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DOE OSTI2025

Unveiling the dark matter of riverine dissolved organic matter and its role in molecular chemodiversity

Chemodiversity of riverine dissolved organic matter (DOM) plays a crucial role in global elemental cycles and ecosystem function. However, DOM “dark matter”—molecules without assigned specific formulae—remain unexplored in the interpretation of chemodiversity. Here, we systematically investigated the characteristics and drivers of dark matter and its impacts on DOM chemodiversity using 551 river water and sediment samples. Compared to known matter with specific formulae, dark matter exhibited lower molecular weight and diversity, but higher compositional dissimilarity, with dissolved organic carbon (DOC) as the primary driver. Including dark matter into chemodiversity analysis changed mass, diversity, and compositional dissimilarity of DOM from –10.1 to –0.04 %, –0.7 to 4.9 %, and 0.4 to 28.8 % in waters, and from –17.5 to 5.7 %, –10.5 to 19.2 %, and –22.3 to 33.1 % in sediments, respectively. DOC mediated these ecosystem-dependent effects: lower DOC amplified the effects on chemodiversity in waters, whereas in sediments, the effects shifted from negative to positive with changing DOC. Furthermore, ignoring dark matter would overestimate the regulatory role of DOC on sediment DOM chemodiversity. In conclusion, collectively, our findings clarify the influence of dark matter on DOM chemodiversity assessments across environmental gradients, improving understanding of riverine DOM and refining its analytical framework.

Chemodiversity↗

DOE OSTI2020

Influence of Added Salt on Chain Conformations in Poly(ethylene oxide) Melts: SANS Analysis with Complications

Poly(ethylene oxide) (PEO)-based electrolytes have gained increasing attention in both the rechargeable battery industry and fundamental research, but any influence of the ions on the polymer conformation is not fully understood. Small-angle neutron scattering (SANS) is a powerful means to determine single-polymer chain conformations. We conducted SANS experiments on 50:50 blends of perdeuterated PEO (dPEO) and hydrogenous PEO (hPEO) of two different molecular weights (20 and 40 kDa) doped with two different salts (LiTFSI and LiClO 4 ) at various concentrations. An additional measurement with LiI is also reported. The scattering profiles of salt-doped dPEO/hPEO blends were measured, and the incoherent scattering from dPEO and hPEO doped with salt was measured separately. A strong low q upturn was observed in some of the blends and in the pure dPEO homopolymers. The statistical segment lengths of PEO–salt mixtures were derived using a Kratky analysis. The segment length decreases modestly with increasing amounts of LiTFSI but apparently first increases then decreases with added LiClO 4 . At the highest salt concentration examined (r = [Li+]/[EO] = 0.125), a roughly 10% decrease in the statistical segment length was observed in both LiTFSI and LiClO 4 -doped PEOs, for both molecular weights. This work confirms that added salt causes a contraction of the PEO chain dimensions, but the effect appears slightly weaker than reported recently. Certain difficulties in data analysis are also discussed, including the unexplained low q scattering even in pure deuterated polymers, uncertainties in background subtraction, and inappropriate application of the Debye function.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Charged Biological Membranes Repel Large Neutral Molecules by Surface Dielectrophoresis and Counterion Pressure

Macromolecular crowding is the usual condition of cells. The implications of the crowded cellular environment for protein stability and folding, protein–protein interactions, and intracellular transport drive a growing interest in quantifying the effects of crowding. While the properties of crowded solutions have been extensively studied, less attention has been paid to the interaction of crowders with the cellular boundaries, i.e., membranes. However, membranes are key components of cells and most subcellular organelles, playing a central role in regulating protein channel and receptor functions by recruiting and binding charged and neutral solutes. While membrane interactions with charged solutes are dominated by electrostatic forces, here we show that significant charge-induced forces also exist between membranes and neutral solutes. Using neutron reflectometry measurements and molecular dynamics simulations of poly(ethylene glycol) (PEG) polymers of different molecular weights near charged and neutral membranes, we demonstrate the roles of surface dielectrophoresis and counterion pressure in repelling PEG from charged membrane surfaces. The resulting depletion zone is expected to have consequences for drug design and delivery, the activity of proteins near membrane surfaces, and the transport of small molecules along the membrane surface.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Using leaf and stomatal traits to predict biomass production and water use efficiency in Populus

