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At least 271 records · Page 15

Carbon nanotube nanofluidics

Fluid flow under extreme spatial confinement exhibits unusual physical behaviors. This nanofluidic transport regime is relevant to a variety of mass transport, separation, and energy production processes in biological and industrial systems. Carbon nanotubes (CNTs) offer a nearly ideal platform for exploring nanofluidic transport because of their extremely narrow, smooth, hydrophobic inner pores, which enable very fast molecular flow while providing strong selectivity. In this review, we aim to provide a comprehensive understanding of nanofluidics in CNTs, focusing on the basic physics of mass transport in CNTs, various experimental platforms developed to investigate these phenomena, and key results on the permeation of water, protons, and ions. We focus on the critical factors that influence transport efficiency and selectivity, such as slip flow and charge regulation in CNTs, and the roles of entrance effects, dehydration processes and ion–charge interactions at the CNT entrances. We also explore the confinement effects, highlighting how the unique one-dimensional structure of CNTs imposes distinct constraints on fluid behavior and leads to novel single-file transport phenomena. Finally, we address current challenges and future directions of CNT nanofluidics.

Li, Zhongwu [Lawrence Livermore National Laborator↗

The spin selectivity effect in chiral materials

We overview experiments performed on the chiral induced spin selectivity (CISS) effect using various materials and experimental configurations. Through this survey of different material systems that manifest the CISS effect, we identify several attributes that are common to all the systems. Among these are the ability to observe spin selectivity for two point contact configurations, when one of the electrodes is magnetic, and the correlation between the optical activity of the chiral systems and a material’s spin filtering properties. In addition, recent experiments show that spin selectivity does not require pure coherent charge transport and the electron spin polarization persists over hundreds of nanometers in an ordered medium. Finally, we point to several issues that still have to be explored regarding the CISS mechanism. Among them is the role of phonons and electron–electron interactions.

36 MATERIALS SCIENCE↗

The very high n Rydberg series of Ar 16+ in Alcator C-Mod tokamak plasmas

We report x-ray transitions of the very high-n Rydberg series in Ar 16+ have been observed from Alcator C-Mod tokamak plasmas. Individual emission lines up to 1s16p-1s 2 have been resolved and the central chord line brightnesses with principal quantum number n between 7 and 16 are generally found to decay as 1/n α , with α slightly larger than 3. In the plasma periphery, emission from 1s9p-1s 2 and 1s10p-1s 2 are found to be significantly enhanced relative to this decrease, indicative of selected population of these levels through charge exchange between background neutral deuterium in the ground state and Ar 17+ . An unresolved feature between the wavelengths of 1s27p-1s 2 and 1s30p-1s 2 is also present, which arises through charge exchange with neutral deuterium in the n* = 3 excited state. The brightnesses of transitions populated by charge exchange are spatially up/down asymmetric, with an excess on the side of the magnetic surface X-point. The relative brightness of the unresolved very high-n feature compared to 1s7p-1s 2 is found to increase with electron temperature and decrease with electron density. Simulations of line emission just on the long wavelength side of the Ar 16+ ionization limit indicate that the principal quantum number decay exponent is closer to α = 4 at very high n. The brightness dependence on n below 16 is in excellent agreement with calculations from the flexible atomic code package.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Scalable Parallel Measurement of Individual Nitrogen-Vacancy Centers

The nitrogen-vacancy (NV) center in diamond is a solid-state spin defect that has been widely adopted for quantum sensing and quantum information processing applications. Typically, experiments are performed either with a single isolated NV center or with an unresolved ensemble of many NV centers, resulting in a trade-off between measurement speed and spatial resolution or control over individual defects. In this work, we introduce an experimental platform that bypasses this trade-off by addressing multiple optically resolved NV centers in parallel. We perform charge- and spin-state manipulations selectively on multiple NV centers from within a larger set, and we manipulate and measure the electronic spin states of over 100 NV centers in parallel. We show that the high signal-to-noise ratio of the measurements enables the detection of shot-to-shot pairwise correlations between the spin states of 108 NV centers, corresponding to the simultaneous measurement of 5778 unique correlation coefficients. We discuss how our platform can be scaled to parallel experiments with thousands of individually resolved NV centers. These results enable parallelized high-throughput sensing experiments that retain the spatial resolution of single defects and will, thereby, help to unlock advances in applications such as single-molecule NMR and characterization of integrated circuits. In addition, our approach to multiplexing provides a natural platform for the application of recently developed correlated sensing techniques.

