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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

1D Magnetic MX 3 Single-Chains (M = Cr, V and X = Cl, Br, I)

Magnetic materials in reduced dimensions are not only excellent platforms for fundamental studies of magnetism, but they play crucial roles in technological advances. The discovery of intrinsic magnetism in monolayer 2D van der Waals systems has sparked enormous interest, but the single-chain limit of 1D magnetic van der Waals materials has been largely unexplored. This paper reports on a family of 1D magnetic van der Waals materials with composition MX 3 (M = Cr, V, and X = Cl, Br, I), prepared in fully-isolated fashion within the protective cores of carbon nanotubes. Atomic-resolution scanning transmission electron microscopy identifies unique structures that differ from the well-known 2D honeycomb lattice MX 3 structure. Density functional theory calculations reveal charge-driven reversible magnetic phase transitions.

1D materials↗
DOE OSTI2024

Viability of Additively Manufactured Electrodes for Lithium-Ion Batteries

As the global economy becomes increasingly electrified, the demand for batteries and energy storage is expected to rise significantly, particularly in the transportation and electricity sectors. Lithium-ion batteries (LIBs) are currently the most advanced and widely used technology in this field. Traditionally, LIBs are manufactured using simple 2D planar geometries to maximize production efficiency and minimize costs. However, this approach limits energy density due to the restricted design flexibility of the electrodes. Additive manufacturing (AM) offers a promising solution to enhance the energy density and efficiency of LIBs by enabling the design of architectures that reduce diffusive losses and allow for a greater amount of active material to be incorporated within the same device footprint, thereby minimizing the use of inactive materials. Different AM techniques come with their own set of limitations, including printing speed, material compatibility, and scale, which must be considered when designing electrodes. Scalable and cost-effective methods are particularly important for electric vehicle batteries, while achieving higher energy densities in microbatteries is crucial for the miniaturization of wearable electronics and medical devices. Here, in this study, we simulate various 3D porous electrode designs for LIBs using graphite and nickel manganese cobalt oxide (NMC) electrodes. These designs are selected to represent structures that could be produced using different AM techniques, such as direct ink writing, fused deposition modeling, and stereolithography. Our results indicate that at higher charging rates and increased areal mass loading, 3D structures can outperform traditional 2D electrodes, although the benefits may diminish with more complex designs that are harder to manufacture. The observed gains in energy density are attributed to improved electrode utilization and reduced diffusive energy losses. This comprehensive analysis of structure–performance relationships will provide valuable insights to guide future research on 3D designs, material selection, and AM techniques for additively manufactured battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2024

High-throughput screening of 2D materials identifies p-type monolayer WS2 as potential ultra-high mobility semiconductor

Abstract 2D semiconductors offer a promising pathway to replace silicon in next-generation electronics. Among their many advantages, 2D materials possess atomically-sharp surfaces and enable scaling the channel thickness down to the monolayer limit. However, these materials exhibit comparatively lower charge carrier mobility and higher contact resistance than 3D semiconductors, making it challenging to realize high-performance devices at scale. In this work, we search for high-mobility 2D materials by combining a high-throughput screening strategy with state-of-the-art calculations based on the ab initio Boltzmann transport equation. Our analysis singles out a known transition metal dichalcogenide, monolayer WS 2 , as the most promising 2D semiconductor, with the potential to reach ultra-high room-temperature hole mobilities in excess of 1300 cm 2 /Vs should Ohmic contacts and low defect densities be achieved. Our work also highlights the importance of performing full-blown ab initio transport calculations to achieve predictive accuracy, including spin–orbital couplings, quasiparticle corrections, dipole and quadrupole long-range electron–phonon interactions, as well as scattering by point defects and extended defects.

