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At least 469 records · Page 26

Adsorption-based membranes for air separation using transition metal oxides

In this work, we use computational modeling to examine the viability of adsorption-based pore-flow membranes for separating gases when a purely size-based separation strategy is ineffective. Using molecular dynamics simulations of O 2 and N 2 , we model permeation through a nanoporous graphene membrane. Permeation is assumed to follow a five-step adsorption-based pathway, with desorption being the rate-limiting step. Using this model, we observe increased selectivity between O 2 and N 2 , resulting from increased adsorption energy differences. We explore the limits of this strategy, providing an initial set of constraints that need to be satisfied to allow for selectivity. Finally, we provide a preliminary exploration of some transition metal oxides that appear to satisfy those conditions. Using density functional theory calculations, we confirm that these oxides possess adsorption energies needed to operate as adsorption-based pore-flow membranes. These adsorption energies provide a suitable motivation to examine adsorption-based pore-flow membranes as a viable option for air separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Supramolecular assemblies of polybenzimidazole and aromatic polycarboxylic acids with superior mechanical and H 2 /CO 2 separation properties

Aromatic polycarboxylic acids complex with imidazoles, forming supramolecular assemblies. Herein, we demonstrate that polybenzimidazole (PBI) can be augmented by aromatic polycarboxylic acids, including phthalic acid (PA), trimesic acid (TMA), and pyromellitic acid (PMA), and the resulting supramolecular assemblies exhibit attractive H 2 /CO 2 separation performance for precombustion carbon capture. The acid doping decreases the free volume and gas permeability but increases H 2 /CO 2 selectivity, which can be correlated with the molar ratio of the protons to PBI repeating units in the assemblies. Increasing the temperature decreases the H 2 /CO 2 selectivity because of weakened interactions. When challenged with model gas mixtures, a supramolecular assembly based on TMA shows H 2 /CO 2 separation properties superior to state-of-the-art materials and above Robeson's upper bound. Furthermore, this study elucidates the fruitful harnessing of dynamic non-covalent bonds to design robust and highly selective membranes for industrial gas separations.

36 MATERIALS SCIENCE↗

Tuneable phase behaviour and glass transition via polymerization-induced phase separation in crosslinked step-growth polymers

We report once limited to chain-growth polymerizations, fine control over polymerization-induced phase separation (PIPS) has recently been demonstrated in rubber-toughened thermoset materials formed through step-growth polymerizations. The domain length scales of these thermoset materials can be elegantly tuned by utilizing a binary mixture of curing agents (CAs) that individually yield disparate morphologies. Importantly, varying the composition of the binary mixture affects characteristics of the materials such as glass transition temperature and tensile behavior. Here, we establish a full phase diagram of PIPS in a rubber-toughened epoxy system tuned by a binary CA mixture to provide a robust framework of phase behaviour. X-Ray scattering in situ and post-PIPS is employed to elucidate the PIPS mechanism whereby an initial polymerization-induced compositional fluctuation causes nanoscale phase separation of rubber and epoxy components prior to local chain crosslinking and potential macrophase separation. We further demonstrate the universality of this approach by alternatively employing binary epoxy or binary rubber mixtures to achieve broad variations in morphology and glass transitions.

59 BASIC BIOLOGICAL SCIENCES↗

Precisely segmented PEEK–ionene + ionic liquid composite membranes for CO 2 separation

Ionenes, polymers with ionic groups incorporated directly within the backbone are a highly versatile class of materials, although they have received much less attention than polyelectrolytes which have ionic groups pendant from the polymer backbone. By designing ionenes that incorporate robust properties of poly(ether ether ketone) (PEEK), we have achieved new imidazolium-containing PEEK–ionene architectures that create opportunities for enhanced CO 2 separation membranes. To achieve these materials, an new imidazole-functionalized PEEK oligomer (ImK(EEK) 2 KIm) was synthesized through facile and straightforward routes. This molecule was then polymerized via condensation reactions with two different aromatic (α,α'-dibromo-p-xylene) and aliphatic (dibromohexyl containing-bis(imidazolium)hexane dibromide salt) comonomers and exchanged with bistriflimide ([Tf 2 N]) anion to obtain two unique PEEK–ionenes containing distinct PEEK and ionic segments: p([ImK(EEK) 2 Im-p-xyl][Tf 2 N] 2 ) and p([ImK(EEK) 2 (ImC 6 ) 3 ][Tf 2 N] 4 ). While the neat PEEK–ionenes exhibited high molecular weight but were not able to form high-quality films, adding stoichiometric amounts of “free” IL (1-methyl-3-butylimidazolium bistriflimide, [C 4 mIm][Tf 2 N]), greatly improved the flexibility and processability of the resultant membranes. Further, the structure–property relationships of bulk PEEK–ionenes and corresponding composites were extensively characterized by different analytical techniques (thermogravimetric analysis, differential scanning calorimetry, X-ray diffraction, and solid-state NMR). In conclusion, the gas separation properties were investigated, with the PEEK–ionenes + IL composites exhibiting CO 2 permeabilities of 14–94 barrer and good CO 2 /N 2 permselectivities of 26–35, indicating that new designs of segmented ionenes and composites with ILs a promising material design strategy for developing gas separation membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Picolinate-based acyclic ligand for rare earth element extraction and separation