NV centers↗

Disentangling Centrality Bias and Final-State Effects in the Production of High-𝑝 𝑇 Neutral Pions Using Direct Photon in 𝑑+Au Collisions at $\sqrt{s_{NN}}$ = 200 GeV

Here, PHENIX presents a simultaneous measurement of the production of direct 𝛾 and 𝜋 0 in 𝑑 + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV over a 𝑝 𝑇 range of 7.5 to 18 GeV/𝑐 for different event samples selected by event activity, i.e., charged-particle multiplicity detected at forward rapidity. Direct-photon yields are used to empirically estimate the contribution of hard-scattering processes in the different event samples. Using this estimate, the average nuclear-modification factor, 𝑅$^{𝜋^0}_{dAu,EXP}$, is 0.925 ± 0.023⁢(stat) ± 0.15⁢(scale), consistent with unity for minimum-bias (MB) 𝑑+Au collisions. For event classes with low and moderate event activity, 𝑅$^{𝜋^0}_{dAu,EXP}$ is consistent with the MB value within 5% uncertainty. This result confirms that the previously observed enhancement of high-𝑝 𝑇 𝜋 0 production found in small-system collisions with low event activity is a result of a bias in interpreting event activity within the Glauber framework. In contrast, for the top 5% of events with the highest event activity, 𝑅$^{𝜋^0}_{dAu,EXP}$ is suppressed by 20% relative to the MB value with a significance of 4.5⁢𝜎, which may be due to final-state effects. This suppression corresponds to a 𝑝 𝑇 shift of 𝛿⁢𝑝 𝑇 = 0.213 ± 0.055 Gev/𝑐 at 9 Gev/𝑐.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

First Extraction of Single Differential Cross-Sections on Argon for CC1$\mu$2p0$\pi$ Event Topologies in the MicroBooNE Detector

The precise measurement of cross-sections for a variety of interactions is critical to the success of forthcoming flagship neutrino experiments. Of special interest are neutrino interactions that leave the nucleus in a 2-particle 2-hole state (2p2h). This note will present the first cross-section measurement for the production of 2p2h states on argon. Using MicroBooNE data collected from the first three years of operation, we select events corresponding to a charged-current $ν_µ$ interaction that left the argon nucleus in a 2p2h state. These interactions produce a topology with one muon and two protons in the final state (CC1$\mu$2p0$\pi$). This analysis targets a single differential cross-section measurement for CC1$\mu$2p0$\pi$ event topologies in a variety of kinematic variables. Comparisons are made to a set of theoretical models that explore different cross-section modeling configurations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Artificial-Intelligence Aided Design and Synthesis of Novel Layered 2D Multi-Principal Element Materials for Energy Storage (Final Report)

This DOE-EPSCoR project aimed to predict, synthesize, and characterize novel layered two-dimensional (2D) high-entropy materials (HEMs). These 2D-HEMs, composed of multiple principal elements in nearly equal concentrations, are distinct from traditional 2D materials (typically containing two or three elements) and conventional alloys (dominated by a single primary element with minor secondary additions). Their unique structural and compositional features enable significant lattice strain accommodation, resulting in enhanced electrode performance and potential applications in catalysis, hydrogen storage, sensing, quantum information technologies, and flexible electronics. The research focused on addressing four fundamental questions: (i) What combinations of elements can form stable and synthesizable 2D-HEMs? (ii) What mechanisms drive the stability and synthesizability of crystalline single-phase 2D-HEMs? (iii) How do local chemical disorder and defects influence the macroscopic electronic and mechanical properties? and (iv) What charge storage mechanisms are active in selectively synthesized 2D-HEMs for battery and supercapacitor electrode applications? To achieve these goals, the project employed an integrated theory-experiment approach, incorporating high-throughput first-principles calculations, theoretical modeling, data mining, experimental synthesis, and advanced characterization techniques. The advanced computing resources and state-of-the-art experimental characterization facilities at Oak Ridge National Laboratory (ORNL) were leveraged through collaboration. Beyond scientific advancements, the project contributed to workforce development. Two postdoctoral researchers and three graduate students at the University of Maine were trained through co-advising by ORNL scientists and collaborative interactions, strengthening their expertise in cutting-edge materials science.