Chemistry↗
DOE OSTI2025

Emergent Above-Gap Photoluminescence in Molecularly Engineered Hybrid Bilayer Crystals

Bilayer crystals, built by stacking two-dimensional (2D) covalent monolayers, give rise to coupled excitonic states whose properties are constrained by fixed lattice symmetry and orientation. Replacing one covalent monolayer with a 2D molecular crystal––held together by non-covalent forces––overcomes this limitation, as molecular functional groups afford tunable in-plane lattice geometry, intermolecular spacing, and interlayer coupling, providing a powerful knob for exciton engineering. Here, in this study, we report four-atom-thick hybrid bilayer crystals (HBCs) synthesized by directly growing single-crystalline PDI molecular crystal atop WS 2 monolayers, which exhibit a robust photoluminescence (PL) peak 120 meV above the WS 2 optical band gap alongside a belowgap emission. Both peaks display strong polarization anisotropy—nearing unity for the above-gap emission—and maintain a perfectly linear power-law dependence up to an excitation density of ~10 7 mW/cm 2 , indicative of coexisting localized and delocalized excitonic states. Substituting PDI with a PTCDA monolayer on WS 2 fully quenches PL, demonstrating molecular control over excitonic emission. Lattice scale ab initio GW and GW-BSE calculations reveal a significantly hybridized bilayer band structure in PDI/WS 2 that supports interlayer excitonic species both above and below the WS 2 gap with strong polarization anisotropy, in excellent agreement with experiment. Our work introduces a molecule-based bilayer platform for the bottom-up design and control of excitonic phenomena in atomically thin optoelectronic and quantum materials.

2D materials↗
DOE OSTI2022

Metal-Confined Synthesis of ZnS 2 Monolayer Catalysts for Dinitrogen Electroreduction

Atomically thin two-dimensional (2D) materials are of great significance in catalytic, energy storage, and electronic devices. So far, such materials are limited to several categories with layered structures. Herein, we predict an unusual atomically thin ZnS2 monolayer and exploit a metal-confined chemical vapor deposition strategy for the successful preparation of such an unprecedented 2D material, where a sulfide monolayer was first grown on metal nanosheets to form a sulfide/metal/sulfide sandwich structure, and then, the metal core was etched out to obtain freestanding sulfide monolayers. As shown in this work, the ZnS 2 monolayer possesses unique electron-deficient properties related to the atomic structure and exhibits high catalytic activity for dinitrogen electroreduction. Our work will enable creating 2D TMD materials that were previously inexistent or inaccessible.

2D Materials↗
DOE OSTI2023

A parametric finite element study for determining burst strength of thin and thick-walled pressure vessels

To accurately predict the burst strength of both thin and thick-walled pressure vessels (PVs), a parametric study of PV burst strength was performed for a wide range of vessel geometries and materials using elastic-plastic finite element analysis (FEA). A valid FEA model was established through a detailed study of 2D versus 3D FEA models, the critical stress failure criterion versus the limit load criteria, and the thick-wall effect on the FEA simulations. Here, the results show that the stresses and strains at the mean diameter, rather than outside diameter, determines a more accurate burst strength for both thin and thick-walled PVs. On this basis, a parametrized FEA script using the ABAQUS Python application programming interface (API) was used to create a large database of PV burst strengths for a variety of vessel geometries and materials, demonstrating that Python scripting is a powerful technique for performing parametric studies or generating large databases. From the FEA results, using the regression method, a new burst pressure model was developed as a function of the vessel geometry (D/t ratio) and material properties (UTS and n). As validated by a large number of full-scale burst test data, the proposed burst model can very accurately predict the burst strength for both thin and thick-walled PVs.

42 ENGINEERING↗
DOE OSTI2021

Heterostructured Lepidocrocite Titanate-Carbon Nanosheets for Electrochemical Applications