Climate change is reshaping ecosystems, driving plants to adapt through leaf-trait plasticity that reflects strategies for growth and water use. Predicting biomass production and intrinsic water use efficiency (iWUE) remains challenging because of genetic, taxonomic, and environmental variability. Here, we used eastern cottonwood and Populus hybrids as a model system to test whether easily measurable leaf traits can serve as reliable predictors of performance, and whether adding stomatal and biochemical traits improves predictive power. Across two field sites in Mississippi, leaf mass per area (LMA), biomass production, iWUE, leaf area, and foliar nitrogen ( N %) differed significantly among taxa and sites, while other traits were conserved. Factorial analysis of mixed data (FAMD) revealed distinct clustering of taxa and sites, indicating coordinated variation among leaf and stomatal traits. Pairwise correlations highlighted fundamental trade-offs, with biomass positively related to LMA and petiole length but negatively associated with iWUE, N %, and carbon isotopic ratios (δ 13 C). Leaf temperature and leaf angle varied among taxa and were significantly correlated with LMA and petiole length, suggesting mechanisms of heat dissipation and leaf movability that link simple traits to gas exchange and productivity. Weighted multiple linear regression models explained 80%–91% of variation in biomass production and iWUE. Models using only LMA, petiole length, and stomatal metrics performed nearly as well as those incorporating N %, and δ 13 C, with complex traits adding approximately 10% explanatory power. These results demonstrate that simple morphological traits capture integrated functional trade-offs, while complex traits refine predictions. This tiered approach provides an efficient framework for selecting high-yielding, water-efficient genotypes of Populus and other hardwood species, offering practical pathways to enhance carbon uptake and iWUE under climate change.

biomass production↗

DOE OSTI2025

Optimizing transmit field inhomogeneity of parallel RF transmit design in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) provides a higher signal-to-noise ratio and, thereby, higher spatial resolution. However, UHF MRI introduces challenges such as transmit radiofrequency (RF) field (B+1) inhomogeneities, leading to uneven flip angles and image intensity anomalies. These issues can significantly degrade imaging quality and its medical applications. This study addresses B+1 field homogeneity through a novel deep learning-based strategy. Traditional methods like Magnitude Least Squares (MLS) optimization have been effective but are time-consuming and dependent on the patient’s presence. Recent machine learning approaches, such as RF Shim Prediction by Iteratively Projected Ridge Regression and deep learning frameworks, have shown promise but face limitations like extensive training times and oversimplified architectures. We propose a two-step deep learning strategy. First, we obtain the desired reference RF shimming weights from multi-channel B+1 fields using random-initialized Adaptive Moment Estimation. Then, we employ Residual Networks (ResNets) to train a model that maps B+1 fields to target RF shimming outputs. Our approach does not rely on pre-calculated reference optimizations for the testing process and efficiently learns residual functions. Comparative studies with traditional MLS optimization demonstrate our method’s advantages in terms of speed and accuracy. The proposed strategy achieves a faster and more efficient RF shimming design, significantly improving imaging quality at UHF. This advancement holds potential for broader applications in medical imaging and diagnostics.

Lu, Zhengyi [Vanderbilt University]↗

DOE OSTI2023

Reinforcement Learning Approach to Cybersecurity in Space (RELACSS)