36 MATERIALS SCIENCE↗

First Results from the Search for Muon-Neutrino Disappearance with the ICARUS Detector

After successful operation at LNGS and a major upgrade at CERN, the 760-ton ICARUS T600 detector has been running at Fermilab since 2020, collecting neutrino interactions from the BNB and NuMI beams. In late 2025, ICARUS reached five years of continuous data taking, demonstrating the maturity of large-scale LAr-TPC technology and its relevance for future experiments such as DUNE. This contribution presents the first ICARUS search for muon-neutrino disappearance in the BNB. Charged-current 1$\mu$Np events selected from 2022–2023 data are compared to simulations and interpreted, for the first time, within a two-neutrino approximation of the 3+1 sterile-neutrino model, including systematic uncertainties from flux, interaction, and detector effects. Although currently limited by systematic uncertainties, this first oscillation analysis probes the parameter space suggested by existing $\nu_\mu$ disappearance results and lays the groundwork for future SBN combined analyses with SBND, which will significantly improve sensitivity to sterile-neutrino scenarios.

Steklain, Andre [Parana Tech. Fed. U., Toledo] (OR↗

The Very High n Rydberg Series of Ar^16+ in Alcator C-Mod Tokamak Plasmas

X-ray transitions of the very high-n Rydberg series in Ar^16+ have been observed from Alcator C-Mod tokamak plasmas. Individual emission lines up to 1s16p - 1s^2 have been resolved and the central chord line brightnesses with principal quantum number n between 7 and 16 are generally found to decay as 1/n^alpha, with alpha slightly larger than 3. In the plasma periphery, emission from 1s9p - 1s^2 and 1s10p - 1s^2 are found to be significantly enhanced relative to this decrease, indicative of selected population of these levels through charge exchange between background neutral deuterium in the ground state and Ar^17+. An unresolved feature between the wavelengths of 1s27p - 1s^2 and 1s30p - 1s^2 is also present, which arises through charge exchange with neutral deuterium in the n^* = 3 excited state. The brightnesses of transitions populated by charge exchange are spatially up/down asymmetric, with an excess on the side of the magnetic surface X-point. The relative brightness of the unresolved very high-n feature compared to 1s7p - 1s^2 is found to increase with electron temperature and decrease with electron density. Simulations of line emission just on the long wavelength side of the Ar^16$ ionization limit indicate that the principal quantum number decay exponent is closer to alpha = 4 at very high n. The brightness dependence on n below 16 is in excellent agreement with calculations from the Flexible Atomic Code package.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploring the Photophysics of N-Type Polymer N2200

The polymer interphase is a complex environment comprised of polymer chains, solvent molecules, and electrolyte ions. However, the microenvironments that these ingredients produce is both poorly-understood and difficult to investigate given the system's inherent structural heterogeneity. Nonetheless, a fundamental understanding of the structure, electrochemical behavior, and excited-state dynamics is a key prerequisite to optimizing devices based on such a system - for instance, photoelectrochemical cells for the direct, light-driven production of solar hydrogen, which may minimize efficiency losses compared to sequential light harvesting and electrochemical hydrogen production in separate but linked devices. This work combines transient absorption (TA) spectroscopy, which is a powerful tool for the observation of a variety of excited states on a femto- to microsecond timescale, with time-resolved microwave conductivity (TRMC) spectroscopy, which selectively probes the dynamics of free charge carriers (FC), of a blend of a donor polymer (PTB7-Th) and acceptor polymer (N2200) in a bulk heterojunction. Initial results indicate an extension of FC lifetime and homogenization of the microenvironment on a whole-film level, not just at the surface of the polymer; however, many questions are still under active investigation, including the changes in energy of the involved polaron states, effective conjugation length, FC mobility and migration distance, etc. Additional experiments regarding the photoinitiated behavior of the blend in different environments and on different timescales are ongoing.

charge recombination↗

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

First Measurement of Differential Charged Current Quasielastic-like $\nu_\mu$–Argon Scattering Cross Sections In Kinematic Imbalance Variables With The MicroBooNE Detector

