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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Tailoring the Properties of Chemically Recyclable Polyethylene‐Like Multiblock Polymers by Modulating the Branch Structure

Abstract Developing plastics that fill the need of polyolefins yet are more easily recyclable is a critical need to address the plastic waste crisis. However, most efforts in this vein have focused on high‐density polyethylene (PE), while many different types of PE exist. To create broadly sustainable PE with modular properties, we present the synthesis, characterization, and demonstration of materials applications for chemically recyclable PE‐like multiblock polymers prepared from distinct hard and soft blocks using ruthenium‐catalyzed dehydrogenative polymerization. By altering the branching pattern within the soft blocks, a series of PE‐like multiblock polymers were synthesized with tunable glass transition temperatures ( T g ) while maintaining consistent high melting temperatures ( T m ). A clear U‐shape trend between T g and mechanical properties was found, showcasing their potential as sustainable materials with tailored properties spanning commercial linear low‐density polyethylene (LLDPE) and low‐density polyethylene (LDPE). These materials offer adjustable adhesive strength to metal and demonstrate chemical recyclability and selective depolymerization in mixed plastic streams, promoting circularity and separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Prediction of superconductivity and topological aspects in single-layer β -Bi 2 Pd

Topological superconductors, characterized by topologically nontrivial states residing in a superconducting gap, are a recently discovered class of materials having Majorana fermions. The interplay of superconductivity and topological states gives rise to opportunities for achieving such topological superconductors in condensed matter systems. Up to now, several single-material topological superconductors in this form have been theoretically predicted and experimentally confirmed. Here, using the first-principles calculations, we study the superconducting single-layer β-Bi 2 Pd. In this work, the electronic density of states near Fermi level of this monolayer are dominated by the Bi-p and Pd-d orbitals, forming a two-band Fermi surface with multiclass sheets. The presence of soft phonon bands, in cooperation with the electron susceptibility, accounts for electron-phonon superconductivity of single-layer β-Bi 2 Pd. With the centrosymmetric structure, single-layer β-Bi 2 Pd possesses a continuous gap over the whole Brillouin zone and topological Dirac-like states at its one-dimensional boundary. The present findings would lead to the expectation of one-dimensional topological superconductivity and Majorana bound states in a monolayer candidate of β-Bi 2 Pd with intrinsic full-gap superconductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

On the Prospect of Chemically Transferable Coarse-Grained Electronic Models for Soft Materials

Electronic coarse-graining (ECG) methods predict quantum-mechanical electronic properties directly from coarse-grained (CG) molecular configurations, enabling electronic predictions at mesoscale length scales. Here, we present a diagnostic assessment of the feasibility of chemically transferable ECG models across a broad polymer-relevant chemical space using all-atom, united-atom, and Martini-scale representations. While high-resolution ECG models achieve near-quantitative accuracy, we show that chemically transferable ECG at the Martini resolution fails because the CG force field does not sample the same configurational distribution of local molecular structure as that underlying the DFT-parameterized ECG model. We demonstrate that our proposed Element-Count-Label (ECL) representation, which augments Martini beads with explicit stoichiometric data, significantly improves chemical generalization across diverse polymer chemistries. However, we find that even with improved chemical resolution, the model cannot recover electronic property distributions that are absent from the configurational space sampled by the CG force field. These results demonstrate that chemically transferable ECG requires future Martini-like force fields to explicitly preserve quantum chemistry–compatible local molecular structure in addition to thermodynamic and structural fidelity.