Securing satellite groundstations against cyber-attacks is vital to national security missions. However, these cyber threats are constantly evolving. As vulnerabilities are discovered and patched, new vulnerabilities are discovered and exploited. In order to automate the process of discovering existing vulnerabilities and the means to exploit them, a reinforcement learning framework is presented in this report. We demonstrate that this framework can learn to successfully navigate an unknown network and detect nodes of interest despite the presence of a moving target defense. The agent then exfiltrates a file of interest from the node as quickly as possible. This framework also incorporates a defensive software agent that learns to impede the attacking agents progress. This setup allows for the agents to work against each other and improve their abilities. We anticipate that this capability will help uncover unforeseen vulnerabilities and the means to mitigate them. The modular nature of the framework enables users to swap out learning algorithms and modify the reward functions in order to adapt the learning tasks to various use cases and environments. Several algorithms, viz., tabular Q learning, deep Q networks, proximal policy optimization, advantage actor-critic, generative adversarial imitation learning, are explored for the agents and the results highlighted. The agent learns to solve the tasks in a light-weight abstract environment. Once the agent learns to perform sufficiently well, it can be deployed in a minimega virtual machine environment (or a real network) with wrappers that map abstract actions to software commands. The agent also uses a local representation of the actions called a ‘slot-mechanism’. This allows the agent to learn in a certain network and generalize it to different networks. The defensive agent learns to predict the actions taken by an offensive agent and uses that information to anticipate the threat. This information can then either be used to raise an alarm or to take actions to thwart the attack. We believe that with the appropriate reward design, a representative environment, and action set, this framework can be generalized to tackle other cybersecurity tasks. By sufficiently training these agents, we can anticipate vulnerabilities leading to robust future designs. We can also deploy automated defensive agents that can help secure satellite groundstation and their vital national security missions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2020

Structural Connectivity-Based Parcellation of the Dopaminergic Midbrain in Healthy Subjects and Schizophrenic Patients

Background and objectives: Functional deregulation of dopaminergic midbrain regions is a core feature of schizophrenia pathophysiology. Anatomical research on primates suggests that these regions may be subdivided into distinct, topographically organized functional territories according to their connectivity to the striatum. The aim of the present work was the reconstruction of dopaminergic midbrain subregions in healthy subjects and schizophrenic patients and the evaluation of their structural connectivity profiles. Materials and Methods: A hypothesis-driven connectivity-based parcellation derived from diffusion tractography was applied on 24 healthy subjects and 30 schizophrenic patients to identify distinct territories within the human dopaminergic midbrain in vivo and non-invasively. Results: We identified a tripartite subdivision of dopaminergic midbrain, including limbic, prefrontal and sensorimotor territories. No significant differences in structural features or connectivity were found between subjects and patients. Conclusions: The parcellation scheme proposed herein may help to achieve detailed characterization of structural and functional anomalies of the dopaminergic midbrain in schizophrenic patients.

ventral tegmental area↗

DOE OSTI2022

Real-space texture and pole-figure analysis using the 3D pair distribution function on a platinum thin film

An approach is described for studying texture in nanostructured materials. The approach implements the real-space texture pair distribution function (PDF), txPDF, laid out by Gong & Billinge {(2018). arXiv:1805.10342 [cond-mat]}. It is demonstrated on a fiber-textured polycrystalline Pt thin film. The approach uses 3D PDF methods to reconstruct the orientation distribution function of the powder crystallites from a set of diffraction patterns, taken at different tilt angles of the substrate with respect to the incident beam, directly from the 3D PDF of the sample. A real-space equivalent of the reciprocal-space pole figure is defined in terms of interatomic vectors in the PDF and computed for various interatomic vectors in the Pt film. Furthermore, it is shown how a valid isotropic PDF may be obtained from a weighted average over the tilt series, including the measurement conditions for the best approximant to the isotropic PDF from a single exposure, which for the case of the fiber-textured film was in a nearly grazing incidence orientation of ∼10°. Finally, an open-source Python software package, FouriGUI , is described that may be used to help in studies of texture from 3D reciprocal-space data, and indeed for Fourier transforming and visualizing 3D PDF data in general.

