Nanoscale chemical imaging with structured X-ray illumination.

High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.

In situ visualization of multicomponents coevolution in a battery pouch cell.

Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro-computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 µm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.

Surface coating by mechanofusion modulates bulk charging pathways and battery performance of Ni-rich layered cathodes.

Ni-rich layered oxides as high-capacity battery cathodes suffer from degradation at high voltages. We utilize a dry surface modification method, mechanofusion (MF), to achieve enhanced battery stability. The simplicity, high yield, and flexibility make it cost-effective and highly attractive for processing at the industrial scale. The underlying mechanisms responsible for performance improvement are unveiled by a systematic study combining multiple probes, e.g., 3D nano-tomography, spectroscopic imaging, in situ synchrotron diffraction, and finite element analysis (FEA). MF affects the bulk crystallography by introducing partially disordered structure, microstrain, and local lattice variation. Furthermore, the crack initiation and propagation pattern during delithiation are regulated and the overall mechanical fracture is reduced after such surface coating. We validate that MF can alter the bulk charging pathways. Such a synergic effect between surface modification and bulk charge distribution is fundamentally important for designing next-generation battery cathode materials.

Revealing the Chemical and Structural Complexity of Electrochemical Ion Exchange in Layered Oxide Materials.

Soft chemistry techniques, such as ion exchange, hold great potential for the development of battery electrode materials that cannot be stabilized via conventional equilibrium synthesis methods. Nevertheless, the intricate mechanisms governing ion exchange remain elusive. Herein, we investigate the evolution of the long-range and local structure, as well as the ion (de)intercalation mechanism during electrochemical Li-to-Na ion exchange initiated from an O3-type lithium-layered oxide cathode. The in situ-formed mixed-cation electrolyte leads to competitive intercalation of Li and Na ions. While Li ion intercalation predominates at the beginning of initial discharge, Na ion cointercalation into a different layer results in ion redistribution and phase separation, with the emergence of a P3-Na phase alongside an O3-Li phase. Further, this study spatially resolves the heterogeneous nature of electrochemical ion exchange reactions within individual particles and provides insights into the correlations between local Ni redox processes and phase separation. Overall, electrochemical ion exchange leads to a mixed-phase cathode and alters its reaction kinetics. Those findings have important implications for the development of new metastable materials for renewable energy devices and ion separation applications.

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation.

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

Chemomechanics of Rechargeable Batteries: Status, Theories, and Perspectives.

Chemomechanics is an old subject, yet its importance has been revived in rechargeable batteries where the mechanical energy and damage associated with redox reactions can significantly affect both the thermodynamics and rates of key electrochemical processes. Thanks to the push for clean energy and advances in characterization capabilities, significant research efforts in the last two decades have brought about a leap forward in understanding the intricate chemomechanical interactions regulating battery performance. Going forward, it is necessary to consolidate scattered ideas in the literature into a structured framework for future efforts across multidisciplinary fields. This review sets out to distill and structure what the authors consider to be significant recent developments on the study of chemomechanics of rechargeable batteries in a concise and accessible format to the audiences of different backgrounds in electrochemistry, materials, and mechanics. Importantly, we review the significance of chemomechanics in the context of battery performance, as well as its mechanistic understanding by combining electrochemical, materials, and mechanical perspectives. We discuss the coupling between the elements of electrochemistry and mechanics, key experimental and modeling tools from the small to large scales, and design considerations. Lastly, we provide our perspective on ongoing challenges and opportunities ranging from quantifying mechanical degradation in batteries to manufacturing battery materials and developing cyclic protocols to improve the mechanical resilience.

High-resolution multicontrast tomography with an X-ray microarray anode-structured target source.

