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At least 73 records · Page 4

Optimal production of Phanerochaete chrysosporium manganese peroxidases and Trametes sp. C30 laccase hybrid Lac131 in Aspergillus niger for lignin bioconversion

Background Incorporating the production of related ligninolytic enzymes into industrial filamentous fungus Aspergillus niger will enhance the bioconversion of lignocelluloses to various chemical products. Results In this study, transgenic expression of Phanerochaete chrysosporium manganese peroxidases (mnps) and Trametes sp. C30 laccase hybrid Lac131 (lac131) were examined and optimized in A. niger 11414 prtT∆ strain. Five mnps (mnp1, mnp2, mnp3, mnp4, and mnp5) and lac131 genes were expressed separately or in combination. The transgenic strain containing the entire mnp2 genomic coding sequence (gmnp2) exhibited the highest mnP activity among the five mnp over-expression strains in the modified minimal medium (mMM) with addition of 5 g/L bovine hemoglobin (bHg). We examined the effects of hemin and bHg on mnP production in the gmnp2 strain cultures and found that at least 1 g/L bHg was required, while hemin was not. Culture conditions for mnP production were further optimized for the gmnp2 strain and the highest mnP activities were detected in the cultures grown at 25 °C and 200 rpm with an initial pH of 4.5. Effects of soy protein, skim milk, and bovine serum albumin on mnP production were investigated; 5 g/L of soy proteins or skim milk had comparable effects to 2.5 g/L bHg, while cultures with bovine serum albumin had diminished mnP activity. Disruption of both prtT and vsm1 substantially augmented the mnP production and its activity reached 575 U/L. Trametes sp. C30 laccase hybrid lac131 was strongly expressed in either A. niger gmnp2 (1975 U/L) or 11414prtT∆ (3895 U/L) strain. Both mnP and laccase in the culture supernatants effectively decolorized selected phenolic compounds (dyes) and cleaved tagged model lignin dimers. Conclusion The mnP was successfully produced in A. niger by optimizing the culture conditions and host strain. Co-expression of all four mnp genes in the same expression host by multiplex CRISPR will lead to the mnP production reaching levels comparable to P. chrysosporium, while only requiring 36 h at 25 °C. The Lac131 activity in transgenic A. niger strain is 4- to 7-times higher than that in previous studies. Co-production of mnP and laccase in A. niger will enhance the lignin bioconversion efficiency.

Aspergillus niger↗

Nitrilotriacetamides: Nitric Acid and Water Extraction and Physicochemical Properties

Nitrilotriacetamides are an emerging class of extractants that have been identified as promising candidates for a variety of separation schemes. Systems incorporating these ligands are prone to third-phase formation at high loading, but this can be mitigated by increasing the alkyl chain length or adding a phase modifier (e.g., 1-octanol). In this work, the impacts of these modifications on HNO 3 extraction, H 2 O extraction, and physiochemical properties (interfacial tension, viscosity, and density) are examined. The studies show that ligand alkyl chain length has very little impact on HNO 3 and H 2 O extraction, whereas the addition of 10% octanol significantly increases extraction of both HNO 3 and H 2 O. Viscosity and interfacial ten-sion are impacted by HNO 3 concentration, alkyl chain length, and the presence of phase modifier but remain in a range that should be compatible with commonly used solvent contacting equipment. Additional studies of physiochemical properties at variable ligand concentration suggest that a change in aggregation occurs above approximately 10-50 mM ligand. Thermodynamic modeling of distribution ratios and spectroscopic studies aimed at understanding speciation in the presence of HNO 3 are also reported. Further, these experiments suggest that the first equivalent of extracted HNO 3 interacts with both the central amine and carbonyl groups of the ligand. The spectroscopic changes at higher HNO 3 concentrations are relatively minor, suggesting additional HNO 3 is associated in an outer-sphere manner

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulations of divertor designs that spatially separate power and particle exhaust using mid-leg divertor particle pumping

