Relationship of interface structure to the dynamics of selective lanthanide extraction
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The role of nanoscale chemomechanical behavior in the macroscopic performance of functional materials is well recognized. For lithium-ion battery cathodes, tremendous effort has been devoted to the development of new chemistry and structure, yet fundamental understanding of the correlation between redox processes and mechanical properties of the novel materials lags behind. In the present study, we prepare large discrete single grains of Li-excess cation-disordered rocksalts (DRX) and investigate their chemomechanical behavior at the particle level, using nanoresolution X-ray and electron-based spectro-imaging and chemical mapping techniques. While irregular cracking upon lithium extraction leads to the eventual breakdown of the baseline DRX oxide (Li 1.2 Ti 0.4 Mn 0.4 O 2 ) particles at a high delithiation state, the fluorinated-DRX (Li 1.3 Ti 0.3 Mn 0.4 O 1.7 F 0.3 ) clearly displays aligned cracking along the <001> direction. The resulting periodicity in the cracking pattern enables the particles to retain their integrity and, consequently, improved electrochemical stability. Density functional theory (DFT) calculations showed that fluorination leads to increased concentration of Li+ on the (001) planes and preferential Li movements along the <001>-family directions, revealing the underlying mechanism for directional cracking. Overall, our study demonstrates the unique role of fluorine in modulating nanoscale chemomechanics, which in turn influences the evolution of charge and strain heterogeneity at the particle level. These insights provide important design guidelines in further improving DRX cathode materials.
Produced water is a by-product of industrial operations, such as hydraulic fracturing for increased oil recovery, that causes environmental issues since it includes different metal ions (e.g., Li+, K+, Ni2+, Mg2+, etc.) that need to be extracted or collected before disposal. To remove these substances using either selective transport behavior or absorption-swing processes employing membrane-bound ligands, membrane separation procedures are promising unit operations. This study investigates the transport of a series of salts in crosslinked polymer membranes synthesized using a hydrophobic monomer (phenyl acrylate, PA), a zwitterionic hydrophilic monomer (sulfobetaine methacrylate, SBMA), and a crosslinker (methylenebisacrylamide, MBAA). Membranes are characterized according to their thermomechanical properties, where an increased SBMA content leads to decreased water uptake due to structural differences within the films and to more ionic interactions between the ammonium and sulfonate moieties, resulting in a decreased water volume fraction, and Young’s modulus increases with increasing MBAA or PA content. Permeabilities, solubilities, and diffusivities of membranes to LiCl, NaCl, KCl, CaCl2, MgCl2, and NiCl2 are determined by diffusion cell experiments, sorption-desorption experiments, and the solution-diffusion relationship, respectively. Permeability to these metal ions generally decreases with an increasing SBMA content or MBAA content due to the corresponding decreasing water volume fraction, and the permeabilities are in the order of K+ > Na+ > Li+ > Ni2+ > Ca2+ > Mg2+ presumably due to the differences in the hydration diameter.
Since lithium (Li) is a key element for clean energy technologies, the global lithium demand is anticipated to increase rapidly. As a result, efficient lithium extraction technologies that allow the exploitation of unconventional lithium resources, such as geothermal brines and inland brine streams, are essentially needed to meet the Li demand and keep supply chains stable. However, because of low Li concentration, low ratio of Li/Mg or Li/Ca, and complex feed compositions in these feedstocks, using conventional hydrometallurgy or current Direct Lithium Extraction (DLE) processes are often chemical-intensive, requiring substantial amounts of reagent chemicals to recover Li at scale, resulting in large chemical footprints. Therefore, we developed a novel Zwitterionic Chromatography (ZIC) process to separate Li from these resources. Because Li can be partitioned from divalent salts on ZIC under water elution without using chemicals, exploiting the unconventional resources via a ZIC approach can be environmentally benign and sustainable. In this work, we will present the development of the ZIC process for DLE applications. Simulation studies for the Li separation mechanism in ZIC and the demonstration of a continuous ZIC process to separate Li from domestic inland brine and mining wastewater will be presented. Finally, the chemical and energy footprints of ZIC in comparison to other DLE processes will be discussed.