The rare earth elements (REEs) play an important role in many modern technologies, particularly those relevant to clean energy. Despite their increasing importance, obtaining them in elementally pure forms suitable for downstream applications is challenging due to their similar chemical properties. This problem has impeded efforts to efficiently and selectively extract them from end-of-life materials and electronic waste. Here, we report a cost-efficient acyclic picolinate-based chelator H 4 aapa. The REE stability constants (log K ML ) of this chelator were measured via pH potentiometric and UV-Visible spectrophotometric titrations, revealing it to preferably bind light over heavy REEs like many recently reported 18-membered macrocycles. Its REE complexes were characterized by X-ray crystallography and NMR spectroscopy, demonstrating that this chelator can attain different conformations. The unique properties of aapa were subsequently used to separate REEs via the dissolution of insoluble REE oxalate mixtures. This dissolution-based separation led to large separation factors, the most significant being that for the Ce 3+ /Lu 3+ pair (38.6) at pH 4. Leveraging the strong REE binding affinity of aapa, we further demonstrated this chelator can leach REEs from authentic end-of-life materials in the form of magnet waste and autocatalyst smelting (autocat) slag. With this approach, exposure of these materials to a 20 mM solution of aapa at neutral pH generates a metal-containing solution enriched in Nd 3+ and Dy 3+ by 56.9 wt% and 3.0 wt%, marking a 4-fold improvement over the use of 4 M HNO 3 .

Gao, Yangyang [University of California, Santa Bar↗

MUSE adaptive-optics spectroscopy confirms dual active galactic nuclei and strongly lensed systems at sub-arcsec separation

The novel Gaia multi peak (GMP) technique has proven to be able to successfully select dual and lensed active galactic nuclei (AGN) candidates at sub-arcsecond separations. Both populations are important because dual AGN represent one of the central, still largely untested, predictions of ΛCDM cosmology, and compact lensed AGN allow us to probe the central regions of the lensing galaxies. In this work, we present high-spatial-resolution spectroscopy of 12 GMP-selected systems. We used the adaptive-optics assisted integral-field spectrograph MUSE at the VLT to resolve each system and investigate the nature of each component. All targets show the presence of two components confirming the GMP selection. We classify 4 targets as dual AGN, 3 as lensed quasar candidates, and 5 as a chance alignment of a star and an AGN. With separations ranging from 0.30″ to 0.86″, these dual and lensed systems are among the most compact systems discovered to date at z > 0.5. This is the largest sample of distant dual AGN with sub-arcsecond separations ever presented in a single paper.

Scialpi, M. (ORCID:0009000651004986)↗

Photoinduced phase separation in the lead halides is a polaronic effect

We present a perspective on recent observations of the photoinduced phase separation of halides in multi-component lead-halide perovskites. The spontaneous phase separation of an initial homogeneous solid solution under steady-state illumination conditions is found experimentally to be reversible, stochastic, weakly dependent on morphology, yet strongly dependent on composition and thermodynamic state. Regions enriched in a specific halide species that form upon phase separation are self-limiting in size, pinned to specific compositions, and grow in number in proportion to the steady-state carrier concentration until saturation. These empirical observations of robustness rule out explanations based on specific defect structures and point to the local modulation of an existing miscibility phase transition in the presence of excess charge carriers. A model for rationalizing existing observations based on the coupling between composition, strain, and charge density fluctuations through the formation of polarons is reviewed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface photovoltage spectroscopy observes junctions and carrier separation in gallium nitride nanowire arrays for overall water-splitting

Gallium nitride (GaN) nanowire arrays on silicon are able to drive the overall water-splitting reaction with up to 3.3% solar-to-hydrogen efficiency. Photochemical charge separation is key to the operation of these devices, but details are difficult to observe experimentally because of the number of components and interfaces. Here, we use surface photovoltage spectroscopy to study charge transfer in i-, n-, and p-GaN nanowire arrays on n+ -Si wafers in the presence and absence of Rh/Cr 2 O 3 co-catalysts. The effect of the space charge layer and sub-bandgap defects on majority and minority carrier transport can be clearly observed, and estimates of the built-in potential of the junctions can be made. Transient illumination of the p-GaN/n + -Si junction generates up to -1.4 V surface photovoltage by carrier separation along the GaN nanowire axis. This process is central to the overall water-splitting function of the n + -Si/p-GaN/Rh/Cr 2 O 3 nanowire array. Overall, these results improve our understanding of photochemical charge transfer and separation in group III–V semiconductor nanostructures for the conversion of solar energy into fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulation of polymerization induced phase separation in model thermosets

