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At least 1,063 records · Page 59

Radiolysis and Photolysis of Icy Satellite Surfaces: Experiments and Theory

The transport and exchange of material between bodies in the outer solar system is often facilitated by their exposure to ionizing radiation. With this in mind we review the effects of energetic ions, electrons and UV photons on materials present in the outer solar system. We consider radiolysis, photolysis, and sputtering of low temperature solids. Radiolysis and photolysis are the chemistry that follows the bond breaking and ionization produced by incident radiation, producing, e.g., O2 and H2 from irradiated H2O ice. Sputtering is the ejection of molecules by incident radiation. Both processes are particularly effective on ices in the outer solar system. Materials reviewed include H2O ice, sulfur-containing compounds (such as S02 and S8), carbon~contajning compounds (such as CH4), nitrogen-containing compounds (such as NH3 and N2), and mixtures of those compounds. We also review the effects of ionizing radiation on a mixture of N2 and CH4 gases, as appropriate to Titan's upper atmosphere, where radiolysis and photolysis produce complex organic compounds (tholins).

Cassidy, T.↗

Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning

Scalable electronic predictions are critical for soft materials design. Recently, the Electronic Coarse-Graining (ECG) method was introduced to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions using deep neural networks (DNNs). While DNNs can learn complex representations that prove challenging for kernel-based methods, they are susceptible to overfitting and the overconfidence of uncertainty estimations. Here, we develop ECG within a GPU-accelerated Deep Kernel Learning (DKL) framework to enable CG QC predictions using range-separated hybrid density functional theory (DFT), obtaining a 107 speedup relative to naive all-atom QC. By treating the predicted electronic properties as random Gaussian Processes, DKL incorporates CG mapping degeneracy by learning the distribution of electronic energies as a function of CG configuration. DKL-ECG accurately reproduces molecular orbital energies from range-separated DFT while facilitating efficient training via active learning using the uncertainties provided by DKL. Further, we show that while active learning algorithms enable efficient sampling of a more diverse configurational space relative to random sampling, all explored query methods exhibit comparable performance for the examined system. We attribute this result to the significant overlap of the feature space and output property distributions across multiple temperatures.

97 MATHEMATICS AND COMPUTING↗

Spontaneous shock waves in pulse-stimulated flocks of Quincke rollers

Active matter demonstrates complex spatiotemporal self-organization not accessible at equilibrium and the emergence of collective behavior. Fluids comprised of microscopic Quincke rollers represent a popular realization of synthetic active matter. Temporal activity modulations, realized by modulated external electric fields, represent an effective tool to expand the variety of accessible dynamic states in active ensembles. Here, we report on the emergence of shockwave patterns composed of coherently moving particles energized by a pulsed electric field. The shockwaves emerge spontaneously and move faster than the average particle speed. Combining experiments, theory, and simulations, we demonstrate that the shockwaves originate from intermittent spontaneous vortex cores due to a vortex meandering instability. They occur when the rollers’ translational and rotational decoherence times, regulated by the electric pulse durations, become comparable. The phenomenon does not rely on the presence of confinement, and multiple shock waves continuously arise and vanish in the system.

36 MATERIALS SCIENCE↗

Stochastic nucleation processes and substrate abundance explain time-dependent freezing in supercooled droplets

Atmospheric immersion freezing (IF), a heterogeneous ice nucleation process where an ice nucleating particle (INP) is immersed in supercooled water, is a dominant ice formation pathway impacting the hydrological cycle and climate. Implementation of IF derived from field and laboratory data in cloud and climate models is difficult due to the high variability in spatio-temporal scales, INP composition, and morphological complexity. We demonstrate that IF can be consistently described by a stochastic nucleation process accounting for uncertainties in the INP surface area. This approach accounts for time-dependent freezing, a wide range of surface areas and challenges phenomenological descriptions typically used to interpret IF. The results have an immediate impact on the current description, interpretation, and experiments of IF and its implementation in models. The findings are in accord with nucleation theory, and thus should hold for any supercooled liquid material that nucleates in contact with a substrate.