Multicontrast X-ray imaging with high resolution and sensitivity using Talbot-Lau interferometry (TLI) offers unique imaging capabilities that are important to a wide range of applications, including the study of morphological features with different physical properties in biological specimens. The conventional X-ray TLI approach relies on an absorption grating to create an array of micrometer-sized X-ray sources, posing numerous limitations, including technical challenges associated with grating fabrication for high-energy operations. We overcome these limitations by developing a TLI system with a microarray anode-structured target (MAAST) source. The MAAST features an array of precisely controlled microstructured metal inserts embedded in a diamond substrate. Using this TLI system, tomography of a Drum fish tooth with high resolution and tri-contrast (absorption, phase, and scattering) reveals useful complementary structural information that is inaccessible otherwise. The results highlight the exceptional capability of high-resolution multicontrast X-ray tomography empowered by the MAAST-based TLI method in biomedical applications.

P2-Type Moisture-Stable and High-Voltage-Tolerable Cathodes for High-Energy and Long-Life Sodium-Ion Batteries.

P2-Na0.67Ni0.33Mn0.67O2 represents a promising cathode for Na-ion batteries, but it suffers from severe structural degradation upon storing in a humid atmosphere and cycling at a high cutoff voltage. Here we propose an in situ construction to achieve simultaneous material synthesis and Mg/Sn cosubstitution of Na0.67Ni0.33Mn0.67O2 via one-pot solid-state sintering. The materials exhibit superior structural reversibility and moisture insensitivity. In-operando XRD reveals an essential correlation between cycling stability and phase reversibility, whereas Mg substitution suppressed the P2-O2 phase transition by forming a new Z phase, and Mg/Sn cosubstitution enhanced the P2-Z transition reversibility benefiting from strong Sn-O bonds. DFT calculations disclosed high chemical tolerance to moisture, as the adsorption energy to H2O was lower than that of the pure Na0.67Ni0.33Mn0.67O2. A representative Na0.67Ni0.23Mg0.1Mn0.65Sn0.02O2 cathode exhibits high reversible capacities of 123 mAh g-1 (10 mA g-1), 110 mAh g-1 (200 mA g-1), and 100 mAh g-1 (500 mA g-1) and a high capacity retention of 80% (500 mA g-1, 500 cycles).

Identification of AURKA as a Biomarker Associated with Cuproptosis and Ferroptosis in HNSCC.

Cuproptosis and ferroptosis represent copper- and iron-dependent forms of cell death, respectively, and both are known to play pivotal roles in head and neck squamous cell carcinoma (HNSCC). However, few studies have explored the prognostic signatures related to cuproptosis and ferroptosis in HNSCC. Our objective was to construct a prognostic model based on genes associated with cuproptosis and ferroptosis. We randomly assigned 502 HSNCC samples from The Cancer Genome Atlas (TCGA) into training and testing sets. Pearson correlation analysis was utilized to identify cuproptosis-associated ferroptosis genes in the training set. Cox proportional hazards (COX) regression and least absolute shrinkage operator (LASSO) were employed to construct the prognostic model. The performance of the prognostic model was internally validated using single-factor COX regression, multifactor COX regression, Kaplan-Meier analysis, principal component analysis (PCA), and receiver operating curve (ROC) analysis. Additionally, we obtained 97 samples from the Gene Expression Omnibus (GEO) database for external validation. The constructed model, based on 12 cuproptosis-associated ferroptosis genes, proved to be an independent predictor of HNSCC prognosis. Among these genes, the increased expression of aurora kinase A (AURKA) has been implicated in various cancers. To further investigate, we employed small interfering RNAs (siRNAs) to knock down AURKA expression and conducted functional experiments. The results demonstrated that AURKA knockdown significantly inhibited the proliferation and migration of HNSCC cells (Cal27 and CNE2). Therefore, AURKA may serve as a potential biomarker in HNSCC.

Resolving Charge Distribution for Compositionally Heterogeneous Battery Cathode Materials.

The isostructural nature of Li-layered cathodes allows for accommodating multiple transition metals (TMs). However, little is known about how the local TM stoichiometry influences the charging behavior of battery particles thus impacting battery performance. Here, we develop heterogeneous compositional distributions in polycrystalline LiNi1-x-yMnxCoyO2 (NMC) particles to investigate the interplay between local stoichiometry and charge distribution. These NMC particles exhibit a broad, continuous distribution of local Ni/Mn/Co stoichiometry, which does not compromise the global layeredness. The local Mn and Ni concentrations in individual NMC particles are positively and negatively correlated with the electrochemically induced Ni oxidation, respectively, whereas the Co concentration does not impose a clear effect on the Ni oxidation. The resulting material delivers excellent reversible capacity, rate capability, and cycle life at high operating voltages. Engineering Ni/Mn/Co distribution in NMC particles may provide a path toward controlling the charge distribution and thus chemomechanical properties of polycrystalline battery particles.