Critical minerals (CM) such as rare earth elements (REE+) and Lithium (Li) are essential to technological innovation, energy transitions, global economic and defense security, necessitating the search for unconventional resources and efficient recovery methods to avert supply chain disruptions. Here, this study evaluates coal-associated sediments (underclay and roof rock) and wastes from the Pennsylvanian Pottsville Formation of the Southern Appalachian Basin (SAB) as potential feedstocks for CM recovery. A total of 34 samples (15 underclays, 12 roof rocks, 5 Acid Mine Drainage (AMD) sludges, and 2 coal mining wastes) were characterized using XRD, XRF, ICP-MS, and μ-XRF analytical methods. The REE+ and Li concentrations of these materials ranged from 46.8 to 334.4 ppm and from 11.1 to 519 ppm, respectively, with one underclay sample (Hendrix 3456) yielding the highest values for both. Bulk mineralogy for all samples was dominated by aluminosilicate clay phases, particularly illite and kaolinite. All samples exhibited REY def, rel% values >26% and C outl indices that ranged from 0.69 to 0.94, classifying their REE ore potential as Category II (Promising) as defined by Seredin and Dai (2012). Extractability tests (EPA method 3051 A) yielded low REE+ and Li recoveries, with maximum values of 3.3% and 3.6%, respectively, suggesting associations with resistant minerals like clay and phosphates. Elemental mapping indicates that REE+ is associated with phosphate, whereas statistical analysis suggests that REE+ are associated with aluminosilicates, suggesting heterogeneous associations or minimal phosphate contribution. Li also correlated positively with Al 2 O 3 , indicating an aluminosilicate host. This study highlights the potential of coal-associated sediments in the SAB.
A great challenge for 21 cm intensity mapping experiments is the strong foreground radiation which is orders of magnitude brighter than the 21 cm signal. Removal of the foreground takes advantage of the fact that its frequency spectrum is smooth while the redshifted 21 cm signal spectrum is stochastic. However, a complication is the non-smoothness of the instrument response. This paper describes the electromagnetic simulation of the Tianlai cylinder array, a pathfinder for 21 cm intensity mapping experiments. Due to the vast scales involved, a direct simulation requires a large amount of computing resources. We have made the simulation practical by using a combination of methods: first simulate a single feed, then an array of feed units, finally with the feed array and a cylindrical reflector together, obtain the response for a single cylinder. We studied its radiation pattern, bandpass response and the effects of mutual coupling between feed units, and compared the results with observation. Many features seen in the measurement result are reproduced well in the simulation, especially the oscillatory features which are associated with the standing waves on the reflector. The mutual coupling between feed units is quantified with S-parameters, which decrease as the distance between the two feeds increases. Based on the simulated S-parameters, we estimate the correlated noise which has been seen in the visibility data, and the results show very good agreement with the data in both magnitude and frequency structures. These results provide useful insights on the problem of 21 cm signal extraction for real instruments.
Contour trees describe the topology of level sets in scalar fields and are widely used in topological data analysis and visualization. A main challenge of utilizing contour trees for large-scale scientific data is their computation at scale using highperformance computing. To address this challenge, recent work has introduced distributed hierarchical contour trees for distributed computation and storage of contour trees. However, effective use of these distributed structures in analysis and visualization requires subsequent computation of geometric properties and branch decomposition to support contour extraction and exploration. In this work, we introduce distributed algorithms for augmentation, hypersweeps, and branch decomposition that enable parallel computation of geometric properties, and support the use of distributed contour trees as query structures for scientific exploration. Finally, we evaluate the parallel performance of these algorithms and apply them to identify and extract important contours for scientific visualization.
We review our recent quantum stochastic model for spectroscopic lineshapes in the presence of a coevolving and nonstationary background population of excitations. Starting from a field theory description for interacting bosonic excitons, we derive a reduced model whereby optical excitons are coupled to an incoherent background via scattering as mediated by their screened Coulomb coupling. The Heisenberg equations of motion for the optical excitons are then driven by an auxiliary stochastic population variable, which we take to be the solution of an Ornstein–Uhlenbeck process. Here, we present an overview of the theoretical techniques we have developed as applied to predicting coherent nonlinear spectroscopic signals. We show how direct (Coulomb) and exchange coupling to the bath give rise to distinct spectral signatures and discuss mathematical limits on inverting spectral signatures to extract the background density of states.