Predictive design modeling of a Dissipation-Focused Divertor for future operation in DIII-D reveals that increasing the poloidal distance of the pump duct entrance from the target surface along the low-field side divertor baffle increases neutral compression and modifies the spatial distribution of power dissipation. With a divertor pump located mid-leg between the target and the X-point, SOLPS-ITER boundary plasma simulations without drifts predict the formation of a dense neutral cloud near the target with > 30x higher neutral compression in detachment, a more stable detachment front located further from the target, and ~25% lower outer midplane separatrix density required for detachment onset, compared to a pump located in the scrape-off layer at the target surface. Up to 19 MW of power flowing into the divertors is modeled using the following two numerical implementations for particle pumping: a specified fraction of particles incident on variable wall sections of the plasma grid is removed from the computational domain (so-called albedo pumping), and a pump duct is modeled which includes dynamics of kinetic neutrals in the duct. The simulations show that the detachment front is located between the divertor target and the X-point and is relatively stable near the pump entrance, without a strong dependence on gas puff rate or injected power. The mid-leg pump design spatially separates the two primary functions of a divertor (power handling and particle exhaust), with the majority of power dissipation occurring near the target plate and particle exhaust taking place further upstream. The benefit of enhanced dissipation using mid-leg pumping comes at the cost of a higher outer midplane separatrix density for a given amount of particle injection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

$Ξ$ 𝑏 → $Ξ$ form factors from lattice QCD and standard-model predictions for $Ξ$ 𝑏 → $Ξ$⁢𝜇 + ⁢𝜇 − and $Ξ$ 𝑏 → $Ξ$⁢𝛾 decays

We present the first lattice QCD determination of the $Ξ$ 𝑏 → $Ξ$ vector, axial-vector, and tensor form factors, which are relevant for the theory of rare decays including $Ξ$ 𝑏 → $Ξ$⁢ℓ + ⁢ℓ − and $Ξ$ 𝑏 → $Ξ$⁢𝛾. The calculation is performed with 2+1 flavors of domain-wall fermions at three different lattice spacings and pion masses in the range from approximately 430 to 230 MeV. The bottom quark is implemented using an anisotropic clover action. Three-point functions with a wide range of source-sink separations and model averaging are used to extract the ground-state contributions. We fit the dependence of the form factors on the momentum transfer, the pion mass, and the lattice spacing using modified 𝑧 expansions that account for subthreshold branch cuts, and apply dispersive bounds and asymptotic behavior constraints to achieve controlled uncertainties in the full semileptonic kinematic region. Using our form factor results, we present standard model predictions for the $Ξ$$^{−}_{𝑏}$ → $Ξ$ − ⁢𝛾 and $Ξ$$^{−}_{𝑏}$ → $Ξ$ − ⁢𝜇 + ⁢𝜇 − branching fractions and two angular observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bridging Hydrological Ensemble Simulation and Learning Using Deep Neural Operators

Ensemble-based simulation and learning (ESnL) has long been used in hydrology for parameter inference, but computational demands of process-based ESnL can be quite high. To address this issue, we propose a deep neural operator learning approach. Neural operators are generic machine learning algorithms that can learn functional mappings between infinite-dimensional spaces, providing a highly flexible tool for scientific machine learning. Our approach is built upon DeepONet, a specific deep neural operator, and is designed to address several common problems in hydrology, namely, model parameter estimation, prediction at ungaged locations, and uncertainty quantification. Here we demonstrate the effectiveness of our DeepONet-based workflow using an existing large model ensemble created for an eastern U.S. watershed that is instrumented with 10 streamflow gages. Results suggest DeepONet achieves high efficiency in learning an ML surrogate model from the model ensemble, with the modified Kling-Gupta Efficiency exceeding 0.9 on holdout test sets. Parameter inference, carried out using the trained DeepONet surrogate model and genetic algorithm, also yields robust results. Additionally, we formulate and train a separate DeepONet model for physics-informed, seq-to-seq streamflow forecasting, which further reduces biases in the pre-trained DeepONet surrogate model. While this study focuses primarily on a single watershed, our approach is general and may be extended to enable learning from model ensembles across multiple basins or models. Thus, this research represents a significant contribution to the application of hybrid machine learning in hydrology.

54 ENVIRONMENTAL SCIENCES↗

Stabilizing a low temperature phase change material based on Glaubers salt

The aim of this research is to enhance the performance of Glauber's salt (sodium sulfate decahydrate, SSD) as a phase change material (PCM) for thermal energy storage applications, as well as for shipping of temperature-sensitive materials. The study investigates the effects of modifying SSD with potassium chloride (KCl) and ammonium chloride (NH 4 Cl) to achieve lower phase transition temperatures of between +6 °C and + 13 °C. Sodium polyacrylate (PAAS) is employed as a thickening agent to prevent phase separation, and borax is used as a nucleating agent to suppress supercooling. Various ratios of KCl:NH 4 Cl are tested, and the impact of PAAS concentration on phase segregation is explored. The results show that a 2 wt% concentration of PAAS effectively prevents phase separation. Samples with a KCl:NH 4 Cl ratio of 1:1.83 exhibit stable phase transition behavior and maintain latent heat values within the range of 130–140 J/g after 30 thermal cycles. Maintaining a total KCl and NH 4 Cl proportion of 10 wt% is crucial to achieve the desired lower melting temperature. As a result, the study highlights the significance of thermal cycling in improving the stability of the PCM. The optimized SSD-based eutectic PCM formulations hold promise for applications in the cold chain industry.