Creation of a Prognostic Model Using Cuproptosis-Associated Long Noncoding RNAs in Hepatocellular Carcinoma.

Cuproptosis is an unusual form of cell death caused by copper accumulation in mitochondria. Cuproptosis is associated with hepatocellular carcinoma (HCC). Long noncoding RNAs (LncRNAs) have been shown to be effective prognostic biomarkers, yet the link between lncRNAs and cuproptosis remains unclear. We aimed to build a prognostic model of lncRNA risk and explore potential biomarkers of cuproptosis in HCC. Pearson correlations were used to derive lncRNAs co-expressed in cuproptosis. The model was constructed using Cox, Lasso, and multivariate Cox regressions. Kaplan-Meier survival analysis, principal components analysis, receiver operating characteristic curve, and nomogram analyses were carried out for validation. Seven lncRNAs were identified as prognostic factors. A risk model was an independent prognostic predictor. Among these seven lncRNAs, prostate cancer associated transcript 6 (PCAT6) is highly expressed in different types of cancer, activating Wnt, PI3K/Akt/mTOR, and other pathways; therefore, we performed further functional validation of PCAT6 in HCC. Reverse transcription-polymerase chain reaction results showed that PCAT6 was aberrantly highly expressed in HCC cell lines (HepG2 and Hep3B) compared to LO2 (normal hepatocytes). When its expression was knocked down, cells proliferated and migrated less. PCAT6 might be a potential biomarker for predicting prognosis in HCC.

Constructed Risk Prognosis Model Associated with Disulfidptosis lncRNAs in HCC.

Disulfidptosis is a novel cell death mode in which the accumulation of disulfide bonds in tumor cells leads to cell disintegration and death. Long-stranded noncoding RNAs (LncRNAs) are aberrantly expressed in hepatocellular carcinoma (HCC) and have been reported to carry significant potential as a biomarker for HCC prognosis. However, lncRNA studies with disulfidptosis in hepatocellular carcinoma have rarely been reported. Therefore, this study aimed to construct a risk prognostic model based on the disulfidptosis-related lncRNA and investigate the mechanisms associated with disulfidptosis in hepatocellular carcinoma. The clinical and transcriptional information of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA) and divided into test and validation sets. Furthermore, 1668 lncRNAs associated with disulfidptosis were identified using Pearson correlation. Six lncRNA constructs were finally identified for the risk prognostic model using one-way Cox proportional hazards (COX), multifactorial COX, and lasso regression. Kaplan-Meier (KM) analysis, principal component analysis, receiver operating characteristic curve (ROC), C-index, and column-line plot results confirmed that the constructed model was an independent prognostic factor. Based on the disulfidptosis risk score, risk groups were identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. Finally, we confirmed that phospholipase B domain containing 1 antisense RNA 1 (PLBD1-AS1) and muskelin 1 antisense RNA (MKLN1-AS) were highly expressed in hepatocellular carcinoma and might be potential biomarkers in HCC by KM analysis and quantitative real-time PCR (RT-qPCR). This study demonstrated that lncRNA related to disulfidptosis could serve as a biomarker to predict prognosis and treatment targets for HCC.

RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers.

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches. Systematic protocols for comparing models and crystal structures are described and analyzed. In these six puzzles, we discuss (i) the comparison between the automated web servers and human experts; (ii) the prediction of coaxial stacking; (iii) the prediction of structural details and ligand binding; (iv) the development of novel prediction methods; and (v) the potential improvements to be made. We show that correct prediction of coaxial stacking and tertiary contacts is essential for the prediction of RNA architecture, while ligand binding modes can only be predicted with low resolution and simultaneous prediction of RNA structure with accurate ligand binding still remains out of reach. All the predicted models are available for the future development of force field parameters and the improvement of comparison and assessment tools.