Kidder, Katherine M [Department of Chemistry; Univ↗
DOE OSTI2020

Imaging broadband soft X-ray transmission-grating spectrograph for a wavelength range λ > 111 Å

A family of aperiodic Mo/Be multilayer mirrors was designed for maximum uniform reflectivity in the ranges 111 – 138, 111 – 150, 111 – 200 and 111 – 222 Å at normal radiation incidence. The simulations took into account the existence of Mo-on-Be and Be-on-Mo transition layers. It was shown that the reflectivity may be as high as 10% in an octave wavelength range of 111 – 222 Å. We demonstrate the operation of an imaging transmission-grating spectrograph with a broadband Mo/Be multilayer mirror with a uniform reflectivity in the wavelength range 111 – 138 Å synthesised at the Institute for the Physics of Microstructures, RAS. The spectrograph was used to record the line spectra of multiply charged fluorine and magnesium ions from a laser-produced plasma. The role of the grating support structure in the formation of spectral source images is discussed. The spatial resolution of 50 μm is demonstrated. (laser applications and other topics in quantum electronics)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Improving Charge Transport and Environmental Stability of Carbohydrate-Bearing Semiconducting Polymers in Organic Field-Effect Transistors

Semiconducting polymers offer synthetic tunability, good mechanical properties, and biocompatibility, enabling the development of soft technologies previously inaccessible. Side-chain engineering is a versatile approach for optimizing these semiconducting materials, but minor modifications can significantly impact material properties and device performance. Carbohydrate side chains have been previously introduced to improve the solubility of semiconducting polymers in greener solvents. Despite this achievement, these materials exhibit suboptimal performance and stability in field-effect transistors. In this work, structure–property relationships are explored to enhance the device performance of carbohydrate-bearing semiconducting polymers. Toward this objective, a series of isoindigo-based polymers with carbohydrate side chains of varied carbon-spacer lengths is developed. Material and device characterizations reveal the effects of side chain composition on solid-state packing and device performance. With this new design, charge mobility is improved by up to three orders of magnitude compared to the previous studies. Processing–property relationships are also established by modulating annealing conditions and evaluating device stability upon air exposure. Notably, incidental oxygen-doping effects lead to increased charge mobility after 10 days of exposure to ambient air, correlated with decreased contact resistance. Bias stress stability is also evaluated. This work highlights the importance of understanding structure–property relationships toward the optimization of device performance

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reversible motions and disordered structure of soft particles in amorphous solids

In amorphous solids, soft vibrational modes derived from normal mode analysis can be utilized to identify the soft particles that are prone to irreversible rearrangements. However, the normal mode analysis approach cannot explain why the spatial distributions of clustered soft particles do not change over time. We define a softness parameter based on the vibrational density of states calculated directly from molecular dynamics simulations with both the harmonic vibrations and anharmonic relaxations being properly captured at finite temperatures. This parameter spontaneously correlates with the real space atomic motions and the dynamics heterogeneity. Using the softness parameter, we show that the softest particles are confined within rigid cages. These particles keep rearranging reversibly without long-range diffusion. The moderately soft particles rearrange irreversibly, and the hard particles mainly participate in vibrations without rearrangement. Here, we also show that the soft particles form locally disordered structures, while the hard particles present strong ordering. These findings confirm the defective nature of soft particles, and provide insights on the nature of softness as the ability to rearrange, but not necessarily irreversibly.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ironsand (Titanomagnetite-Titanohematite): Chemistry, Magnetic Properties and Direct Applications for Wireless Power Transfer

Ironsand is an abundant and inexpensive magnetic mineral resource. However, the magnetic properties of unprocessed ironsand are often inadequate for any practical applications. In this work, the applicability of ironsand for use as a component in a soft magnetic composite for large-scale inductive power transfer applications was investigated. After magnetic separation, the chemical, structural and magnetic properties of ironsand sourced from different locations were compared. Differences observed in the DC magnetic properties were consistent with changes in the chemical compositions obtained from X-ray Absorption Near-Edge Spectroscopy (XANES), which suggests varying the titanohematite to titanomagnetite content. Increased content in titanomagnetite and magnetic permeability correlated well with the total Fe content in the materials. The best-performing ironsand with the highest permeability and lowest core losses was used alongside Mn,Zn-Ferrite particles (ranging from ~100 μm to 2 mm) to fabricate toroid cores with varying magnetic material loading. It was shown that ironsand can be used to replace up to 15 wt.% of the magnetic materials with minimal impact on the composite magnetic performance, thus reducing the cost. Ironsand was also used as a supporting material in a single-rail wireless power transfer system, effectively increasing the power transfer, demonstrating potential applications to reduce flux leakage.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Crystalline Order Yet Glass-Like Heat Transport Driven by Hidden Local Distortions as the Structural Origin of Ultralow Thermal Conductivity in AgErTe 2