25 ENERGY STORAGE↗

Optically multiplexed neutron time-of-flight technique for inertial confinement fusion

Neutron time-of-flight (nTOF) detectors are crucial in diagnosing the performance of inertial confinement fusion (ICF) experiments, which implode targets of deuterium–tritium fuel to achieve thermonuclear conditions. These detectors utilize the fusion neutron energy spectrum to extract key measurements, including the hotspot ion temperature and fuel areal density. Previous work [Danly et al., Rev. Sci. Instrum. 94, 043502 (2023)] has demonstrated adding 1D spatial resolution to an nTOF-like detector using a neutron aperture and streak camera to measure the ion temperature profile of an ICF implosion. By contrast, the study presented herein explores modifying the 1D detector to use a fast photomultiplier tube (PMT) to validate the design of a 2D spatially resolved instrument based on reconstruction from 1D profiles. The modification would collect time-of-flight traces from separate scintillators in an imaging array with one PMT using optical fibers of varying lengths to time-multiplex the signals. This technique has been demonstrated in ride-along experiments on the OMEGA laser with 20 fiber-coupled scintillator channels connected to a Photek PMT210. Results provide constraints on the fiber lengths and PMT gating requirements to promote pulse fidelity throughout all channels. Calibration of the detector to fixed nTOFs can provide a preliminary estimate of the instrument response function (IRF), although measurement of the IRF is currently under way. These results suggest that nTOF signals can potentially be time-multiplexed with fibers so long as the design is strategic to mitigate signal-to-noise reduction, modal dispersion, and charge build-up in the PMT, which has implications beyond ion temperature imaging.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Analysis of Polarized Dust Emission Using Data from the First Flight of SPIDER

Using data from the first flight of Spider and from the Planck High Frequency Instrument, we probe the properties of polarized emission from interstellar dust in the Spider observing region. Component-separation algorithms operating in both the spatial and harmonic domains are applied to probe their consistency and to quantify modeling errors associated with their assumptions. Analyses of diffuse Galactic dust emission spanning the full Spider region demonstrate (i) a spectral energy distribution that is broadly consistent with a modified-blackbody (MBB) model with a spectral index of β d = 1.45 ± 0.05 (1.47 ± 0.06) for E (B)-mode polarization, slightly lower than that reported by Planck for the full sky; (ii) an angular power spectrum broadly consistent with a power law; and (iii) no significant detection of line-of-sight polarization decorrelation. Tests of several modeling uncertainties find only a modest impact (~10% in σ r ) on Spider's sensitivity to the cosmological tensor-to-scalar ratio. The size of the Spider region further allows for a statistically meaningful analysis of the variation in foreground properties within it. Assuming a fixed dust temperature T d = 19.6 K, an analysis of two independent subregions of that field results in inferred values of β d = 1.52 ± 0.06 and β d = 1.09 ± 0.09, which are inconsistent at the 3.9σ level. Furthermore, a joint analysis of Spider and Planck 217 and 353 GHz data within one subregion is inconsistent with a simple MBB at more than 3σ, assuming a common morphology of polarized dust emission over the full range of frequencies. This evidence of variation may inform the component-separation approaches of future cosmic microwave background polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Leptodermic corrections to the TOV equations and nuclear astrophysics within the effective surface approximation

The macroscopic model for a neutron star (NS) as a liquid drop at the equilibrium is used to extend the Tolman-Oppenheimer-Volkoff (TOV) equations taking into account the gradient terms responsible for the system surface. The parameters of the Schwarzschild metric in the spherical case are found with these surface corrections to the known leading (zero) order of the leptodermic approximation a/R << 1, where a is the NS effective-surface (ES) thickness, and R is the effective NS radius. The energy density $\mathscr{E}$ is considered in a general form including the functions of the particle number density and of its gradient terms. The macroscopic gravitational component $Φ$(ρ) of the energy density is taken into account in the simplest form as expansion in powers of $ρ$ – $\overline{ρ}$, where $\overline{ρ}$ is the saturation density, up to second order, in terms of its contributions to the separation particle energy and incompressibility. Density distributions ρ across the NS ES in the normal direction to the ES, which are derived in the simple analytical form at the same leading approximation, was used for the derivation of the modified TOV (MTOV) equations by accounting for their NS surface corrections. As a result, the MTOV equations are analytically solved at first order and the results are compared with the standard TOV approach of the zero order.