54 ENVIRONMENTAL SCIENCES↗

High-frequency ECG

The standard ECG is by convention limited to 0.05-150 Hz, but higher frequencies are also present in the ECG signal. With high-resolution technology, it is possible to record and analyze these higher frequencies. The highest amplitudes of the high-frequency components are found within the QRS complex. In past years, the term "high frequency", "high fidelity", and "wideband electrocardiography" have been used by several investigators to refer to the process of recording ECGs with an extended bandwidth of up to 1000 Hz. Several investigators have tried to analyze HF-QRS with the hope that additional features seen in the QRS complex would provide information enhancing the diagnostic value of the ECG. The development of computerized ECG-recording devices that made it possible to record ECG signals with high resolution in both time and amplitude, as well as better possibilities to store and process the signals digitally, offered new methods for analysis. Different techniques to extract the HF-QRS have been described. Several bandwidths and filter types have been applied for the extraction as well as different signal-averaging techniques for noise reduction. There is no standard method for acquiring and quantifying HF-QRS. The physiological mechanisms underlying HF-QRS are still not fully understood. One theory is that HF-QRS are related to the conduction velocity and the fragmentation of the depolarization wave in the myocardium. In a three-dimensional model of the ventricles with a fractal conduction system it was shown that high numbers of splitting branches are associated with HF-QRS. In this experiment, it was also shown that the changes seen in HF-QRS in patients with myocardial ischemia might be due to the slowing of the conduction velocity in the region of ischemia. This mechanism has been tested by Watanabe et al by infusing sodium channel blockers into the left anterior descending artery in dogs. In their study, 60 unipolar ECGs were recorded from the entire ventricular surface and were signal-averaged and filtered in the 30-250 Hz frequency range. The results showed that the decrease noted in the HF-QRS correlated linearly with the local conduction delay. The results suggest that HF-QRS is a potent indicator of disturbed local conduction. An alternative theory is that HF-QRS reflect the shape of the original electrocardiographic signal. Bennhagen et al showed that root mean square (RMS) voltage values of the depolarization signal correlate poorly with the signal amplitude but highly with the first and second derivatives, i.e. the velocity and the acceleration of the signal. It has also been suggested that the autonomic nervous system affects HF-QRS. For example, sitting up causes significant changes in HF-QRS in some leads compared to the supine position [Douglas et al., 2006]. Unpublished results indicate that familial dysautonomic patients (both vagal and sympathetic degeneration) have very little Reduced Amplitude Zones (RAZ) formation . Athletic individuals, especially elite athletes, who have vagally-mediated changes on the conventional ECG (i.e. early repolarization, bradycardia) have increased RAZ formation. Further electrophysiological studies are needed, however, to better understand the underlying mechanisms of HF-QRS. Several investigators have studied HF-QRS in different cardiac conditions, including acute myocardial ischemia and myocardial infarction (MI). However, in order for clinicians to confidently use HF-QRS as an adjunct to standard ECG, more knowledge about the characteristics of HF-QRS is needed.

Tragardh, Elin↗

Computational modeling of grain boundary segregation: A review

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

36 MATERIALS SCIENCE↗

Excited State Dynamics of a Conformationally Fluxional Copper Coordination Complex

The conversion of solar energy into chemical fuel represents a capstone goal of the 21st century and has the potential to supply terawatts of power in a globally distributed manner. However, the disparate time scales of photodriven charge separation (~fs) and steps in chemical reactions (~μs) represent an inherent bottleneck in solar-to-fuels technology. Here to address this discrepancy, we are developing earth-abundant coordination complexes that undergo light-induced conformational rearrangements such that charge separation (CS) is hastened, while charge recombination (CR) is slowed. To these ends, we report the preparation and characterization of a new series of conformationally fluxional copper coordination complexes that contain a twisted intramolecular charge transfer (TICT) fluorophore as part of their ligand scaffold. Structural and spectroscopic characterization of the Cu(I) and Cu(II) complexes formed with these ligands in their ground states establish oxidation state-dependent conformational dynamicity, while time-resolved emission and transient absorption spectroscopies define the photopysical parameters of photo-induced excited states. Building on initial reports with a related set of molecules, the improved ligand design presented here greatly simplifies the observed photophysics, effectively shutting down unwanted ligand-centered excited states previously observed. Finally, time-dependent density functional theory (TDDFT) analyses reveal an unusual metal-to-TICT electronic transition only reported once before, and though the formation of a CS state is not observed directly through experiments, TDDFT geometry optimizations in the excited states support the formation of transient Cu(II) CS species, lending credence to the potential success of our approach. These studies establish a clear model for the excited state dynamics at play in proof-of-concept systems and clarify key design parameters for future optimizations toward achieving long-lived CS via photoinduced conformational gating.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing reaction channels via reinforcement learning