This data package contains the data for Tooley et al. (2022) Intra-canopy leaf trait variation facilitates high leaf area index and compensatory growth in a clonal woody encroaching shrub. The purpose of this project was to evaluate the leaf ecophysiological traits of Cornus drummondii C.A. Mey to better understand how C. drummondii maximizes photosynthetic rates across large gradients of light availability in its short, dense canopies. We also evaluate how C. drummondii modifies its allocation of leaf traits in response to grassland disturbance. High LAI canopies and a compensatory growth response to disturbance are two key factors contributing to the success of C. drummondii and other woody species responsible for the encroachment of grasslands.The data package contains ecophysiological measurements, including leaf morphological, physiological, and chemical traits; photosynthetic measurements, leaf carbon and nitrogen stable isotopes, leaf area index, and photosynthetically active radiation. All measurements were taken vertically across canopies of the clonal woody-encroaching shrub Cornus drummondii under browsed, grazed, and control (unbrowsed and ungrazed) conditions.Files:SeasonalMeasurements_Archive.csv - Data for all seasonal measurements used in the study.LeafPhotoSeasonalRaw_Archive.zip - zip file containing raw data from an li-6400 for each sampling period in the study.LAI_Archive.xlsx - Data for LAI Measurements.ACiandLightCurveResults_Archive.xlsx - Contains parameters extracted from A-ci and Light Response curves along with the morphological and chemical traits for each leaf.ACiRaw Archive.xlsx - Raw data from Li-6400 for A-ci response curvesLightCurves_Raw.zip - zip file containing raw data for Li-6400 light response curves. Excel file format: "IslandID"-"Depth"-lc.xlsx (or .csv)DataCollectionMethods.docx - file containing the methods of data collection, processing, and QA/QC for all data files. File also contains a list of excel file headers, abbreviations, and their units.
This project aims to develop technologies toward the production of Li and Ni from CO 2 -reactive minerals and rocks that contain Ca and Mg, while sequestering CO 2 . The technologies include acoustic stimulation and electrolytic proton production, which use electricity to liberate valuable metal ions from the surrounding mineral matrix at sub-boiling temperatures (~20-80°C). Feedstocks include Li/Ni/Ca/Mg-rich igneous and sedimentary rocks and minerals such as holmquistite, hectorite, lateritic Ni ores enriched in Mg-rich serpentine. Other examples of feedstocks that could be used include coarse grained orthocumulate, mine tailings, etc. In the first step, the electrolytic breakdown of water to H + and OH – (as well as O 2 and H 2 ) will be induced by applying an electric potential to simultaneously produce acidity and alkalinity. The solid feedstocks will be dissolved in the acidic anolyte under acoustic stimulation. Solubilized species will then undergo separation using our unique Li + -selective membranes driven by electrodialysis, leading to concentration of Li as soluble lithium silicate, from which Li 2 CO 3 can be derived by reaction with CO 2(g) while supplying cathode alkalinity. Also at the cathode, stepwise electrolytic precipitation of metal hydroxides, including Ni(OH) 2 , Ca(OH) 2 , and Mg(OH) 2 is performed along a cascade reactor in which both the applied potential and pH increase downstream, thereby simultaneously extracting and separating the metals. Finally, exposure of Ca(OH) 2 and Mg(OH) 2 to dilute CO 2 will result in CO 2 uptake in the form of Ca and Mg carbonates. The primary accomplishments include sample procurement and characterization. Progress has been made on precursor identification and mapping, establishing protocols for assessing metal extractability under sonication, and preliminary technoeconomic analysis (TEA) and life cycle analysis (LCA).
The search for batteries with high energy density has highlighted lithium-rich manganese-based layered oxides due to their exceptionally high capacity. Although it is clear that both cationic and anionic redox are present in the charge compensation mechanism, the microstructural evolution of the Li 2 MnO 3 -like phase during anionic redox and its role in battery performance and structural stability are still not fully understood. Here, we systematically probe microstructural evolution using spatially resolved synchrotron X-ray measurements and reveal an underlying interaction between the Li 2 MnO 3 -like domains and bulk rhombohedral structure. Mn ion activation and a previously unobserved structural distortion are discovered at high voltages, and can be related to structural strain present in the Li 2 MnO 3 -like phase upon substantial lithium ion extraction. Moreover, we elucidate a correlation between this structural distortion and irreversible phase transitions by thermally perturbing delithiated samples. These insights highlight a pathway toward achieving high capacity cathode materials required for future commercial applications.