Magner, A. G. [Institute for Nuclear Research, Kyi↗

Hydrogen-Steam Separation Using Mechanical Vapor Recompression Cycle

Solar thermochemical hydrogen and fuel production is a promising pathways for producing sustainable fuels and chemicals. One of the main challenges in the development of these systems is their low steam conversion extent, dictated by its restrictive thermodynamics requiring extremely high temperatures and low oxygen partial pressure to obtain conversions over 10 \%. While condensing the unreacted steam is technically simple, the latent heat is thus lost, which can be larger than the producd hydrogen higher heating value. We propose to use a modified mechanical vapor recompression cycle, allowing to recover the latent heat by compressing the steam-hydrogen mixture prior to the condensation process, thus creating a temperature different between the hot exhaust and cold inlet streams. We show that this method can recover over 90 % of the latent heat, thus increasing the viability of solar thermochemical hydrogen production cycles even under limited conversion conditions.

hydrogen technology↗

Characterization of a SiPM-based monolithic neutron scatter camera using dark counts

The Single Volume Scatter Camera (SVSC) Collaboration aims to develop portable neutron imaging systems for a variety of applications in nuclear non-proliferation. Conventional double-scatter neutron imagers are composed of several separate detector volumes organized in at least two planes. A neutron must scatter in two of these detector volumes for its initial trajectory to be reconstructed. As such, these systems typically have a large footprint and poor geometric efficiency. We report on the design and characterization of a prototype monolithic neutron scatter camera that is intended to significantly improve upon the geometrical shortcomings of conventional neutron cameras. The detector consists of a 50 mm×56 mm× 60 mm monolithic block of EJ-204 plastic scintillator instrumented on two faces with arrays of 64 Hamamatsu S13360-6075PE silicon photomultipliers (SiPMs). The electronic crosstalk is limited to < 5% between adjacent channels and < 0.1% between all other channel pairs. SiPMs introduce a significantly elevated dark count rate over PMTs, as well as correlated noise from after-pulsing and optical crosstalk. In this article, we characterize the dark count rate and optical crosstalk and present a modified event reconstruction likelihood function that accounts for them. We find that the average dark count rate per SiPM is 4.3 MHz with a standard deviation of 1.5 MHz among devices. The analysis method we employ to measure internal optical crosstalk also naturally yields the mean and width of the single-electron pulse height. Here, we calculate separate contributions to the width of the single-electron pulse-height from electronic noise and avalanche fluctuations. We demonstrate a timing resolution for a single-photon pulse to be (128 ± 4) ps. Finally, coincidence analysis is employed to measure external (pixel-to-pixel) optical crosstalk. We present a map of the average external crosstalk probability between 2×4 groups of SiPMs, as well as the in-situ timing characteristics extracted from the coincidence analysis. Further work is needed to characterize the performance of the camera at reconstructing single- and double-site interactions, as well as image reconstruction.

47 OTHER INSTRUMENTATION↗

In situ oxidation of reduced graphene oxide membranes by peracetic acid for dye desalination

Graphene oxide (GO) membranes with tunable interlayer spacings are of interest for dye removal from salty textile wastewater, and the membranes are often reduced to improve their stability, which inevitably lowers water permeance. Herein, we demonstrate that reduced GO (rGO) membranes can be facilely modified using peracetic acid (PAA) in situ to dramatically enhance water permeance while retaining dye rejection. Specifically, PAA-modified membranes (PrGO) are synthesized by vacuum-filtering hydrazine-reduced rGO nanosheets onto Nylon substrate and then exposing them to PAA solutions. The effects of the rGO layer thickness, PAA content, and PAA exposure time on the membrane chemistry, nanostructures, and salt/dye separation properties are thoroughly examined. For example, the PAA oxidation of a 100 nm-thick rGO membrane for 10 min increases water permeance by 180 %, from 35 to 93 Liter m −2 h −1 bar −1 , and decreases Na 2 SO 4 rejection from 10 % to 3.3 % while retaining the rejection of Congo red at ≈99.7 %. The PrGO membranes exhibit stable water permeance and >99 % dye rejection in multi-cycle tests in a crossflow system, surpassing state-of-the-art GO membranes and showcasing their potential for practical applications.