Abstract Chemical reactions are dynamical processes involving the correlated reorganization of atomic configurations, driving the conversion of an initial reactant into a result product. By virtue of the metastability of both the reactants and products, chemical reactions are rare events, proceeding fleetingly. Reaction pathways can be modelled probabilistically by using the notion of reactive density in the phase space of the molecular system. Such density is related to a function known as the committor function, which describes the likelihood of a configuration evolving to one of the nearby metastable regions. In theory, the committor function can be obtained by solving the backward Kolmogorov equation (BKE), which is a partial differential equation (PDE) defined in the full dimensional phase space. However, using traditional methods to solve this problem is not practical for high dimensional systems. In this work, we propose a reinforcement learning based method to identify important configurations that connect reactant and product states along chemical reaction paths. By shooting multiple trajectories from these configurations, we can generate an ensemble of states that concentrate on the transition path ensemble. This configuration ensemble can be effectively employed in a neural network-based PDE solver to obtain an approximation solution of a restricted BKE, even when the dimension of the problem is very high. The resulting solution provides an approximation for the committor function that encodes mechanistic information for the reaction, paving a new way for understanding of complex chemical reactions and evaluation of reaction rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of biomechanical models for human factors evaluations

Previewing human capabilities in a computer-aided engineering mode has assisted greatly in planning well-designed systems without the cost and time involved in mockups and engineering models. To date, the computer models have focused on such variables as field of view, accessibility and fit, and reach envelopes. Program outputs have matured from simple static pictures to animations viewable from any eyepoint. However, while kinematics models are available, there are few biomechanical models available for estimating strength and motion patterns. Those, such as Crew Chief, that are available are based on strength measurements taken in specific positions. Johnson Space Center is pursuing a biomechanical model which will use strength data collected on single joints at two or three velocities to attempt to predict compound motions of several joint simultaneously and the resulting force at the end effector. Two lines of research are coming together to produce this result. One is an attempt to use optimal control theory to predict joint motion in complex motions, and another is the development of graphical representation of human capabilities. The progress to date in this research is described.

Woolford, Barbara↗

Direct observation of key aluminum hydroxide prenucleation oligomers for gibbsite nucleation and crystallization in sodium aluminate solution by liquid ToF-SIMS

The mechanism of gibbsite (aluminum hydroxide) crystallization from highly alkaline solutions such as Bayer liquors remains poorly understood, where aluminum (Al) transforms from largely tetrahedrally coordinated aluminate monomers in sodium aluminate solutions into a network of octahedra in gibbsite crystals. A variety of traditional analytical approaches applied to this system do not readily reveal the presence of higher-order oligomeric intermediates. To overcome this limitation, we employed in-situ liquid Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) to examine the Al species present in concentrated sodium aluminate solutions favoring crystallization of gibbsite or sodium aluminate. A complex mixture of Al oligomers was found. By comparing the change in the relative concentration of Al oligomers with +1 and -1 charge, we were able to identify three major Al oligomer candidates, iso-tetramers, iso-pentamers, and cyclic-hexamers, for the nucleation and crystallization of gibbsite. The concentrations of iso-tetramers and iso-pentamers significantly surpass those of cyclic-hexamers. Time-dependent in-situ Raman spectroscopy analysis indicated that the appearance of gibbsite coincided with the peak concentration of these oligomers. The Density-functional theory (DFT) calculation suggests that the formation of iso-oligomers is more favorable than that of cyclic-hexamers. The combined results suggest that iso-tetramers and iso-pentamers play the most substantial role in the nucleation and growth of gibbsite in the sodium aluminate solutions. Our findings also suggest that the oligomers that promote gibbsite crystallization are more stable in dilute sodium aluminate solutions, making these solutions particularly suitable for efficient gibbsite crystallization. In conclusion, our study fills a major knowledge gap in understanding Al speciation that leads to the nucleation and crystallization of gibbsite in concentrated sodium aluminate solutions.

