the ligand led to a decrease in the rate of the reaction due to quenching of the ligand excited state. These results demonstrate that the direct modulation of the metal coordination environment, combined with the metal-dependent reaction rate, could provide a strategy for the development of RE−separation processes based on differences in their optical properties.
Economically scalable carbon molecular sieve (CMS) hollow fiber membranes rely upon a tunable bimodal pore morphology to separate gas pairs using angstrom-level size discrimination. Freshly formed CMS membranes experience self-retarding physical aging, reflected by permeance losses and selectivity gains that stabilize over short times compared to the lifetime of the membrane. Self-retarding morphology rearrangements are of special interest here due to tightening of the largest size range of ultramicropores, thereby causing aging for polyimide-derived CMS. We report effects of such aging for two A/B penetrant pairs, C 3 H 6 /C 3 H 8 and CO 2 /CH 4 . These two pairs not only have different average sizes, $\overline{d}_{A/B}$, but also different size differences,Δd A/B , between the members in each pair. We focus primarily on the C 3 H 6 /C 3 H 8 pair, which is the most difficult of the two pairs to separate, and use some CO 2 /CH 4 results as a comparison case. We study CMS derived from 6FDA:BPDA-DAM (1:1) polyimide by pyrolysis at 550 °C, 600 °C and 650 °C. Here we suggest conditions and physical causes that expedite, retard or even suppress the aging process within CMS membranes. Finally, we suggest how analysis of CMS derived from other precursors and other penetrant pairs can be generalized by understanding the results for the 6FDA:BPDA-DAM (1:1) polyimide derived CMS.
Abstract Interfaces, the boundary that separates two or more chemical compositions and/or phases of matter, alters basic chemical and physical properties including the thermodynamics of selectivity, transition states, and pathways of chemical reactions, nucleation events and phase growth, and kinetic barriers and mechanisms for mass transport and heat transport. While progress has been made in advancing more interface‐sensitive experimental approaches, their interpretation requires new theoretical methods and models that in turn can further elaborate on the microscopic physics that make interfacial chemistry so unique compared to the bulk phase. In this review, we describe some of the most recent theoretical efforts in modeling interfaces, and what has been learned about the transport and chemical transformations that occur at the air–liquid and solid–liquid interfaces. This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Structure and Mechanism > Computational Materials Science Software > Quantum Chemistry Software > Simulation Methods
Ni and Co are critical elements needed for modern technologies, and a better understanding of the ability of Mg-based minerals to incorporate these elements would benefit strategy development for Ni and Co recovery from mafic and ultramafic deposits. Here, in this work, we performed density functional theory (DFT) calculations of Ni and Co incorporation in six potential products of the carbonation of mafic and ultramafic silicates: brucite (Mg(OH) 2 ), magnesite (MgCO 3 ), nesquehonite (MgCO 3 ⸱3H 2 O), lansfordite (MgCO 3 ⸱5H 2 O), artinite (Mg 2 CO 3 (OH) 2 ⸱3H 2 O), and hydromagnesite (Mg 5 (CO 3 ) 4 (OH) 2 ⸱4H 2 O). The DFT results were used in an ab initio thermodynamics framework to explore the pH 2 O–pCO 2 conditions at which the Mg-based minerals were predicted to be thermodynamically stable and to quantify the Gibbs free energy of Ni and Co substitution at Mg sites. Among the six Mg-based minerals, brucite and magnesite were predicted to have the lowest Ni and Co substitution free energy. An analysis of the effect of temperature indicated that, at low temperature (<100 K), brucite more readily accommodated Ni and Co, while, at higher temperature (>335 K), magnesite more favorably incorporated Ni and Co. Between 100 K and 335 K, Ni was predicted to preferentially substitute for Mg in brucite and Co for Mg in magnesite, thus leading to a driving force for separating Ni and Co in conditions where brucite and magnesite both form. Insights gained in this work could therefore help select experimental conditions that either promote or inhibit incorporation of these critical elements into Mg-based mineral phases.
We present an approach for quantitatively predicting the temperature-dependent single-component adsorption behavior of linear alkanes in silica and Na-exchanged cationic zeolites using machine learning (ML) models trained from extensive molecular simulations based on force fields with coupled cluster accuracy. A high-performing classification model was developed to distinguish between instances with negligible and non-negligible adsorption. Subsequently, two ML models were trained to predict the single-component adsorption loading and the heat of adsorption at any pressure at 300 K for any zeolite topology and silicon-to-aluminum ratio. The ML models were trained on International Zeolite Association (IZA) zeolites, and their transferability to hypothetical zeolites was successfully validated. We then expand the power of these predictions to adsorbed mixtures at arbitrary temperatures by integrating them with the Clausius–Clapeyron equation and ideal adsorbed solution theory (IAST). This approach was validated and then applied to a temperature swing adsorption separation process to demonstrate its practical utility. We demonstrate how predictions from this ML-enabled approach can allow the selection of high-performing materials that are then validated using detailed molecular simulations based on quantitatively accurate force fields.