We report the first measurement of flux-integrated multi-differential cross sections for charged-current events with muon neutrinos scattering on argon with solely a muon and a single proton in the final state as a function of kinematic imbalance variables. The measurement was carried out using the Booster Neutrino Beam at Fermi National Accelerator Laboratory within the MicroBooNE Liquid Argon Time Projection Chamber detector with an exposure of 6.79 × 10 20 protons on target. Events were selected to enhance the contribution of charged-current mesonless interactions with one proton detected in the final state. The data discussed here are reported in terms of multidifferential cross sections in kinematic imbalance variables, which are generally sensitive to nuclear effects. The double-differential results in these variables can provide an excellent handle to disentagle specific nuclear aspects not easily isolated via single differential cross sections. Our results pave a path towards identifying regions of the phase-space where future interaction modeling development and Monte Carlo neutrino generator tuning efforts should concentrate. EVENT SELECTION Neutrino oscillation measurements aim to extract neutrino mixing angles, mass differences, the value of the chargeparity violating phase in the lepton sector, and to search for new physics beyond the Standard Model [1, 2]. For that to be achieved, an unprecedented understanding of neutrino-argon interactions is of utmost importance since a growing number of neutrino oscillation experiments employ Liquid Argon Time Projector Chamber (LArTPC) neutrino detectors [3–6]. The accuracy to which these experiments can extract neutrino oscillation parameters requires a good understanding of the neutrino energy. Experimentally, this energy is deduced from the measured kinetic energies of particles that are emitted following the neutrino interaction in the detector. The kinematic properties of such finalstate particles reflect complex dynamics due to nuclear and initial-state effects of the interaction [7]. However, certain categories of nuclear effects can be isolated by variables built specifically to characterize the degeneracy between such effects [8–10]. This note reports cross sections in kinematic variables sensitive to nuclear effects using events with one detected muon with momentum 0.1 < pµ < 1.2 GeV/c, and exactly one proton with 0.3 < pp < 1 GeV/c. This signal definition includes events with any number of protons below 300 MeV/c, neutrons at any momenta, and charged pions with momentum lower than 70 MeV/c. This choice is guided by the fact that their experimental signature of correlated muon-proton pairs is fairly straightforward to reconstruct [11–22]. Such events primarily originate from chargedcurrent (CC) neutrino-nucleon quasielastic (QE) scattering interactions where the neutrino removes a single intact nucleon from the nucleus without producing any additional particles. This definition can also include contributions from interactions that lead to the production of additional particles that are absent from the final state due to nuclear effects, such as pion absorption, or have momenta that are below the experimental detection threshold.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Time‐Dependent Cation Selectivity of Titanium Carbide MXene in Aqueous Solution

Abstract Electrochemical ion separation is a promising technology to recover valuable ionic species from water. Pseudocapacitive materials, especially 2D materials, are up‐and‐coming electrodes for electrochemical ion separation. For implementation, it is essential to understand the interplay of the intrinsic preference of a specific ion (by charge/size), kinetic ion preference (by mobility), and crystal structure changes. Ti 3 C 2 T z MXene is chosen here to investigate its selective behavior toward alkali and alkaline earth cations. Utilizing an online inductively coupled plasma system, it is found that Ti 3 C 2 T z shows a time‐dependent selectivity feature. In the early stage of charging (up to about 50 min), K + is preferred, while ultimately Ca 2+ and Mg 2+ uptake dominate; this unique phenomenon is related to dehydration energy barriers and the ion exchange effect between divalent and monovalent cations. Given the wide variety of MXenes, this work opens the door to a new avenue where selective ion‐separation with MXene can be further engineered and optimized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Supramolecular Control of Redox-Mediated Interactions for Ion-Selective Electroseparations