Given their rich chemical diversity and the interplay among the p-, d-, and f-orbitals of chalcogens, transition metals, and lanthanides, respectively, rare-earth transition-metal chalcogenides exhibit a wide variety of structural, magnetic, and transport phenomena. As a result, they form a particularly appealing platform for investigating structure–property relationships, emergent electronic and magnetic behaviors, and thermal transport. Here we investigate AgErTe 2 as a model system to understand phonon-glass behavior in ordered crystalline solids, which establishes the design principles for thermal barrier coatings and next-generation thermoelectrics. The local bonding asymmetry and lattice softness suppress the inherently low lattice thermal conductivity, resembling the characteristics of amorphous materials. This suppression is significantly influenced by local off-centering of Ag atoms, which breaks lattice periodicity while maintaining global crystallinity. The presence of antibonding states just below the Fermi level, arising from Ag 4d and Te 5p orbital interactions, leads to lattice softening and destabilizes ideal tetrahedral coordination, resulting in a pseudo Jahn–Teller distortion. Furthermore, the coexistence of weaker, more polarizable Ag–Te bonds and stronger Er–Te bonds creates a complex vibrational landscape enriched with low-frequency modes and enhanced phonon scattering. A pronounced disparity in interatomic force constants gives rise to highly localized, low-energy optical phonons linked to Ag rattling. These flat vibrational modes exhibit strong coupling with transverse acoustic phonons, resulting in ultrashort phonon lifetimes and mean free paths approaching interatomic distances. These features collectively enhance phonon scattering across a broad range of length and energy scales. This work offers a framework for engineering suppressed thermal conductivity in crystalline systems without the introduction of alloying elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics–Informed Neural Networks

The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field heterogeneous elastic properties of soft materials using traditional engineering approaches is fundamentally challenging due to difficulties in estimating local stress fields. Recently, there has been a growing interest in data-driven models for learning full-field mechanical responses, such as displacement and strain, from experimental or synthetic data. However, research studies on inferring full-field elastic properties of materials, a more challenging problem, are scarce, particularly for large deformation, hyperelastic materials. Here, a physics-informed machine learning approach is proposed to identify the elasticity map in nonlinear, large deformation hyperelastic materials. This study reports the prediction accuracies and computational efficiency of physics-informed neural networks (PINNs) in inferring the heterogeneous elasticity maps across materials with structural complexity that closely resemble real tissue microstructure, such as brain, tricuspid valve, and breast cancer tissues. Further, the improved architecture is applied to three hyperelastic constitutive models: Neo-Hookean, Mooney Rivlin, and Gent. Furthermore, the improved network architecture consistently produces accurate estimations of heterogeneous elasticity maps, even when there is up to 10% noise present in the training data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Performance evaluation of the USGS velocity model for the San Francisco Bay Area

In this study, we evaluated the performance of the United States Geological Survey velocity model developed for the San Francisco Bay Area (SFBA), version 21.1. The evaluation was performed through high-resolution three-dimensional physics-based ground motion simulations of seven small-magnitude earthquakes (ranging from magnitude 3.8 to 4.4) that occurred on the eastern side of the San Francisco Bay. The simulations were performed in the frequency range from 0 to 5 Hz with a minimum shear-wave velocity of 250 m/s, which allowed the capture of wave propagation effects of the near-surface soft materials that characterize local basins. Based on the direct comparison of Fourier amplitude spectra between recorded and simulated ground motions for more than 250 stations, we found that the velocity model generally performs well in the frequency range of 0.2–5 Hz. The median value of the Fourier amplitude residuals was found to be near zero for all seven earthquakes. The slight over-prediction of 0.2 log-natural units at frequencies above 3 Hz in our simulations was attributed to the potentially inaccurate representation of the source radiation pattern by a double-couple point source model, and simple representation of shallow small-scale underground structural complexity in the velocity model. Maps of spectral amplitude differences between the simulated and recorded data were used to identify areas responsible for systematic ground motion over-predictions or under-predictions. For example, while some sub-domains over soft sediments show over-prediction patterns, the block east of the Hayward fault is prone to exhibit patterns of under-prediction. These maps can be used to guide future refinements of the SFBA velocity model. Since our simulation methodology allows for the decoupling of the source and wave propagation effects, the ground motion data generated by our simulations can also be used to quantify the epistemic uncertainty due to the velocity model, in empirically based ground motion estimates for the SFBA.