Solar-driven, highly sustained splitting of seawater into hydrogen and oxygen fuels.

Electrolysis of water to generate hydrogen fuel is an attractive renewable energy storage technology. However, grid-scale freshwater electrolysis would put a heavy strain on vital water resources. Developing cheap electrocatalysts and electrodes that can sustain seawater splitting without chloride corrosion could address the water scarcity issue. Here we present a multilayer anode consisting of a nickel-iron hydroxide (NiFe) electrocatalyst layer uniformly coated on a nickel sulfide (NiSx) layer formed on porous Ni foam (NiFe/NiSx-Ni), affording superior catalytic activity and corrosion resistance in solar-driven alkaline seawater electrolysis operating at industrially required current densities (0.4 to 1 A/cm2) over 1,000 h. A continuous, highly oxygen evolution reaction-active NiFe electrocatalyst layer drawing anodic currents toward water oxidation and an in situ-generated polyatomic sulfate and carbonate-rich passivating layers formed in the anode are responsible for chloride repelling and superior corrosion resistance of the salty-water-splitting anode.

Highly active oxygen evolution integrated with efficient CO2 to CO electroreduction.

Electrochemical reduction of CO2 to useful chemicals has been actively pursued for closing the carbon cycle and preventing further deterioration of the environment/climate. Since CO2 reduction reaction (CO2RR) at a cathode is always paired with the oxygen evolution reaction (OER) at an anode, the overall efficiency of electrical energy to chemical fuel conversion must consider the large energy barrier and sluggish kinetics of OER, especially in widely used electrolytes, such as the pH-neutral CO2-saturated 0.5 M KHCO3 OER in such electrolytes mostly relies on noble metal (Ir- and Ru-based) electrocatalysts in the anode. Here, we discover that by anodizing a metallic Ni-Fe composite foam under a harsh condition (in a low-concentration 0.1 M KHCO3 solution at 85 °C under a high-current ∼250 mA/cm2), OER on the NiFe foam is accompanied by anodic etching, and the surface layer evolves into a nickel-iron hydroxide carbonate (NiFe-HC) material composed of porous, poorly crystalline flakes of flower-like NiFe layer-double hydroxide (LDH) intercalated with carbonate anions. The resulting NiFe-HC electrode in CO2-saturated 0.5 M KHCO3 exhibited OER activity superior to IrO2, with an overpotential of 450 and 590 mV to reach 10 and 250 mA/cm2, respectively, and high stability for >120 h without decay. We paired NiFe-HC with a CO2RR catalyst of cobalt phthalocyanine/carbon nanotube (CoPc/CNT) in a CO2 electrolyzer, achieving selective cathodic conversion of CO2 to CO with >97% Faradaic efficiency and simultaneous anodic water oxidation to O2 The device showed a low cell voltage of 2.13 V and high electricity-to-chemical fuel efficiency of 59% at a current density of 10 mA/cm2.

Fast Li Plating Behavior Probed by X-ray Computed Tomography.

Uneven lithium plating/stripping is an essential issue that inhibits stable cycling of a lithium metal anode and thus hinders its practical applications. The investigation of this process is challenging because it is difficult to observe lithium in an operating device. Here, we demonstrate that the microscopic lithium plating behavior can be observed in situ in a close-to-practical cell setup using X-ray computed tomography. The results reveal the formation of porous structure and its progressive evolution in space over the charging process with a large current. The elaborated analysis indicates that the microstructure of deposited lithium makes a significant impact on the subsequent lithium plating, and the impact of structural inhomogeneity, further exaggerated by the large-current charging, can lead to severely uneven lithium plating and eventually cell failure. Therefore, a codesign strategy involving delicate controls of microstructure and electrochemical conditions could be a necessity for the next-generation battery with lithium metal anode.

Automatic 3D image registration for nano-resolution chemical mapping using synchrotron spectro-tomography.