Abstract Bioproduction of renewable chemicals is considered as an urgent solution for fossil energy crisis. However, despite tremendous efforts, it is still challenging to generate microbial strains that can produce target biochemical to high levels. Here, we report an example of biosynthesis of high-value and easy-recoverable derivatives built upon natural microbial pathways, leading to improvement in bioproduction efficiency. By leveraging pathways in solventogenic clostridia for co-producing acyl-CoAs, acids and alcohols as precursors, through rational screening for host strains and enzymes, systematic metabolic engineering-including elimination of putative prophages, we develop strains that can produce 20.3 g/L butyl acetate and 1.6 g/L butyl butyrate. Techno-economic analysis results suggest the economic competitiveness of our developed bioprocess. Our principles of selecting the most appropriate host for specific bioproduction and engineering microbial chassis to produce high-value and easy-separable end products may be applicable to other bioprocesses.
Ionic liquids (ILs) are promising solvents for the pretreatment of lignocellulosic biomass due to their ability to disrupt cellulose, hemicellulose, and lignin structures. However, large-scale implementation requires the development of efficient recovery and recycling methods. This review provides a comprehensive analysis of the recyclability potential of ILs used in biomass pretreatment, emphasizing their mechanisms, recent innovations, and ongoing challenges. We begin by discussing the structural diversity and tunability of ILs, which underlie their effectiveness in biomass deconstruction. The distinct roles of IL anions and cations in dissolving specific biomass components are systematically presented and compared. Advances in IL recycling techniques, including antisolvent precipitation methods, membrane separation, and distillation, are critically examined, with attention to how mechanistic insights can inform the design of more efficient and selective recovery strategies. Despite progress, significant challenges remain to scaling up IL-based biomass processing, including high cost, environmental concerns, and impact of biomass-derived impurities (e.g., lignin residues, sugars, proteins) on IL purity and functionality after reuse. We also review the applicability of different ILs based on life cycle assessments and techno-economic analyses. Lastly, we identify critical research gaps and propose future directions, including the design and development of next-generation ILs with improved recyclability, reduced toxicity, and enhanced economic viability for industrial-scale applications.
The production cross-section of a top quark in association with a W boson is measured using proton–proton collisions at √s = 8TeV. The dataset corresponds to an integrated luminosity of 20.2 fb –1 , and was collected in 2012 by the ATLAS detector at the Large Hadron Collider at CERN. The analysis is performed in the single-lepton channel. Events are selected by requiring one isolated lepton (electron or muon) and at least three jets. A neural network is trained to separate the tW signal from the dominant tt¯ background. The cross-section is extracted from a binned profile maximum-likelihood fit to a two-dimensional discriminant built from the neural-network output and the invariant mass of the hadronically decaying W boson. The measured cross-section is σ tW = 26 ± 7pb, in good agreement with the Standard Model expectation.
A search for charged Higgs bosons produced in vector boson fusion processes and decaying into vector bosons, using proton–proton collisions at √s = 13 TeV at the LHC, is reported. The data sample corresponds to an integrated luminosity of 137 fb -1 collected with the CMS detector. Events are selected by requiring two or three electrons or muons, moderate missing transverse momentum, and two jets with a large rapidity separation and a large dijet mass. No excess of events with respect to the standard model background predictions is observed. Model independent upper limits at 95% confidence level are reported on the product of the cross section and branching fraction for vector boson fusion production of charged Higgs bosons as a function of mass, from 200 to 3000GeV. The results are interpreted in the context of the Georgi–Machacek model.
This chapter aims to provide a comprehensive overview of metadata types that may be useful during system design, optimization, and automation. Metadata are grouped into three main categories: (a) metadata describing signal generation, (b) metadata describing signal quality, and (c) contextual information in the form of annotations. Each of these categories is introduced and explained in three separate sections. Importantly, this chapter mainly answers what is considered metadata. To a lesser degree, recommendations are made regarding the selection of metadata for long-term storage. Chapter 4 will explain where and how to store metadata. Chapters 5 and 6 explain how to collect certain metadata through dedicated sensor validation tests (Chapter 5) or algorithmic analysis (Chapter 6).