58 GEOSCIENCES↗
DOE OSTI2024

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Filled Elastomers: Mechanistic and Physics-Driven Modeling and Applications as Smart Materials

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction (ϕ) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer–particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For ϕ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer–particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

2D in-Plane Ordered MXene Nanosheets Derived from (Mo 2/3 Er 1/3 ) 2 AlC Rare-Earth i-MAX for Energy Storage Applications

MXenes have become one of the most versatile families of two-dimensional (2D) materials due to their high conductivity, hydrophilicity, and remarkable electrochemical performance. This has stimulated intense efforts to design and synthesize MXenes, including structurally unique in-plane ordered 2D MXenes called i-MXenes. Here, we have synthesized the quaternary rare earth (RE)-based i-MAX phase (Mo 2/3 Er 1/3 ) 2 AlC using an arc melting method, and the corresponding 2D i-MXene was then obtained through a LiF/HCl soft etching process. Literature studies have shown that Al and the RE element are etched out during the etching process, leading to the formation of pure vacancy-ordered Mo1.33C 2D i-MXene. However, our investigation reveals that upon exposure to a fluorine solution, the i-MAX phase forms RE fluoride impurities, which are challenging to remove through HCl−DI water washing and persist in the final product, resulting in impure Mo 1.33 C@Er i-MXene. These results were confirmed by various characterizations such as X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, and scanning transmission electron microscopy. Although the Mo 1.33 C@Er electrode showed a 24-fold increase in specific capacitance compared to its parent i-MAX phase, it still exhibited a high charge-transfer resistance arising from the insulating nature of RE fluoride byproducts, which adversely influence the overall capacitance behavior of the synthesized 2D Mo 1.33 C@Er i-MXenes. This study contributes to identifying pathways for the preparation of pure 2D i-MXenes from RE-based i-MAX phases and developing improved synthesis methods. With additional process optimization, the 2D i-MXene holds a strong potential for electrochemical energy storage applications. Additionally, the electronic structures of Mo 1.33 C were theoretically studied using first-principles density functional theory calculations, which revealed that pristine Mo 1.33 C is metallic, and this metallic nature is preserved even with −O, −F, and mixed functionalization.

chemical structure↗
DOE OSTI2023

C–H Functionalization of Polyolefins to Access Reprocessable Polyolefin Thermosets

Upcycling plastic waste into reprocessable materials with performance-advantaged properties would contribute to the development of a circular plastics economy. Here, we modify branched polyolefins and postconsumer polyethylene through a versatile C–H functionalization approach using thiosulfonates as a privileged radical group transfer functionality. Cross-linking the functionalized polyolefins with polytopic amines provided dynamically cross-linked polyolefin networks enabled by associative bond exchange of diketoenamine functionality. A combination of resonant soft X-ray scattering and grazing incidence X-ray scattering revealed hierarchical phase morphology in which diketoenamine-rich microdomains phase-separate within amorphous regions between polyolefin crystallites. The combination of dynamic covalent cross-links and microphase separation results in useful and improved mechanical properties, including a ~4.5-fold increase in toughness, a reduction in creep deformation at temperatures relevant to use, and high-temperature structural stability compared to the parent polyolefin. The dynamic nature of diketoenamine cross-links provides stress relaxation at elevated temperatures, which enabled iterative reprocessing of the dynamic covalent polymer network with little cycle-to-cycle property fade. Finally, the ability to convert polyolefin waste into a reprocessable thermoformable material with attractive thermomechanical properties provides additional optionality for upcycling to enable future circularity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Generating forces in confinement via polymerization

