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At least 163 records · Page 9

CMPO-Functionalized Silica Sorbents for pH-Tunable Separation and Enrichment of Rare-Earth Elements from Environmental Matrices

Rare-earth elements (REEs) are crucial in many applications, yet mutual separation is challenging due to their similar chemical behavior. Octylphenyl- N,N-diisobutyl carbamoyl methyl phosphine oxide (CMPO) is an organophosphorus ligand originally developed for extracting actinides and lanthanides from spent nuclear fuel. Here, we report a pH-tunable CMPOfunctionalized silica sorbent for selective REE separation from complex aqueous matrices. A CMPO-associated silica gel sorbent was synthesized and characterized by Brunauer−Emmett−Teller (BET) surface area, scanning electron microscopy, and X-ray photoelectron spectroscopy to confirm the surface functionalization and binding behavior. Sorbent performance was evaluated by using a synthetic 46- element solution and a real phosphate rock fertilizer leachate. Notably, REEs were successfully eluted with ultrapure water, demonstrating reversible desorption controlled by pH adjustment. Packed-bed column studies increased the REE mass fraction from 3.6% to 64% (20-fold enrichment), with up to 30-fold enrichment of neodymium. The adsorption process follows the Langmuir isotherm behavior and follows pseudo-second-order kinetics. The uptake capacity of 1 μmol of REEs per 4.2 μmol of CMPO supports the formation of a predominantly 4:1 ligand:rare earth element(III) pseudocomplex. These results demonstrate CMPO-functionalized silica as a selective, water-elutable, and low-chemical-input platform for sustainable REE recovery from environmental and industrial sources.

chelating ligands↗

Chlorocobaltate-Enabled Selective Separation of CoCl 2 from Mixed Chloride and Nitrate Salts of Mn, Co, and Ni

Described here is the effect of anionic metalates─chlorocobaltate and nitratocobaltate─on the heat-driven separation of the critical element cobalt from potentially competing transition metal salts. Resins bearing the hexadentate glycolamide receptor L (PS-L) exhibit sorption capacities, Q = 1.33 mmol/g for CoCl 2 and Q = 0.66 mmol/g for Co(NO 3 ) 2 , as inferred from sorption isotherm studies. This trend runs counter to the typical Hofmeister series for anion selectivity. Ion chromatographic analysis of a mixed CoCl 2 /Co(NO 3 ) 2 solution revealed an increase in chloride content from 55 mol % to 90 mol % after a single thermally driven catch-and-release cycle. This chloride-selective behavior was recapitulated in a mixed-metal cation, mixed-anion system containing the chloride and nitrate salts of Mn(II), Co(II), and Ni(II) at near-equimolar concentrations. PS-L also displayed enhanced selectivity for Co using this mixed stock solution as observed by ICP-OES. In contrast, for a nitrate-only solution containing Mn(II), Co(II), and Ni(II), PS-L showed increased affinity for Mn, with its proportion rising from 36.6 mol % to 58.1% after a single catch-and-release cycle. Density functional theory calculations support the suggestion that the enhanced uptake of Co(II) in chloride-rich media arises from the high thermodynamic stability of [CoCl 4 ] 2– , which facilitates its outer-sphere coordination to cationic resin-bound cobalt species. Single crystal X-ray crystallographic analyzes of L•MCl 2 (M = Mn, Co, Ni) and L•M(NO 3 ) 2 (M = Mn, Co) confirmed metal complexation by L in the solid state and the concomitant formation of metalate counteranions. Here, the present study highlights a relatively simple approach for separating cobalt from its transition metal congeners.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Suppression of phase separation in AlGaInAs compositionally graded buffers for 1550 nm photovoltaic converters on GaAs