Nano-resolution synchrotron X-ray spectro-tomography has been demonstrated as a powerful tool for probing the three-dimensional (3D) structural and chemical heterogeneity of a sample. By reconstructing a number of tomographic data sets recorded at different X-ray energy levels, the energy-dependent intensity variation in every given voxel fingerprints the corresponding local chemistry. The resolution and accuracy of this method, however, could be jeopardized by non-ideal experimental conditions, e.g. instability in the hardware system and/or in the sample itself. Herein is presented one such case, in which unanticipated sample deformation severely degrades the data quality. To address this issue, an automatic 3D image registration method is implemented to evaluate and correct this effect. The method allows the redox heterogeneity in partially delithiated LixTa0.3Mn0.4O2 battery cathode particles to be revealed with significantly improved fidelity.

Deep-learning-based image registration for nano-resolution tomographic reconstruction.

Nano-resolution full-field transmission X-ray microscopy has been successfully applied to a wide range of research fields thanks to its capability of non-destructively reconstructing the 3D structure with high resolution. Due to constraints in the practical implementations, the nano-tomography data is often associated with a random image jitter, resulting from imperfections in the hardware setup. Without a proper image registration process prior to the reconstruction, the quality of the result will be compromised. Here a deep-learning-based image jitter correction method is presented, which registers the projective images with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. This development is demonstrated and validated using synthetic and experimental datasets. The method is effective and readily applicable to a broad range of applications. Together with this paper, the source code is published and adoptions and improvements from our colleagues in this field are welcomed.

Quantifying redox heterogeneity in single-crystalline LiCoO2 cathode particles.

Active cathode particles are fundamental architectural units for the composite electrode of Li-ion batteries. The microstructure of the particles has a profound impact on their behavior and, consequently, on the cell-level electrochemical performance. LiCoO2 (LCO, a dominant cathode material) is often in the form of well-shaped particles, a few micrometres in size, with good crystallinity. In contrast to secondary particles (an agglomeration of many fine primary grains), which are the other common form of battery particles populated with structural and chemical defects, it is often anticipated that good particle crystallinity leads to superior mechanical robustness and suppressed charge heterogeneity. Yet, sub-particle level charge inhomogeneity in LCO particles has been widely reported in the literature, posing a frontier challenge in this field. Herein, this topic is revisited and it is demonstrated that X-ray absorption spectra on single-crystalline particles with highly anisotropic lattice structures are sensitive to the polarization configuration of the incident X-rays, causing some degree of ambiguity in analyzing the local spectroscopic fingerprint. To tackle this issue, a methodology is developed that extracts the white-line peak energy in the X-ray absorption near-edge structure spectra as a key data attribute for representing the local state of charge in the LCO crystal. This method demonstrates significantly improved accuracy and reveals the mesoscale chemical complexity in LCO particles with better fidelity. In addition to the implications on the importance of particle engineering for LCO cathodes, the method developed herein also has significant impact on spectro-microscopic studies of single-crystalline materials at synchrotron facilities, which is broadly applicable to a wide range of scientific disciplines well beyond battery research.

A monovalent ion in the DNA binding interface of the eukaryotic junction-resolving enzyme GEN1.

GEN1 is a member of the FEN/EXO family of structure-selective nucleases that cleave 1 nt 3' to a variety of branchpoints. For each, the H2TH motif binds a monovalent ion and plays an important role in binding one helical arm of the substrates. We investigate here the importance of this metal ion on substrate specificity and GEN1 structure. In the presence of K+ ions the substrate specificity is wider than in Na+, yet four-way junctions remain the preferred substrate. In a combination of K+ and Mg2+ second strand cleavage is accelerated 17-fold, ensuring bilateral cleavage of the junction. We have solved crystal structures of Chaetomium thermophilum GEN1 with Cs+, K+ and Na+ bound. With bound Cs+ the loop of the H2TH motif extends toward the active site so that D199 coordinates a Mg2+, buttressed by an interaction of the adjacent Y200. With the lighter ions bound the H2TH loop changes conformation and retracts away from the active site. We hypothesize this conformational change might play a role in second strand cleavage acceleration.