Lepidocrocite-type titanates that reversibly intercalate sodium ions at low potentials (~0.6 V vs Na/Na + ) are promising anode candidates for sodium-ion batteries. However, large amounts of carbon additives are often used to improve their electrical conductivity and overcome poor cycling performance in the electrode composites. To ameliorate electronic transport issues of lepidocrocite titanate (K 0.8 Ti 1.73 Li 0.27 O 4 , KTL) in sodium-ion batteries, we have designed and synthesized heterostructures of exfoliated lepidocrocite-type titanium oxide (LTO) nanosheets with alternating carbon layers via a solution-based self-assembly approach. Positively charged dopamine (Dopa) was used as the carbon precursor and intercalated between negatively charged exfoliated titania nanosheets through electrostatic interaction. Dopa-intercalated LTO was then annealed under argon to form conductive carbon layers between titania sheets. The carbon content in the heterostructures was controlled by modifying the self-assembly conditions (i.e., pH, stirring duration, and Dopa-to-LTO ratio). Electrodes were prepared using carbonized heterostructures (LTO-C) without adding more carbon to the composites and tested in sodium half-cell configurations. Further, higher capacities and improved capacity retention over 250 cycles and lower impedance were observed, as the carbon content of LTO-C heterostructures was increased from 0% (LTO nanosheets) to 30%. These results indicate that the self-assembly approach for 2D heterostructured electrode materials is a promising strategy to overcome electronic transport limitations of layered transition-metal oxides and improve their electrochemical performance for next-generation energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2022

Simple Approximation for the Ideal Reference State of Gases Adsorbed on Solid-State Surfaces

Reference states are useful as models for facilitating calculations of equilibrium constants, and they may also serve as standard states that are convenient for organizing and tabulating thermodynamic data; however, standard state conventions and appropriate reference states for adsorbed species have received less attention than those for pure substances and solutes. Here, we compare seven choices of reference states for calculations of equilibrium constants and transition state theory rate constants for flat surfaces, in particular (1) an ideal 2D harmonic oscillator, (2) an ideal rigid-molecule harmonic oscillator, (3) an ideal 2D harmonic oscillator with separable surface modes, (4) a 2D ideal gas, (5) an ideal 2D hindered translator, (6) an ideal 2D hindered translator with lowest-order barriers, and (7) a simple ideal 2D hindered translator proposed in this work. The advantage of models 5–7 is that they can treat both mobile and localized adsorbates in a consistent way, whereas models 1–3 are only appropriate for localized adsorbates, and model 4 is only appropriate for a freely translating adsorbate. Furthermore, models 6 and 7 reduce the computational cost without the user having to calculate barrier heights for diffusion. An advantage of the simple ideal 2D hindered translator is that it has a physical high-temperature limit. We also propose a reference state for nonflat surfaces. Here, the user is encouraged to choose a reference state based on the appropriateness of the model and the practicality of the calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Quantum kinetic modeling of KEEN waves in a warm-dense regime

We report the first fully kinetic, quantum study of kinetic electrostatic electron nonlinear (KEEN) waves, showing that quantum diffraction systematically erodes the classical trapping mechanism, narrows harmonic locking to the fundamental, and hastens post-drive decay. Electrons are evolved with a second-order Strang-split 1D1V Wigner–Poisson solver that couples conservative semi-Lagrangian WENO advection to an analytic Fourier space update for the non-local Wigner term, while ions remain classical. We focus on collisionless dynamics in a weakly coupled regime, providing a controlled baseline before collisional extensions. Short, frequency-tuned ponderomotive pulses drive KEEN formation in a uniform Maxwellian plasma; as the dimensionless quantum parameter H rises from the classical limit to values relevant to warm-dense matter, doped semiconductors, and 2D electron systems, the drive threshold increases, higher harmonics are damped, trapped electron vortices diffuse, and the subplasma electrostatic energy relaxes to a lower stationary level, as confirmed by continuous wavelet analysis. These microscopic changes carry macroscopic weight. Ignition-scale capsules now compress matter to regimes where the electron de Broglie wavelength rivals the Debye length, making classical kinetic descriptions insufficient. By extending KEEN physics into this quantum domain, our results offer a potential diagnostic of non-equilibrium electron dynamics for next-generation inertial-confinement designs and high-energy-density platforms, indicating that predictive fusion modeling may benefit from the integration of kinetic fidelity with quantum effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Remote Epitaxial Growth of Compound Semiconductors through Graphene