We investigate strategies to suppress phase separation and reduce threading dislocation density (TDD) in AlGaInAs compositionally graded buffers (CGBs) that span the lattice constant range from GaAs to InP. Combining the results from high resolution x-ray diffraction, cathodoluminescence, transmission electron microscopy, and photovoltaic device measurements, we correlate the choices of epitaxial growth conditions with the defect structure of the CGBs and subsequent device performance. Both the use of substrates with high misorientation off (100) toward the (111)A plane and Zn doping instead of Si doping are shown to suppress phase separation and reduce TDD. We demonstrate a 0.74 eV GaInAs device grown on a GaAs substrate offcut 19.5° toward (111)A using a Zn-doped AlGaInAs CGB with TDD = 3.5 ± 0.2 × 10 6 cm -2 that has a bandgap-open circuit voltage offset of only 0.434 V measured under the AM1.5G solar spectrum. We characterized this device under high-intensity irradiance from a 1570 nm laser and measured a 31.9% peak laser power conversion efficiency at 3.6 W/cm 2 irradiance. These results provide a roadmap to the manufacture of laser- and thermal-power conversion devices with the performance and cost-effectiveness needed to drive adoption of these technologies at scale.

14 SOLAR ENERGY↗

SPIKANs: separable physics-informed Kolmogorov–Arnold networks

Physics-Informed Neural Networks (PINNs) have emerged as a promising method for solving partial differential equations (PDEs) in scientific computing. While PINNs typically use multilayer perceptrons (MLPs) as their underlying architecture, recent advancements have explored alternative neural network structures. One such innovation is the Kolmogorov–Arnold Network (KAN), which has demonstrated benefits over traditional MLPs, including faster neural scaling and better interpretability. The application of KANs to physics-informed learning has led to the development of Physics-Informed KANs (PIKANs), enabling the use of KANs to solve PDEs. However, despite their advantages, KANs often suffer from slower training speeds, particularly in higher-dimensional problems where the number of collocation points grows exponentially with the dimensionality of the system. To address this challenge, we introduce Separable Physics-Informed Kolmogorov–Arnold Networks (SPIKANs). This novel architecture applies the principle of separation of variables to PIKANs, decomposing the problem such that each dimension is handled by an individual KAN. This approach drastically reduces the computational complexity of training without sacrificing accuracy, facilitating their application to higher-dimensional PDEs. Through a series of benchmark problems, we demonstrate the effectiveness of SPIKANs, showcasing their superior scalability and performance compared to PIKANs and highlighting their potential for solving complex, high-dimensional PDEs in scientific computing.

Kolmogorov-Arnold networks↗

Reinforced AEM Separators Based on Triblock Copolymers for Electrode-decoupled RFBs

Washington University in St. Louis (WUSTL), in collaboration with The University of Texas at San Antonio (UTSA) and Giner Inc. developed highly selective anion exchange membranes (AEMs) and a novel electrode-decoupled redox flow battery (RFB) for grid scale energy storage as part of the ARPA-E IONICS program (with connections to the DAYS program in the later part of the project). RFBs exhibit the crucial characteristic of system-level decoupled scaling of energy and power which makes them cost effective for the multi-GWh scales envisioned for grid-scale energy storage solutions. This has led to extensive (and deserved) research interest and attention. This project aimed to enhance the design space available for redox-flow batteries (RFBs) by enabling the long-term separation of disparate cationic (elemental) actives using a highly selective membrane separator, while concurrently permitting the transport of anions to balance charge. The approach proposed was to design and develop a highly selective anion-exchange membrane (AEM), which would in turn permit the design and development of electrode-decoupled RFBs. Pairs of (different element) cationic species with redox reactions exhibiting a large difference in their standard electrode potentials were identified to develop high voltage, high power RFBs while disrupting the existing paradigm of using a single element which can ionize to more than two soluble oxidation states (e.g.: Vanadium).