Understanding how to produce forces using biomolecular building blocks is essential for the development of adaptive synthetic cells and living materials. Here we ask whether a dynamic polymer system can generate deformation forces in soft shells by pure self-assembly, motivated by the fact that biological polymer networks like the cytoskeleton can exert forces, move objects, and deform membranes by simply growing, even in the absence of molecular motors. We address this question by investigating polymer force generation by varying the release rate, the structure, and the interactions of self-assembling monomers. First, we develop a toy computational model of polymerization in a soft elastic shell that reveals the emergence of spontaneous bundling which enhances shell deformation. We then extend our model to account more explicitly for monomer binding dynamics. We find that the rate at which monomers are released into the interior of the shell is a crucial parameter for achieving deformation through polymer growth. Lastly, we demonstrate that the introduction of multivalent particles that can join polymers can either improve or impede polymer performance, depending on the amount and on the structure of the multivalent particles. Our results provide guidance for the experimental realization of polymer systems that can perform work at the nanoscale, for example through rationally designed self-assembling proteins or nucleic acids.

Osmanović, Dino [University of California at Los A↗
DOE OSTI2022

Self-equilibrated backstresses induce compensation between hardening and softening: Micromechanical and microstructural features

For crystal plasticity formulation neglecting the strain gradients at the dislocation scale, backstresses are necessary to satisfy the mesoscopic stress equilibrium and strain compatibility requirements. Backstresses in a material point and those between neighboring points are treated separately. Physically backstresses can dynamically induce either hardening or softening effects to adjust the dislocation hardening of slip systems, whereas the sum of the stresses resulting in backstresses in the representative volume element (RVE) is zero. Backstress hardening suppresses certain slip activities, while backstress softening triggers excess dislocations. A two-phase brass is studied. Backstresses make the hard phase deform smaller and the soft phase deform more than those without employing backstresses in a model. In the former, more homogeneous lattice strain and higher yield stress are obtained. Backstress has limited effects on the evolution of the critical resolved shear stress and crystallographic texture. Furthermore, it is a major cause of the banded structures featuring sharp crystallographic contrasts which are not parallel to the slip planes. Tests indicate that backstress induces a serrated behavior at the early stages of deformation and induces the geometrically necessary bands (GNBs), which are parallel to the macroscopic axes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding the Mn dissolution mechanism in rock salt-type Li 4 Mn 2 O 5 cathodes

For the first time, a detailed exploration of Mn dissolution in disordered rock salt (DRX) Li 4 Mn 2 O 5 is presented. Herein, we apply a suite of synchrotron and lab scale X-ray techniques to both the cathode and the separator harvested from pristine, charged, or cycled lithium half-cells containing the disordered rock salt (DRX) material Li 4 Mn 2 O 5 , in order to understand Mn dissolution processes throughout charging and discharging. Previous research has hypothesized two concurrent effects that may drive Mn dissolution in cells during cycling: acid-induced disproportionation of Jahn–Teller active Mn 3+ and structural rearrangement of the cathode lattice. Through depth probing of the Mn oxidation state in both the cathode and separator via soft X-ray absorption spectroscopy (XAS), hard XAS, and X-ray photoelectron spectroscopy (XPS) in progressive states-of-charge, as well as extended X-ray absorption fine structure (EXAFS) analysis of the local Mn environment, the primary driving force of Mn dissolution is determined to be high-voltage structural rearrangement above 4.2 V. Mn dissolution is, additionally, a main source of capacity fade in Li 4 Mn 2 O 5 DRX cells, which retain only 59% capacity after 20 cycles.

Theibault, Monica↗