Bayer liquor↗

Unraveling Local Structure of Molten Salts via X-ray Scattering, Raman Spectroscopy, and Ab Initio Molecular Dynamics

In this work, we resolve a long-standing issue concerning the local structure of molten MgCl 2 by employing a multimodal approach, including X-ray scattering and Raman spectroscopy, along with the theoretical modeling of the experimental spectra based on ab initio molecular dynamics (AIMD) simulations utilizing several density functional theory (DFT) methods. We demonstrate the reliability of AIMD simulations in achieving excellent agreement between the experimental and simulated spectra for MgCl 2 and 50 mol % MgCl 2 + 50 mol % KCl, and ZnCl 2 , thus allowing structural insights not directly available from experiment alone. A thorough computational analysis using five DFT methods provides a convergent view that octahedrally coordinated magnesium in pure MgCl 2 upon melting preferentially coordinates with five chloride anions to form distorted square pyramidal polyhedra that are connected via corners and to a lesser degree via edges. This is contrasted with the results for ZnCl 2 , which does not change its tetrahedral coordination on melting. Although the five-coordinate MgCl 5 3– complex was not considered in the early literature, together with an increasing tendency to form a tetrahedrally coordinated complex with decreasing the MgCl 2 content in the mixture with alkali metal chloride systems, current work reconciles the results of most previous seemingly contradictory experimental studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando probing dynamic migration of copper carbonyl during electrocatalytic CO2 reduction

Single crystals and shape-controlled nanocrystals are well known to exhibit facet-dependent catalytic properties. However, few studies have investigated how those nanocrystals evolve and (de)activate during reactions, calling for the development of nanoscale time-resolved operando methods. In this context, we have designed Cu nanocubes as a model system to elucidate the underlying driving force of dynamic nanocatalyst reconstruction during the CO2 reduction reaction (CO2RR). Operando electrochemical liquid-cell scanning transmission electron microscopy (EC-STEM) and synchrotron-based X-ray spectroscopy reveal the size- and potential-dependent complete transformation from (100)-oriented Cu@Cu2O nanocubes to polycrystalline metallic Cu nanograins under CO2RR conditions. In addition, machine learning-assisted operando four-dimensional STEM reveals that large Cu nanograins derived from nanocubes form mainly crystalline domains, while their smaller counterparts are more amorphous due to faster evolution kinetics. In situ Raman spectroscopy and density functional theory calculations suggest that CO drives the ejection of single Cu atoms, resulting in few-nanometre Cu clusters and the surface migration of highly mobile copper carbonyl (Cu–CO) species. Combined, these multimodal operando methods and theoretical approaches pave the way for understanding the complex structural evolution of energy-related nanocatalysts under electrochemical conditions.

Yang, Yao↗

Practical Understanding of Cancer Model Identifiability in Clinical Applications

Mathematical models are a core component in the foundation of cancer theory and have been developed as clinical tools in precision medicine. Modeling studies for clinical applications often assume an individual’s characteristics can be represented as parameters in a model and are used to explain, predict, and optimize treatment outcomes. However, this approach relies on the identifiability of the underlying mathematical models. In this study, we build on the framework of an observing-system simulation experiment to study the identifiability of several models of cancer growth, focusing on the prognostic parameters of each model. Our results demonstrate that the frequency of data collection, the types of data, such as cancer proxy, and the accuracy of measurements all play crucial roles in determining the identifiability of the model. We also found that highly accurate data can allow for reasonably accurate estimates of some parameters, which may be the key to achieving model identifiability in practice. As more complex models required more data for identification, our results support the idea of using models with a clear mechanism that tracks disease progression in clinical settings. For such a model, the subset of model parameters associated with disease progression naturally minimizes the required data for model identifiability.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of Long-Range Forces on the Transition States and Dynamics of NaCl Ion-Pair Dissociation in Water