25 ENERGY STORAGE↗

Bridging the length scales in ionic separations via data-driving machine learning

We pursued a data science driven machine learning (ML) approach that blended molecular scale attributes informed from molecular dynamics (MD) simulation and materials properties to the selectivity and energy efficiency in targeted ionic separations using electric fields. The model mixtures investigated for ionic separations are pH sensitive and include organic acids, silica and boron, transition metals, such as copper and chromium. There were two major research thrusts of this project. Firstly, we investigated surrogate models and deep learning that relate material chemistries and structures to selective transport of ionic species under applied electric fields. Secondly we investigated how the bipolar junction interfacial design and water dissociation catalyst in bipolar membranes affect reverse bias polarization behavior and pH modulation in deionization platforms as a function of the platform operating parameters (e.g., cell voltage, residence time, and salt feed concentration). As a result of this work, we also were able to start a new direction, namely ML models for molecular design of surfactants.

36 MATERIALS SCIENCE↗

Strategies for using membrane-based separations to extract critical metals from waste streams

Critical metals are currently extracted by mining followed by their purification. These processes are costly and not environmentally very desirable. In this perspective paper we discuss the potential of extracting these critical metals from a range waste-streams available in abundance globally. These waste streams include brine from desalination plants, effluents from oil drilling and hydraulic fracturing, as well as discharges from various industrial processes such as metal finishing, electroplating, mining, and chemical manufacturing. We show that with a range of new separation processes being developed their separation is showing potential of being both technologically and economically feasible. We also show how high performance computing can be combined with computational models to screen and accelerate the development of new technologies for extracting critical metals from waste streams.

36 MATERIALS SCIENCE↗

Pressure-Gradient-Based RANS Model for Predicting Separation in Transitional and Turbulent Flows

Predicting flow separation poses a significant challenge for RANS models, particularly in transitional flows over airfoils. We propose a novel improvement to RANS models to predict incipient separation in both transitional and fully turbulent flows. Our approach modifies the eddy viscosity model in regions indicated by a pressure-gradient criterion that accounts for intermittency - determining whether the boundary layer is laminar or turbulent. This model demonstrates robust generalization across various airfoil shapes and Reynolds numbers. Applied to the NREL Phase VI wind turbine rotor, our model shows improved aerodynamic performance predictions compared to the baseline RANS model.

k-omega SST↗

Fabrication and Scale-Up of Porous Polybenzimidazole (PBI) Supports for Gas Separation Composite Membranes

Industrial gas separation often uses thin film composite (TFC) membranes comprising a porous support overlaid with a single-/multi-layer gas-selective thin film. An optimal porous support should possess high surface porosity to minimize gas transport resistance and nano-sized pores to ease pore penetration occurring during the thin film coating process. Good chemical and thermal stabilities are essential to withstand the aggressive solvents and heat required for the thin film coating and curing. However, few porous membranes satisfy all these requirements. This study presents a scalable membrane formation method of making highly porous polybenzimidazole (PBI) supports via non-solvent induced phase separation. This presentation also details the scale-up fabrication of PBI supports using a custom roll-to-roll membrane casting machine.

gas separation↗

Mesoscale Magnetostructural Phase Separation in Fe‐deficient Fe 5 GeTe 2

Two-dimensional van der Waals ferromagnet Fe 5-x GeTe 2 (F5GT) is promising for spintronic applications due to its high Curie temperature, layered structure, and ability to host complex magnetic textures. However, the origin of its sample-dependent magnetic anisotropy remains unclear, hindering control of its magnetic behavior. Here, we use spatially resolved cryogenic scanning transmission electron microscopy (STEM) to correlatively map magnetism, lattice structure, and chemistry across atomic-to-micron scales. We reveal that only mesoscale, not nanoscale, inclusions of a Fe-deficient secondary phase significantly modify magnetic behavior, establishing a previously unrecognized critical length scale. This phase separation, induced by quenching, leads to in-plane magnetic anisotropy, while slow cooling confines separation to a few nanometers and preserves out-of-plane anisotropy. These findings reconcile prior inconsistencies and establish a predictive framework for tuning magnetism in F5GT through thermal processing, with broader implications for controlling anisotropy in other two-dimensional magnetic materials.