This report summarizes efforts from the Su Group at the University of Illinois at Urbana-Champaign in researching and developing materials and processes for the recovery of rare earth elements and other metal elements that are critical to the United States economy and national security, under DOE Award No. DE-SC0021409. This report highlights efforts in the recovery of: • Transition metal elements (including arsenic, chromium, molybdenum, rhenium, vanadium): Redox-active metallopolymers are able to capture these elements in their oxyanion form. Direct control of target ion capture/release through electrochemical-mediated switching of metallocene binding sites reduces chemical input and lowers generation of waste in element recovery processes. We study the effects of metallopolymer structure on targeted ion binding through a combination of experimental screening of ion selectivity from multi-component mixtures, computational efforts which elucidate the charge-transfer origins of metallocene binding and provide insight on how binding site structure influences selectivity, and state-of-the-art neutron reflectivity of metallocene polymer films to understand the interplay of polymer-ion (charge-transfer), polymer-solvent (polymer hydrophilicity/hydrophobicity), and ion-solvent (ion hydration) interactions with spatial resolution of polymer films. • Rare earth elements (including yttrium, neodymium, europium, gadolinium, dysprosium, cerium): Here we employ redox-copolymers for recovery of rare earth elements by electrochemically regenerated ion-exchange. Rare earth elements require an alternative route to capture/release than directly with metallopolymers since rare earth elements typically exist in cationic form in water. To address this, copolymerization of traditional ion-exchange moieties with metallocene moieties allowed for capture of rare earth elements with the ion-exchange moieties and electrochemical-mediated release of rare earth elements through oxidation of metallocene moieties.

36 MATERIALS SCIENCE↗

Measurements of differential charged-current cross sections on argon for electron neutrinos with final-state protons in MicroBooNE

This work presents single-differential electron-neutrino charged-current cross sections on argon measured using the MicroBooNE detector at the Fermi National Accelerator Laboratory. The analysis uses data recorded when the Neutrinos at the Main Injector beam was operating in both neutrino and antineutrino modes, with exposures of $2 \times 10^{20}$ and $5 \times 10^{20}$ protons on target, respectively. A selection algorithm targeting electron-neutrino charged-current interactions with at least one proton, one electron, and no pions in the final topology is used to measure differential cross sections as a function of outgoing electron energy, total visible energy, and opening angle between the electron and the most energetic proton. The interaction rate as a function of proton multiplicity is also reported. The total cross section is measured as [4.1 $\pm$ 0.4 (stat.) $\pm$ 1.2 (syst.)]$ $$\times 10^{-39} \mathrm{cm}^{2}/ \mathrm{nucleon}$. The unfolded cross-section measurements are compared to predictions from neutrino event generators commonly employed in the field. Good agreement is seen across all variables within uncertainties.

Abratenko, P. [Tufts U. (main)]↗

Surface Composition Impacts Selectivity of ZnTe Photocathodes in Photoelectrochemical CO 2 Reduction Reaction

Light-driven reduction of CO 2 into chemicals using a photoelectrochemical (PEC) approach is considered as a promising way to meet the carbon neutral target. The very top surface of the photoelectrode and semiconductor/electrolyte interface plays a pivotal role in defining the performance for PEC CO 2 reduction. However, such impact remains poorly understood. Here, we report an electrodeposition-annealing route for tailoring surface composition of ZnTe photocathodes. Our work demonstrates that a Zn-rich surface on the ZnTe photocathode is essential to impact the CO 2 reduction activity and selectivity. In particular, the Zn-rich surface not only facilitated the interfacial charge carrier transfer, but also acted as electrocatalyst for boosting carbon product selectivity and suppressing the hydrogen evolution reaction. This work provides a new avenue to optimize the photocathode, as well as improvement of the CO 2 RR performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure and Potential–Dependent Selectivity in Redox–Metallopolymers: Electrochemically Mediated Multicomponent Metal Separations

Electro-responsive functional materials can play a critical role in selective metal recovery and recycling due to the need for molecular differentiation between transition metals in complex mixtures. Redox-active metallopolymers are a promising platform for electrochemical separations, offering versatile structural tuning and fast electron transfer. First, through a judicious selection of polymer structure between a main-chain metallopolymer (polyferrocenylsilane) and a pendant-group metallopolymer (polyvinylferrocene), charge-transfer interactions and binding strength toward competing metal ions are tuned, which as a result, dictate selectivity. For example, almost an order of magnitude increase in separation factor between chromate and meta-vanadate can be achieved, depending on polymer structure. Second, these metallopolymer electrodes exhibit potential-dependent selectivity that can even flip ion preference, based solely on electrical means—indicating a control parameter that is orthogonal to structural modifications. Finally, this work presents a framework for evaluating electrochemical separations in multicomponent ion mixtures and elucidates the underlying charge-transfer mechanisms resulting in molecular selectivity through a combination of spectroscopy and electronic structure calculations. Furthermore, the findings demonstrate the applicability of redox-metallopolymers in tailored electrochemical separations for environmental remediation, value-added metal recovery, waste recycling, and even mining processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