Dye desalination↗

A novel conditional formulation of the Vlasov–Ampère equations: a conservative, positivity, asymptotic and Gauss law preserving scheme

We propose a novel reformulation of the Vlasov–Ampère equations for plasmas that reveals discrete symmetries that enables simultaneous conservation of mass, momentum and energy; preservation of Gauss’s law; positivity of the distribution function; and consistency with quasi-neutral asymptotics. The approach employs variable and coordinate transformations to yield a coupled system comprising a modified Vlasov equation and associated moment–field equations. The modified Vlasov equation advances a conditional distribution function that excludes mass, momentum and energy densities, which are instead evolved through moment equations enforcing the relevant symmetries, conservation laws and involution constraints. This reformulation aligns naturally with a recent slow-manifold reduction technique, which separates fast electron time scales and simplifies the treatment of the quasi-neutral limit within the reduced moment–field subsystem. Using this framework, we develop a numerical method for the reduced 1D1V subsystem that, for the first time in the literature, satisfies all key physical constraints while maintaining a quasi-neutral asymptotic behaviour. The advantages of the method are demonstrated on canonical electrostatic test problems, including the multiscale ion acoustic shock wave.

1D1V↗

Mesh-based super-resolution of fluid flows with multiscale graph neural networks

A graph neural network (GNN) approach is introduced in this work which enables mesh-based three-dimensional super-resolution of fluid flows. In this framework, the GNN is designed to operate not on the full mesh-based field at once, but on localized meshes of elements (or cells) directly. To facilitate mesh-based GNN representations in a manner similar to spectral (or finite) element discretizations, a baseline GNN layer (termed a message passing layer, which updates local node properties) is modified to account for synchronization of coincident graph nodes, rendering compatibility with commonly used element-based mesh connectivities. Furthermore, the architecture is multiscale in nature, and is comprised of a combination of coarse-scale and fine-scale message passing layer sequences (termed processors) separated by a graph unpooling layer. The coarse-scale processor embeds a query element (alongside a set number of neighboring coarse elements) into a single latent graph representation using coarse-scale synchronized message passing over the element neighborhood, and the fine-scale processor leverages additional message passing operations on this latent graph to correct for interpolation errors. Demonstration studies are performed using hexahedral mesh-based data from Taylor–Green Vortex and backward-facing step flow simulations at Reynolds numbers of 1600 and 3200. Through analysis of both global and local errors, the results ultimately show how the GNN is able to produce accurate super-resolved fields compared to targets in both coarse-scale and multiscale model configurations. Reconstruction errors for fixed architectures were found to increase in proportion to the Reynolds number. Geometry extrapolation studies on a separate cavity flow configuration show promising cross-mesh capabilities of the super-resolution strategy.

Backward-facing step↗

Connecting ground-state properties of 6 Li to each other and to scattering data

We examine the relationship between the asymptotic normalization coefficient (ANC) of 6 Li and other low-energy observables in the α–deuteron system. Our analysis uses a set of calculations carried out within the ab initio no core shell model with continuum (NCSMC) using a variety of inter-nucleon interactions and basis sizes, and yielding 6 Li deuteron separation energies between 1.3 and 1.8 MeV (Hebborn et al 2022 Phys. Rev. Lett. 129 042503). These NCSMC calculations show that the square of the ANC is strongly correlated with the separation energy over this range. In this work, we investigate the origin of this correlation using the phenomenological R-matrix, a single-channel potential and a perturbative approach. We show that this correlation occurs because the depth of the α–deuteron central potential changes by only a small relative amount as the separation energy varies. We then investigate if the ANC can be accurately extracted from α–deuteron phase shifts in an ideal case in which low-energy data are available and there are no experimental errors. We find that both R-matrix and Coulomb-modified effective-range theory (CM-ERE) yield extracted ANCs close to, although not exactly equal to, the NCSMC value, provided the extrapolation is constrained by the known position of the bound-state pole and at least three terms are included in the fit function. The R-matrix approach converges faster than the CM-ERE as the number of parameters increases and is also more robust against the inclusion of low-energy and high-energy phase shift data. Finally, our study also shows that a naive quantification of uncertainties by comparing different truncations used in both theories is not accurate, and suggests the accuracy of ANCs extracted from phase shift data needs further investigation.