3D pair distribution functions↗

DOE OSTI2023

Bandwidth Control and Symmetry Breaking in a Mott‐Hubbard Correlated Metal

Abstract In Mott materials strong electron correlation yields a spectrum of complex electronic structures. Recent synthesis advancements open realistic opportunities for harnessing Mott physics to design transformative devices. However, a major bottleneck in realizing such devices remains the lack of control over the electron correlation strength. This stems from the complexity of the electronic structure, which often veils the basic mechanisms underlying the correlation strength. This study presents control of the correlation strength by tuning the degree of orbital overlap using picometer‐scale lattice engineering. This study illustrates how bandwidth control and concurrent symmetry breaking can govern the electronic structure of a correlated SrVO 3 model system. This study shows how tensile and compressive biaxial strain oppositely affect the SrVO 3 in‐plane and out‐of‐plane orbital occupancy, resulting in the partial alleviation of the orbital degeneracy. The spectral weight redistribution under strain is derived and explained, which illustrates how high tensile strain drives the system toward a Mott insulating state. Implementation of such concepts can push correlated electron phenomena closer toward new solid‐state devices and circuits. These findings therefore pave the way for understanding and controlling electron correlation in a broad range of functional materials, driving this powerful resource for novel electronics closer toward practical realization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Seasonal Disorder in Urban Traffic Patterns: A Low Rank Analysis

This article proposes several advances to sparse nonnegative matrix factorization (SNMF) as a way to identify large-scale patterns in urban traffic data. The input to our model is traffic counts organized by time and location. Nonnegative matrix factorization additively decomposes this information, organized as a matrix, into a linear sum of temporal signatures. Penalty terms encourage this factorization to concentrate on only a few temporal signatures, with weights which are not too large. Our interest here is to quantify and compare the regularity of traffic behavior, particularly across different broad temporal windows. In addition to the rank and error, we adapt a measure introduced by Hoyer to quantify sparsity in the representation. Combining these, we construct several curves which quantify error as a function of rank (the number of possible signatures) and sparsity; as rank goes up and sparsity goes down, the approximation can be better and the error should decreases. Plots of several such curves corresponding to different time windows leads to a way to compare disorder/order at different time scalewindows. In this paper, we apply our algorithms and procedures to study a taxi traffic dataset from New York City. In this dataset, we find weekly periodicity in the signatures, which allows us an extra framework for identifying outliers as significant deviations from weekly medians. We then apply our seasonal disorder analysis to the New York City traffic data and seasonal (spring, summer, winter, fall) time windows. We do find seasonal differences in traffic order.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Quasiparticle description of angle-resolved photoemission spectroscopy for SrCuO 2

SrCuO 2 has long been considered a near-archetypal realization of a quasi-one-dimensional (1D) system of interacting electrons with short-range interactions. Within this framework, experimental observations - interpreted through the lens of the 1D Hubbard model - suggest that electron and hole excitations decay into two types of (unphysical) collective bosonic modes: "spinons", which carry the spin degree of freedom, and "holons", which carry the charge degree of freedom. This model, known as spin-charge separation, is most directly evidenced by angle-resolved photoemission spectroscopy (ARPES), where a photo-induced hole decays into a continuum of these excitations. Here we present an alternative perspective grounded in first-principles, self-consistent, and parameter-free many-body perturbation theory. In this revised quasiparticle framework, ARPES can be understood as a one-body effect arising from mild disorder in a long-range antiferromagnetic ground state. the emergence of the so-called spinon branch arises naturally from spin disorder, the anomalous linewidths are accurately captured, and we provide a compelling explanation for the spectral weight observed at the non-magnetic zone boundary. This reinterpretation provides a unified explanation for key experimental signatures previously attributed to spin-charge separation, including features observed in optical conductivity. Additionally, we show that SrCuO 2 exhibits a nontrivial interchain coupling that significantly influences both its one-particle and two-particle spectral functions. By comparing the spectral features of SrCuO 2 with those of La 2 CuO 4 , we argue that SrCuO 2 shares notable similarities with the two-dimensional cuprates-both being rooted in a common CuO 4 plaquette-based molecular orbital framework.