Polymerization induced phase separation (PIPS) in a three component thermoset is studied using molecular dynamics simulations of a new coarse-grained thermoset model. The system includes two crosslinker molecules, which differ in their glass transition temperatures (T g ) and chain length and thus have the potential for phase separation. Here, one crosslinker has a high T g corresponding to a rubbery behavior, and simulations were performed for a short length (4 beads) and a long length (33 beads). The resin and other crosslinker have low T g . A coarse-grained model is developed with these features and with interaction parameters determined so that for either rubbery crosslinker length, the system is in the liquid state at the cure temperature. For sufficiently slow reaction rates, the long rubbery molecule exhibits PIPS into a bicontinuous array of nanoscale domains, but the short one does not, reproducing recent experimental results. The simulations demonstrate that the reaction rates must be slow enough to allow diffusion to yield phase separation. Particularly, the reaction rate corresponding to the secondary amine must be very slow, else the structure of crosslinked clusters and the substantially increased diffusion time will prevent PIPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate prediction of global-density-dependent range-separation parameters based on machine learning

In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0−1 and only five systems (0.07%) with an absolute error larger than 0.01 a0−1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.

Chemistry↗

TDP-43 α-helical structure tunes liquid–liquid phase separation and function

Liquid–liquid phase separation (LLPS) is involved in the formation of membraneless organelles (MLOs) associated with RNA processing. The RNA-binding protein TDP-43 is present in several MLOs, undergoes LLPS, and has been linked to the pathogenesis of amyotrophic lateral sclerosis (ALS). While some ALS-associated mutations in TDP-43 disrupt self-interaction and function, here we show that designed single mutations can enhance TDP-43 assembly and function via modulating helical structure. Using molecular simulation and NMR spectroscopy, we observe large structural changes upon dimerization of TDP-43. Two conserved glycine residues (G335 and G338) are potent inhibitors of helical extension and helix–helix interaction, which are removed in part by variants at these positions, including the ALS-associated G335D. Substitution to helix-enhancing alanine at either of these positions dramatically enhances phase separation in vitro and decreases fluidity of phase-separated TDP-43 reporter compartments in cells. Furthermore, G335A increases TDP-43 splicing function in a minigene assay. Therefore, the TDP-43 helical region serves as a short but uniquely tunable module where application of biophysical principles can precisely control assembly and function in cellular and synthetic biology applications of LLPS.

60 APPLIED LIFE SCIENCES↗

Anomalous phase separation in a correlated electron system: Machine-learning–enabled large-scale kinetic Monte Carlo simulations

Significance Phase separation is crucial to the functionalities of many correlated electron materials with notable examples including colossal magnetoresistance in manganites and high- T c superconductivity in cuprates. However, the nonequilibrium phase-separation dynamics in such systems are poorly understood theoretically, partly because the required multiscale modeling is computationally very demanding. With the aid of machine-learning methods, we have achieved large-scale dynamical simulations in a representative correlated electron system. We observe an unusual relaxation process that is beyond the framework of classical phase-ordering theories. We also uncover a correlation-induced freezing behavior, which could be a generic feature of phase separation in correlated electron systems.

Zhang, Sheng↗

Mechanical theory of nonequilibrium coexistence and motility-induced phase separation

Nonequilibrium phase transitions are routinely observed in both natural and synthetic systems. The ubiquity of these transitions highlights the conspicuous absence of a general theory of phase coexistence that is broadly applicable to both nonequilibrium and equilibrium systems. Here, in this study, we present a general mechanical theory for phase separation rooted in ideas explored nearly a half-century ago in the study of inhomogeneous fluids. The core idea is that the mechanical forces within the interface separating two coexisting phases uniquely determine coexistence criteria, regardless of whether a system is in equilibrium or not. We demonstrate the power and utility of this theory by applying it to active Brownian particles, predicting a quantitative phase diagram for motility-induced phase separation in both two and three dimensions. This formulation additionally allows for the prediction of novel interfacial phenomena, such as an increasing interface width while moving deeper into the two-phase region, a uniquely nonequilibrium effect confirmed by computer simulations. The self-consistent determination of bulk phase behavior and interfacial phenomena offered by this mechanical perspective provide a concrete path forward toward a general theory for nonequilibrium phase transitions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Phase separation and ripening in a viscoelastic gel

The process of phase separation in elastic solids and viscous fluids is of fundamental importance to the stability and function of soft materials. We explore the dynamics of phase separation and domain growth in a viscoelastic material such as a polymer gel. Using analytical theory and Monte Carlo simulations, we report a domain growth regime in which the domain size increases algebraically with a ripening exponent α that depends on the viscoelastic properties of the material. For a prototypical Maxwell material, we obtain α = 1 , which is markedly different from the well-known Ostwald ripening process with α = 1 / 3 . We generalize our theory to systems with arbitrary power-law relaxation behavior and discuss our findings in the context of the long-term stability of materials as well as recent experimental results on phase separation in cross-linked networks and cytoskeleton.