Epitaxial growth has been widely used for high-quality growth of crystalline materials. However, epitaxial growth techniques usually require lattice match and similar thermal expansion coefficient between growth material and substrate, which blocks this growth technique from wide applicability. Recently, van der Waals (vdW) epitaxy has been demonstrated that allows to relax the limitation of epitaxial growth. vdW epitaxy on layered or two-dimensional (2D) materials is mediated by weak vdW interactions. In addition to these interactions, a substrate below 2D materials also plays a role to intervene in the epitaxial growth process, leaving room to realize a novel epitaxial growth process: remote epitaxy. Potential fluctuation—the difference between potential energy maxima and minima along the surface of the substrate—is influenced by this remote interaction; the fluctuation is predominant over the vdW force, due to the atomic thickness of 2D materials. The remote interactions can be controlled by modulation of polarities of 2D materials and epitaxy materials. Polar-material-based heterostructure, such as GaAs, InP, GaP and GaN with their substrate sandwiching 2D materials, enables the semiconductor film to be exfoliated from the underlying substrates through the 2D materials. This process is expected to open a novel avenue for the field of non-silicon electronics and photonics, where the ability to re-use graphene-coated substrates allows savings on the high cost of non-silicon substrates.

Lee, Kyusang↗
DOE OSTI2023

Quantum Search Approaches to Sampling-Based Motion Planning

In this paper, we present a novel formulation of traditional sampling-based motion planners as database-oracle structures that can be solved via quantum search algorithms. We consider two complementary scenarios: for simpler sparse environments, we formulate the Quantum Full Path Search Algorithm (q-FPS), which creates a superposition of full random path solutions, manipulates probability amplitudes with Quantum Amplitude Amplification (QAA), and quantum measures a single obstacle free full path solution. For dense unstructured environments, we formulate the Quantum Rapidly Exploring Random Tree algorithm, q-RRT, that creates quantum superpositions of possible parent-child connections, manipulates probability amplitudes with QAA, and quantum measures a single reachable state, which is added to a tree. As performance depends on the number of oracle calls and the probability of measuring good quantum states, we quantify how these errors factor into the probabilistic completeness properties of the algorithm. We then numerically estimate the expected number of database solutions to provide an approximation of the optimal number of oracle calls in the algorithm. We compare the q-RRT algorithm with a classical implementation and verify quadratic run-time speedup in the largest connected component of a 2D dense random lattice. We conclude by evaluating a proposed approach to limit the expected number of database solutions and thus limit the optimal number of oracle calls to a given number.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Presentation of antigen to T lymphocytes by non-immune B-cell hybridoma clones: evidence for specific and non-specific presentation

Non-immune SJL (H-2s) spleen cells were fused with non-secreting, non-antigen presenting (H-2d) Balb/c 653-myeloma cells and the hybridomas were cloned by two limiting dilutions. The resulting hybrid B-cell clones were tested for their antigen presentation capability to SJL T-cell lines that were specific for either lysozyme or myoglobin. In proliferative assays, 53% of the antigen presenting B-cell clones presented both myoglobin and lysozyme (general presenters) while the other 47% presented specifically either myoglobin or lysozyme (specific presenters). The ability to selectively present either myoglobin or lysozyme indicates that antigen presentation at the clonal level can be specific or non-specific depending on the particular B-cell clone.

B-Lymphocytes/immunology↗
NASA NTRS1988

Presentation of antigen to T lymphocytes by non-immune B-cell hybridoma clones: evidence for specific and non-specific presentation

Non-immune SJL (H-2s) spleen cells were fused with (H-2d) Balb/c 653-myeloma cells and the hybridomas were cloned by two limiting dilutions. The resulting hybrid B- cell clones were tested for their antigen presentation capability to SJL T-cell lines that were specific for either lysozyme or myoglobin. In proliferative assays, 53% of the antigen presenting B-cell clones were able to present both myoglobin and lysozyme (general presenters) while the other 47% presented specifically either myoglobin or lysozyme (specific presenters). The ability to selectively present either myoglobin or lysozyme indicates that antigen presentation at the clonal level can be specific or non-specific depending on the particular B-cell clone.