2D ferromagnets↗

Molecular Simulation of Functionalized Covalent Organic Framework Membranes for Inorganic Salt Separation

Covalent organic frameworks (COFs) enable molecular-level design of nanochannels for selective separation in pressure-driven membrane processes. Through variation of building blocks and, subsequently, the pore structure and chemistry, membrane performance can be tailored. This study employs nonequilibrium molecular dynamics simulations to theoretically demonstrate the tunable selectivity of COF membranes through a bottom-up functionalization approach. Water and salt transport are evaluated for six β-ketoenamine-linked COFs with varying multilayer thicknesses. For the thinnest multilayer (0.64–0.72 nm), all COFs exhibit low sodium sulfate (Na 2 SO 4 ) rejection (55–66%). However, 20 stacked sheets (6.4–7.2 nm) provide 67–98% rejection, with the sulfonated COF providing the highest Na 2 SO 4 rejection. Analysis of time-resolved ion density profiles reveals that solute rejection is primarily governed by interfacial exclusion arising from pore size and functional group chemistry. Although increasing salt rejection compromises water permeance, the permeance of all COF membranes is at least two orders of magnitude greater than that of a commercially available nanofiltration membrane. Overall, this work guides the rational design of COF membranes for aqueous salt separation.

Nanofiltration↗

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗

Should I stay or should I flow? An exploration of phase‐separated metallosupramolecular liquid crystal polymers

Abstract Dynamic liquid crystalline polymers (dLCPs) incorporate both liquid crystalline mesogens and dynamic bonds into a single polymeric material. These dual functionalities impart order‐dependent thermo‐responsive mechano‐optical properties and enhanced reprocessability/programmability enabling their use as soft actuators, adaptive adhesives, and damping materials. While many previous works studying dynamic LCPs utilize dynamic covalent bonds, metallosupramolecular bonds provide a modular platform where a series of materials can be accessed from a single polymeric feedstock through the variation of the metal ion used. A series of dLCPs were prepared by the addition of metal salts to a telechelic 2,6‐bisbenzimidazolylpyridine (Bip) ligand endcapped LCP to form metallosupramolecular liquid crystal polymers (MSLCPs). The resulting MSLCPs were found to phase separate into hard and soft phases which aids in their mechanical robustness. Variations of the metal salts used to access these materials allowed for control of the thermomechanical, viscoelastic, and adhesive properties with relaxations that can be tailored independently of the mesogenic transition. This work demonstrates that by accessing phase separation through the incorporation of metallosupramolecular moieties, highly processable yet robust MSLCP materials can be realized. This class of materials opens the door to LCPs with bulk flow behavior that can also be utilized as multi‐level adhesives.

Chemistry↗

2D Nitrogen‐Doped Graphene Materials for Noble Gas Separation

Abstract Noble gases, notably xenon, play a pivotal role in diverse high‐tech applications. However, manufacturing xenon is an inherently challenging task, due to its unique properties and trace abundance in the Earth's atmosphere. Consequently, there is a pressing need for the development of efficient methods for the separation of noble gases. Using mild fluorographene chemistry, nitrogen‐doped graphene (GNs) materials are synthesized with abundant aromatic regions and extensive nitrogen doping within the vacancies and holes of the aromatic lattice. Due to the organized interlayer “nanochannels”, nitrogen functional groups, and defects within the two‐dimensional (2D) structures, GNs exhibits effective selectivity for Xe over Kr at low pressure. This enhanced selectivity is attributed to the stronger binding affinity of Xe to GN compared to Kr. The adsorption is governed by London dispersion forces, as revealed by theoretical calculations using symmetry‐adapted perturbation theory (SAPT). Investigation of other GNs differing in nitrogen content, surface area, and pore sizes underscores the significance of nitrogen functional groups, defects, and interlayer nanochannels over the surface area in achieving superior selectivity. This work offers a new perspective on the design and fabrication of functionalized graphene derivatives, exhibiting superior noble gas storage and separation activity exploitable in gas production technologies.