Here, the impacts of calcination on the leaching recovery of rare earth elements (REEs) and other critical metals from a Baker seam coal refuse material were investigated. Acid leaching test results showed that leaching recovery of the REEs, especially the light REEs, was increased significantly from around 24% to 80–90% after calcination under 600–750 °C for two hours. By considering the major element leaching kinetics and the mineralogical changes of the dominant minerals caused by calcination, two mechanisms were proposed for the improved leaching performance: (1) decomposition of difficult-to-dissolve REE-bearing minerals into soluble forms; and (2) liberation of REE-bearing minerals encapsulated in clays after calcination due to the dehydration and disintegration of the layered clay structure. Sequential chemical extraction tests showed that a significant fraction (around 75%) of the REEs in the raw material were present in an insoluble form. After calcination under proper temperatures (600–800 °C), the majority of the insoluble light REEs (LREEs) were converted into soluble forms. Changes in the modes of occurrence of the LREEs and phosphorous based on leaching rate and sequential leaching correlated well as a function of the calcination temperature. This finding in addition to SEM-EDX results tends to indicate the potential that the LREEs occur primarily as rare earth phosphates such as monazite in the untreated coal refuse material. The acid leaching and sequential chemical extraction results show that co-extraction of REEs and other critical metals such as Co, Mn, and Li is possible using a calcination-acid leaching procedure.
Solid state Li-ion batteries (SSLBs) are promising technologies for the next generation energy storage devices with higher energy density and enhanced safety. The solid state electrolyte (SSE) is a key component to deliver these desired electrochemical performance characteristics. Here we provide a brief review on the discovery, synthesis, structure, ion-conduction mechanism, and application of LGPS-type and garnet-type lithium ion conductors as two representative SSEs, aiming to extract principles for future design and discovery of favourable solid state Li-ion electrolytes for SSLBs. Recent advances in the strategies to address the challenges with respect to SSLBs are also discussed. Lastly, a perspective on the future research directions of SSLBs is provided.
Separation processes are essential for purifying and isolating critical materials, but are challenging due to the natural tendency of systems to mix. This project explores far-from-equilibrium separation methods using external electric and magnetic fields to drive selective nucleation and crystal growth. Using in situ electrochemical transmission electron microscopy (TEM), we observed ion transport and crystallization behavior under applied electric fields. We found that ions migrate toward the working electrode, where nucleation preferentially occurs. These findings advance our understanding of non-equilibrium separation mechanisms and support the development of efficient, sustainable methods for extracting critical materials from unconventional domestic sources.
Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the semantic relationships in the text document although it has been widely applied in text mining. BERTopic, created in 2022, leveraged advances in deep learning and can capture the contextual relationships between words. In this work, we integrated Artificial Intelligence (AI) modules to LDA and BERTopic and provided a comprehensive comparison on the analysis of prescription opioid-related cardiovascular risks in women. Opioid use can increase the risk of cardiovascular problems in women such as arrhythmia, hypotension etc. 1,837 abstracts were retrieved and downloaded from PubMed as of April 2024 using three Medical Subject Headings (MeSH) words: “opioid,” “cardiovascular,” and “women.” Machine Learning of Language Toolkit (MALLET) was employed for the implementation of LDA. BioBERT was used for document embedding in BERTopic. Eighteen was selected as the optimal topic number for MALLET and 23 for BERTopic. ChatGPT-4-Turbo was integrated to interpret and compare the results. The short descriptions created by ChatGPT for each topic from LDA and BERTopic were highly correlated, and the performance accuracies of LDA and BERTopic were similar as determined by expert manual reviews of the abstracts grouped by their predominant topics. The results of the t-SNE (t-distributed Stochastic Neighbor Embedding) plots showed that the clusters created from BERTopic were more compact and well-separated, representing improved coherence and distinctiveness between the topics. Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. Therefore, while LDA remains valuable for large-scale text analysis with resource constraints, AI-assisted BERTopic offers significant advantages in providing the enhanced interpretability and the improved semantic coherence for extracting valuable insights from textual data.
New processes directly extract lithium from dilute sources. The accelerating global push to reduce carbon emissions is driving substantial demand for clean energy technologies and the materials on which they depend. Nations are vying for critical minerals, such as lithium, cobalt, and rare earth elements), to produce electric vehicles, energy storage devices, and other low-carbon technologies. Tremendous attention focuses on lithium, which is primarily sourced from either hard rock called spodumene or natural brines—solutions containing lithium and other salts found in continental deposits, for example. However, mining lithium often involves energy-intensive, laborious processes. On pages 1438 and 1444 of this issue, Li et al. and Song et al., respectively, report efficient ways to extract lithium from dilute brine. In conclusion, these advances open up opportunities for sustainable extraction from unexploited dilute brines.