R-matrix↗

Thermoelectric Behavior of Structurally Disordered Lanthanide and Actinide Silicides

Lanthanide and actinide intermetallic materials exhibit intriguing electronic, structural, and magnetic properties arising from their partially filled f orbitals. Strong f-electron correlations can significantly modify the electronic density of states, carrier scattering, and transport behavior, making these systems promising candidates for unconventional thermoelectric materials. In previous studies, single crystals of A1.33T4Al8Si2 (A = Ce, Th, U, Np; T = Co, Ni) were synthesized. This structure consists of ordered TAl2 corrugated double layers separated by disordered An–Si monolayers. The inherent disorder within the An–Si layers has been linked to unusual magnetic behavior, such as spin-glass phenomena, and is expected to strongly influence phonon scattering and charge-carrier transport relevant to thermoelectric performance. However, the thermoelectric properties of this material family have not previously been explored. In this work, DFT calculations were performed to evaluate the electronic density of states, band structures, and thermoelectric properties, including the effects of doping. To validate these predictions, Ce1.33Co4Al8Si2 single crystals were grown and experimentally characterized. Additionally, a new Yb1.33Co4Al8Si2 phase was synthesized and characterized using single-crystal XRD, SEM-EDS, magnetization measurements, and thermoelectric measurements. These results provide insight into structure–property relationships governing thermoelectric behavior in f-electron intermetallics and offer guidance for future thermoelectric materials.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Fabrication of Catalytic Distillation Membranes with Atomic Layer Deposition

The integration of catalysts onto the surface of membranes enables simultaneous physical separation and catalytic transformation of constituents in a feed stream, facilitating improved contaminant removal and fouling mitigation. Distillation membranes are a particularly attractive platform for catalytic membranes because they reject nonvolatile species and exhibit exceptional resistance to oxidative and radical-driven degradation. However, imparting catalytic functionality onto hydrophobic, porous distillation membranes has proven challenging since the membranes used are chemically inert and difficult to modify. Furthermore, catalysts on the membrane surface can decrease hydrophobicity and increase the membrane’s susceptibility to pore wetting and failure. In this work, we create a catalytic distillation membrane by coating a polytetrafluoroethylene membrane surface with titanium dioxide (TiO 2 ) via plasma-assisted atomic layer deposition (ALD). By precisely tuning the ALD parameters, we demonstrate localized growth of TiO 2 near (within approximately 1 μm) the surface of polytetrafluoroethylene membranes, forming a catalytically active interface while preserving the underlying hydrophobic pore structure. Localized growth of TiO 2 is confirmed by electron microscopy and spectroscopy techniques, and membranes coated with 500 cycles of ALD show pressure tolerance up to 12.8 bar and higher than 95% salt rejection in pressure-driven distillation. Photocatalytic activity is demonstrated via the degradation of methylene blue dye under UV irradiation, where increasing TiO2 loading leads to an enhancement in dye degradation. These results establish a general strategy for integrating catalytic functionality into chemically inert, hydrophobic membranes without compromising distillation performance, providing a pathway toward multifunctional membranes that couple advanced oxidation with membrane separation for water treatment.

atomic layer deposition↗

Extreme Nanoconfinement Dramatically Enhances Small Molecule Solubility in Nonpolar Polymers

Elucidating gas solubility in confined polymer systems addresses a fundamental gap in polymer physics and has important implications for gas barrier and separation technologies and polymer upcycling reactions. In this study, we examine the solubility of methanol and n-hexane in polystyrene and low-density polyethylene confined within the interstitial pores of disordered silica nanoparticle packings. Using capillary rise infiltration, these polymers are infiltrated into the nanoparticle packings. Gas solubility in these confined polymers is measured using a quartz crystal microbalance. Remarkably, confinement leads to a 10- to ∼100-fold increase in gas solubility. Systematic experiments reveal that pore size plays a dominant role in increasing solubility. In contrast, the molecular weight of the polymer and the surface wetting characteristics of the nanoparticles, achieved by hydrophobically modifying the nanoparticles, have minimal effects. By systematically varying penetrant polarity, polymer crystallinity, pore size, and nanopore surface chemistry, this study isolates geometric nanoconfinement as the dominant factor governing solubility enhancement in confined polymers. Atomistic simulations revealed that confinement and surface−polymer interactions both contribute to enhanced solubility, with polymer packing playing a significant role in modulating gas uptake. Here, these results suggest that the changes in the molecular arrangements of polymer segments underlie the observed trends. This study highlights the potential of confined polymers in engineering the separation performance of membranes and heterogeneously catalyzed polymer upcycling reactions.

alcohols↗