T-Lymphocytes/immunology↗
NASA NTRSDate not supplied

Using XR for Improving Scientific Discovery With Numerical Weather Models

Earth science (ES) digital twins will help us understand the complex interactions and interrelationships that make up our Earth system and the impacts of earth science phenomena on it. Our work addresses two underdeveloped areas in current ES digital twin work: improving the understanding and interaction with ES model outputs by using Virtual and Mixed Reality (XR) tools and improving the non-intuitive mapping of continuous ES natural phenomena to gridded reference frames in current numerical models. Traditionally, scientists working on ES view and analyze the results of calculated or measured observables with static 1-dimensional (1D), 2D or 3D plots displayed on flat computer screens or paper. Using such limited mediums, it can be very difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. In addition, numerical models, such as the NASA Goddard Earth Observing System (GEOS) ES model, are almost exclusively formulated, visualized and analyzed in an Eulerian reference frame with fixed grid points in space and time. However, ES phenomena such as convective clouds, hurricanes and wildfire smoke plumes are visualized and analyzed in a Lagrangian reference frame: therefore it is often difficult and unnatural to understand these phenomena in relation to each other, visualized either in an Eulerian or Lagrangian context. In 3D visualizations, data generally takes one of three forms: gridded (e.g., voxelized) data, where space is divided into regions; point clouds, where data is represented as a set of points; and meshes, where objects are rendered as surfaces composed of small polygons (usually triangles). A gridded, Eulerian reference frame has been the default representation for the 2D visual analysis of atmospheric data in part because the numerical methods used to generate atmospheric model data in the first place use a gridded approach, with equations defining the relationships between the physical variables in each of a grid's cells across successive timesteps. In our work, we are particularly interested in data from GEOS. Another reason why gridded representations tend to be used for visualizing data from such models is because trajectories are difficult to interpret from representations on 2D surfaces, due to line-of-sight ambiguity. Instead of a fixed grid from GEOS, we embed a trajectory model to simulate particles' movement throughout a GEOS run. We then ingest these particle trajectories as animated point clouds with a NASA open source XR toolkit, the Mixed Reality Exploration Toolkit (MRET), and merge GEOS data with ES phenomena data onto one combined visualization that the user can intuitively interact with. Efficient rendering of arbitrarily large point clouds is an ongoing challenge being addressed by the computer science community, with the GPU-based optimizations and efficient GPU memory utilization a common theme of recent advances, especially for XR, where sustained high frame rate is mandatory to save the user from suffering due to simulation sickness. In this work, we describe and evaluate our progress in choosing and implementing appropriate methods for rendering arbitrarily large point clouds within MRET for XR. While tracking the XR headset enables the immersion of a user within a 3D scene of a data visualization, tracking of XR handheld controllers or user’s hands enables us to implement intuitive user interactions with the visualized datasets. Conventional tools require a user working with an ES visualization to conduct many interactions to commit their intended selections or manipulations with a visualized dataset; for example to specify a set of points in 3D space. Doing so in a 2D flat screen interface has traditionally required specifying a set of points in three distinct 2D coordinate systems (XY, XZ, and YZ), which is cumbersome. In other scientific domains, it has been shown that specifying or selecting a location or volume in XR using handheld controllers or tracked hands allows for greater speed and accuracy. We anticipate the same will hold true for atmospheric data, and we will share initial results of measuring the utility of such an interface. Notably, as the data being visualized is generated by GEOS as a prediction based on initial conditions, an intended application of our tool is to serve as part of an iterative feedback loop. Through XR, a scientist will review and manipulate a GEOS model run, modifying the conditions as needed to do subsequent runs of GEOS. Thereby, XR-based improvements to speed and accuracy of 3D tagging of points minimizes the effort required by both the scientist and the computer cluster conducting the necessary calculations.