Science & Technology - Other Topics↗

Separability of microtearing mode and electron temperature gradient turbulence regimes

The separability of microtearing mode (MTM)-dominated and electron temperature gradient (ETG)-driven turbulence regimes is studied with multiscale nonlinear gyrokinetic simulations. The simulations are based on National Spherical Torus Experiment-like, high-confinement mode pedestal parameters, where electromagnetic perturbations are large. Linear analysis indicates a wide scale-separation between the MTM and ETG modes in binormal wavenumber space (perpendicular to the magnetic field line), with no unstable modes at intermediate scales. Likewise, single-scale nonlinear analyses, retaining ion-only or electron-only spatio-temporal scales, produce seemingly well-converged transport states. Surprisingly, the multiscale simulation, which contains both the ion and electron scales, closely follows the transport from the electron-scale simulation. This trend is robust over a wide range of electron temperature gradient. Remarkably, compared to ion-scale simulations, MTM turbulence is significantly reduced at multiscale resolution even when ETG turbulence is low. In this case, traditional ion-scale resolution overestimates the electron energy flux, and it is not possible to accurately simulate the MTM turbulence with separable ion-scale simulations. Here, while the analysis confirms the validity of electron-scale simulations for predicting the electron transport, it also indicates that multiscale simulation may be required for reproducing the turbulence spectrum for systems with coupled MTM-ETG turbulence.

H-mode↗

A Morphological Model to Separate Resolved–Unresolved Sources in the DESI Legacy Surveys: Application in the LS4 Alert Stream

Separating resolved and unresolved sources in large imaging surveys is a fundamental step to enable downstream science, such as searching for extragalactic transients in wide-field time-domain surveys. Here we present our method to effectively separate point sources from the resolved, extended sources in the Dark Energy Spectroscopic Instrument (DESI) Legacy Surveys (LS). We develop a supervised machine learning model based on the Gradient Boosting algorithm XGBoost. The features input to the model are purely morphological and are derived from the tabulated LS data products. We train the model using ∼2 × 10 5 LS sources in the COSMOS field with HST morphological labels and evaluate the model performance on LS sources with spectroscopic classification from the DESI Data Release 1 (∼2 × 10 7 objects) and the Sloan Digital Sky Survey Data Release 17 (∼3 × 10 6 objects), as well as on ∼2 × 10 8 Gaia stars. A significant fraction of LS sources are not observed in every LS filter, and we therefore build a “Hybrid” model as a linear combination of two XGBoost models, each containing features combining aperture flux measurements from the “blue” (gr) and “red” (iz) filters. The Hybrid model shows a reasonable balance between sensitivity and robustness, and achieves higher accuracy and flexibility compared to the LS morphological typing. With the Hybrid model, we provide classification scores for ∼3 × 10 9 LS sources, making this the largest ever machine learning catalog separating resolved and unresolved sources. The catalog has been incorporated into the real-time pipeline of the La Silla Schmidt Southern Survey (LS4), enabling the identification of extragalactic transients within the LS4 alert stream.

astrostatistics↗

Revisiting separation: Algorithms and complexity

Abstract Linear temporal logic (LTL) with Since and Until modalities is expressively equivalent, over the class of complete linear orders, to a fragment of first-order logic known as FOMLO (first-order monadic logic of order). It turns out that LTL, under some basic assumptions, is expressively complete if and only if it has the property, called separation, that every formula is equivalent to a Boolean combination of formulas that each refer only to the past, present or future. Herein we present simple algorithms and their implementations to perform separation of the LTL with Since and Until, over discrete and complete linear orders, and translation from FOMLO formulas into equivalent temporal logic formulas. We additionally show that the separation of a certain fragment of LTL results in at most a double exponential size growth.

Oliveira, Daniel↗

A novel CMB component separation method: hierarchical generalized morphological component analysis

ABSTRACT We present a novel technique for cosmic microwave background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to generalized morphological component analysis (GMCA), we introduce hierarchical GMCA (HGMCA), a Bayesian hierarchical graphical model for source separation. We test our method on Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25{{\ \rm per\ cent}}$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the 0.02–0.03 per cent level at ℓ > 200 (and $\lt 0.26{{\ \rm per\ cent}}$ for all ℓ), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art internal linear combination type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.

79 ASTRONOMY AND ASTROPHYSICS↗