Šedajová, Veronika↗

Nanofilm Composite Membranes of Bottlebrush Poly(1,3‐Dioxolane) Plasticized by Poly(Ethylene Glycol) for CO 2 /N 2 Separation

Abstract Poly(1,3‐dioxolane) has emerged as a leading membrane material for post‐combustion CO 2 capture due to its high ether oxygen content and strong affinity toward CO 2 . However, they are often cross‐linked to inhibit crystallization, which makes them impossible to fabricate into industrial thin‐film composite membranes. Herein, soluble and high molecular weight bottlebrush polymers ( b PDXLA) are synthesized using reversible addition‐fragmentation chain transfer polymerization and demonstrate the feasibility of fabricating nanofilm (≈100 nm) composite membranes (NCMs). Furthermore, b PDXLA can be plasticized using a miscible additive of poly(ethylene glycol) dimethyl ether (PEGDME) to improve CO 2 permeability while retaining good CO 2 /N 2 selectivity. For example, adding 20 mass% PEGDME improves CO 2 permeance from 930 to 1300 GPU and decreases CO 2 /N 2 selectivity from 74 to 53 at 25 °C; the membrane exhibits stable separation performance competitive with state‐of‐the‐art commercial membranes. This work unveils a practical approach to designing uncross‐linked, highly polar polymers for practical membrane gas separation and highlights a facile way to enhance performance by incorporating miscible plasticizers using industrial manufacturing processes.

Zhang, Gengyi [Department of Chemical and Biologic↗

Side-Chain Nanophase Separation Broadens the Double-Gyroid Stability Window in PS–PODMA Diblock Copolymers

Expanding access to bicontinuous network phases in block copolymers remains an important challenge because the double gyroid (DG) phase is usually stable only within a narrow composition window in conventional diblock copolymers. Here, we show that poly(styrene-block-octadecyl methacrylate) (PS-b-PODMA) exhibits an unusually broad DG window. Small-angle X-ray scattering measurements across a wide composition range reveal lamellar and hexagonally packed cylindrical phases at higher polystyrene fractions. In contrast, the DG phase appears over 0.22 ≤ fPS ≤ 0.35, with DG/BCC and DG/HEX coexistence near fPS = 0.18 and 0.40, respectively. This broad DG window is much wider than those reported for neat diblock copolymers and is not readily explained by conformational asymmetry alone. Wide-angle X-ray scattering detects a characteristic signature of nanophase separation within the PODMA-rich domains, indicating that side-chain ordering introduces an additional internal length scale. These results suggest that hierarchical side-chain nanophase separation modifies packing frustration and curvature selection, thereby broadening DG stability and providing a new molecular design strategy for stabilizing complex network morphologies.

Seko, Tamio↗

Extraction and separation of rare earth elements using LN resins in hydrochloric acid

The separation of the rare earth elements is essential for numerous scientific applications but remains a significant challenge due to the nearly identical chemical properties of the adjacent lanthanide elements. Eichrom’s LN series of extraction chromatographic resins feature organophosphorus extractants and are widely used to achieve adjacent lanthanide separations. While extensive characterization of these resins has been completed for nitric acid matrices, the use of hydrochloric acid is preferred for a variety of applications. Further, the extraction of the rare earth elements, La–Lu and Y, has been characterized on LN and LN2 resins in hydrochloric acid via batch uptake and column chromatographic studies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Ozonolysis of selenium: an alternative oxidation method for radiochemical separations of arsenic and selenium

Many arsenic and selenium radiochemical separation methods use hydrogen peroxide (H 2 O 2 ) to oxidize selenite (Se(IV)) to selenate (Se(VI)), but this reaction is challenging to control and replicate. Here, this study introduces a simple ozonolysis apparatus with an in-line oxygen-ozone generator and impinger system for rapid selenium oxidation in aqueous samples as an alternative to H 2 O 2 . The system quickly converts Se(IV) to Se(VI), enabling successful separations of arsenic-73 and selenium-75 with high recoveries using ion-exchange chromatography (1-X8). Compared to traditional H 2 O2 treatment, ozone oxidation is a faster and more easily controlled method for selenium redox chemistry.

and nuclear chemistry↗