Thomas Grubb↗
DOE OSTI2023

State of the Art of Molecular Visualization in Immersive Virtual Environments

Abstract Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head‐mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Carrier control in Sn–Pb perovskites via 2D cation engineering for all-perovskite tandem solar cells with improved efficiency and stability

All-perovskite tandem solar cells are promising for achieving photovoltaics with power conversion efficiencies above the detailed balance limit of single-junction cells, while retaining the low cost, light weight and other advantages associated with metal halide perovskite photovoltaics. However, the efficiency and stability of all-perovskite tandem cells are limited by the Sn-Pb-based narrow-bandgap perovskite cells. Here we show that the formation of quasi-two-dimensional (quasi-2D) structure (PEA) 2 GAPb 2 I 7 from additives based on mixed bulky organic cations phenethylammonium (PEA+) and guanidinium (GA+) provides critical defect control to substantially improve the structural and optoelectronic properties of the narrow-bandgap (1.25 eV) Sn-Pb perovskite thin films. Additionally, this 2D additive engineering results in Sn-Pb-based absorbers with low dark carrier density (~1.3 x 10 14 cm -3 ), long bulk carrier lifetime (~9.2 us) and low surface recombination velocity (~1.4 cm s -1 ), leading to 22.1%-efficient single-junction Sn-Pb perovskite cells and 25.5%-efficient all-perovskite two-terminal tandems with high photovoltage and long operational stability.

14 SOLAR ENERGY↗
DOE OSTI2024

Defects and Defect Engineering of Two-Dimensional Transition Metal Dichalcogenide (2D TMDC) Materials

As layered materials, transition metal dichalcogenides (TMDCs) are promising two-dimensional (2D) materials. Interestingly, the characteristics of these materials are transformed from bulk to monolayer. The atomically thin TMDC materials can be a good alternative to group III–V and graphene because of their emerging tunable electrical, optical, and magnetic properties. Although 2D monolayers from natural TMDC materials exhibit the purest form, they have intrinsic defects that limit their application. However, the synthesis of TMDC materials using the existing fabrication tools and techniques is also not immune to defects. Additionally, it is difficult to synthesize wafer-scale TMDC materials for a multitude of factors influencing grain growth mechanisms. While defect engineering techniques may reduce the percentage of defects, the available methods have constraints for healing defects at the desired level. Thus, this holistic review of 2D TMDC materials encapsulates the fundamental structure of TMDC materials, including different types of defects, named zero-dimensional (0D), one-dimensional (1D), and two-dimensional (2D). Moreover, the existing defect engineering methods that relate to both formation of and reduction in defects have been discussed. Finally, an attempt has been made to correlate the impact of defects and the properties of these TMDC materials.

2D materials↗
DOE OSTI2026

Visualizing the impact of quenched disorder on 2D electron Wigner solids

Electron Wigner solids (WSs) provide an ideal system for understanding the competing effects of electron–electron and electron–disorder interactions, a central unsolved problem in condensed matter physics. Progress in this topic has been limited by a lack of single-defect-resolved experimental measurements as well as accurate theoretical tools to enable realistic experiment/theory comparison. Here, in this study, we overcome these limitations by combining atomically resolved scanning tunnelling microscopy (STM) with neural-quantum-state quantum Monte Carlo (NQS-QMC) simulation of disordered 2D electron WSs to discover new disorder-induced physical regimes of correlated electron behaviour. STM was used to image the electron density (n e )-dependent evolution of electron WSs in gate-tunable bilayer MoSe 2 (BL-MoSe 2 ) devices with varying long-range (n LR ) and short-range (n SR ) disorder densities. These images were compared with NQS-QMC simulations using realistic disorder maps extracted from experiment, thus allowing the roles of different disorder types to be disentangled. We identify two distinct physical regimes for disordered electron WSs that depend on n SR . For n SR ≲ n e , the WS behaviour is dominated by long-range disorder and features extensive mixed solid–liquid phases, a new type of local re-entrant melting/crystallization and prominent Friedel oscillations. By contrast, when n SR ≫ n e , these features are suppressed and a more robust amorphous WS phase emerges that persists to higher n e , highlighting the importance of short-range disorder in this regime. Our work establishes a powerful framework for studying disordered quantum solids through a combined experimental–theoretical approach.

Ge, Zhehao [University of California, Berkeley, CA↗