We study NaCl ion-pair dissociation in a dilute aqueous solution using computer simulations both for the full system with long-range Coulomb interactions and for a well-chosen reference system with short-range intermolecular interactions. Analyzing results using concepts from Local Molecular Field (LMF) theory and the recently proposed AI-based analysis tool “State predictive information bottleneck” (SPIB), we show that the system with short-range interactions can accurately reproduce the transition rate for the dissociation process, the dynamics for moving between the underlying metastable states, and the transition state ensemble. Contributions from long-range interactions can be largely neglected for these processes because long-range forces from the direct interionic Coulomb interactions are almost completely canceled (>90%) by those from solvent interactions over the length scale where the transition takes place. Thus, for this important monovalent ion-pair system, short-range forces alone are able to capture detailed consequences of the collective solvent motion, allowing the use of physically suggestive and computationally efficient short-range models for the dissociation event. Here, we believe that the framework here should be applicable to disentangling mechanisms for more complex processes such as multivalent ion disassociation, where previous work has suggested that long-range contributions may be more important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fractal Characterization of Multitemporal Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the capture, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISs. Scale is fundamental to the characterization of geo-spatial data as represented in GISs, but we have relatively little insight on how to measure the effects of scale in representing data that are acquired in different formats and exist in varying spatial, temporal and radiometric configurations. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective. "Scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which lead to substantial confusion in the input, manipulation, analysis, and output operations. Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale' across all disciplines that use GISs.

Quattrochi, Dale A.↗

Exploring spin symmetry-breaking effects for static field ionization of atoms: Is there an analog to the Coulson–Fischer point in bond dissociation?

Löwdin's symmetry dilemma is an ubiquitous issue in approximate quantum chemistry. In the context of Hartree-Fock (HF) theory, the use of Slater determinants with some imposed constraints to preserve symmetries of the exact problem may lead to physically unreasonable potential energy surfaces. On the other hand, lifting these constraints leads to the so-called broken symmetry solutions that usually provide better energetics, at the cost of losing information about good quantum numbers that describe the state of the system. This behavior has previously been extensively studied in the context of bond dissociation. Here, this paper studies the behavior of different classes of HF spin polarized solutions (restricted, unrestricted, and generalized) in the context of ionization by strong static electric fields. We find that, for simple two electron systems, unrestricted Hartree-Fock (UHF) is able to provide a qualitatively good description of states involved during the ionization process (neutral, singly ionized, and doubly ionized states), whereas RHF fails to describe the singly ionized state. For more complex systems, even though UHF is able to capture some of the expected characteristics of the ionized states, it is constrained to a single M s (diabatic) manifold in the energy surface as a function of field intensity. In this case, a better qualitative picture can be painted by using generalized Hartree-Fock as it is able to explore different spin manifolds and follow the lowest solution due to lack of collinearity constraints on the spin quantization axis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flexible control techniques for a lunar base

The fundamental elements found in every terrestrial control system can be employed in all lunar applications. These elements include sensors which measure physical properties, controllers which acquire sensor data and calculate a control response, and actuators which apply the control output to the process. The unique characteristics of the lunar environment will certainly require the development of new control system technology. However, weightlessness, harsh atmospheric conditions, temperature extremes, and radiation hazards will most significantly impact the design of sensors and actuators. The controller and associated control algorithms, which are the most complex element of any control system, can be derived in their entirety from existing technology. Lunar process control applications -- ranging from small-scale research projects to full-scale processing plants -- will benefit greatly from the controller advances being developed today. In particular, new software technology aimed at commercial process monitoring and control applications will almost completely eliminate the need for custom programs and the lengthy development and testing cycle they require. The applicability of existing industrial software to lunar applications has other significant advantages in addition to cost and quality. This software is designed to run on standard hardware platforms and takes advantage of existing LAN and telecommunications technology. Further, in order to exploit the existing commercial market, the software is being designed to be implemented by users of all skill levels -- typically users who are familiar with their process, but not necessarily with software or control theory. This means that specialized technical support personnel will not need to be on-hand, and the associated costs are eliminated. Finally, the latest industrial software designed for the commercial market is extremely flexible, in order to fit the requirements of many types of processing applications with little or no customization. This means that lunar process control projects will not be delayed by unforeseen problems or last minute process modifications. The software will include all of the tools needed to adapt to virtually any changes. In contrast to other space programs which required the development of tremendous amounts of custom software, lunar-based processing facilities will benefit from the use of existing software technology which is being proven in commercial applications on Earth.

Kraus, Thomas W.↗

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↗