1D cuprates↗

DOE OSTI2023

Economic competitiveness of pultruded fiber composites for wind turbine applications

Pultrusion manufacturing of fiber reinforced polymers has been shown to yield some of the highest mechanical properties for unidirectional composites, having a high degree of fiber alignment with consistent performance. Pultrusions offer a low-cost manufacturing approach for producing unidirectional composites with a constant cross-section and are used in many applications, including spar caps of wind turbine blades. However, as an intermediate processing step for wind blades, the additional cost of manufacturing pultrusions must be accompanied by sufficient increases in mechanical performance and system benefits. Wind turbine blades are manufactured using vacuum-assisted resin transfer molding with infused unidirectional fiberglass or carbon pultrusions for the spar cap. Infused fiberglass composites are among the most cost-effective structural materials available and replacing this material in the cost-driven wind industry has proven challenging, where infused fiberglass spar caps are still the predominant material system in use. To evaluate alternative material systems in a pultruded composite form, it is necessary to understand the costs for this additional manufacturing step which are shown to add 33%–55% on top of the material costs. A pultrusion cost model has been developed and used to quantify cost sensitivities to various processing parameters. The mechanical performance for pultruded composites is improved versus resin-infusion manufacturing with a 17% increase in design strength at a constant fiber volume fraction, but also enables higher achievable fiber volume fractions. The cost-specific mechanical performance is compared as a function of processing parameters for pultruded composites to identify the opportunities for alternative material and manufacturing approaches for wind turbine spar caps. Finally, four materials are compared in a representative wind turbine blade model to assess the performance of pultruded carbon fiber systems and pultruded fiberglass relative to infused fiberglass, where the pultruded systems produce lower weight blades with various cost distinctions.

42 ENGINEERING↗

DOE OSTI2026

Valorization of consolidated bioprocessing residues for bioplastics

This study demonstrates an organic solvent-free processing strategy to valorize consolidated bioprocessing (CBP) residues, from switchgrass and poplar biomass, into functional poly(butylene succinate) (PBS)-based biocomposites using high-shear homogenization (HSH). HSH transformed the switchgrass and poplar CBP residues (CBP-R) into fine, uniformly distributed particles and microfibers. The composites of PBS with homogenized switchgrass residues (H-CBP-R-SG) or homogenized poplar residues (H-CBP-R-P) at a 70/30 weight ratio exhibited improved processability and mechanical integrity, with the Young's modulus for the PBS/H-CBP-R-SG and PBS/H-CBP-R-P nearly doubling to 0.66 ± 0.07 GPa and 0.65 ± 0.04 GPa, respectively, compared to neat PBS (0.36 ± 0.02 GPa). Dynamic Mechanical Analysis (DMA) reveals a significant suppression of the tan δ peak magnitude, indicating that HSH-mediated physical activation facilitates stress transfer in composites typical of covalent chemical grafting systems. While the transition to a stiffness-dominated profile reduces ductility, the resulting composites exhibit the dimensional stability and resistance to thermal warping required for high-fidelity FDM 3D printing and injection molding. Beyond material performance, comprehensive techno-economic analysis (TEA) and life cycle assessment (LCA) confirmed that diverting CBP residues into composite products can improve the economic viability of the biorefinery without substantially increasing biorefinery global warming potential (GWP). At a 30 wt% blend ratio, incorporating residuals into PBS yielded a minimum selling price for the composite of $\$4.07$ per kg compared to the conventional bioplastic price of $\$5.00$ per kg. This approach aligns with circular bioeconomy principles by converting waste streams into value-added products. Furthermore, this innovative strategy addresses key challenges in bioplastic development, including cost, compatibility, and performance, while simultaneously advancing waste minimization strategies for sustainable manufacturing systems.

09 BIOMASS FUELS↗

DOE OSTI2024

Emergence of the temperature–density relation in the low-density intergalactic medium

We examine the evolution of the phase diagram of the low-density intergalactic medium during the Epoch of Reionization in simulation boxes with varying reionization histories from the Cosmic Reionization on Computers project. The probability density function (PDF) of gas temperature at fixed density exhibits two clear modes: a warm and a cold temperature mode, corresponding to the gas inside and outside of ionized bubbles. We find that the transition between the two modes is ‘universal’ in the sense that its timing is accurately parametrized by the value of the volume-weighted neutral fraction for any reionization history. This ‘universality’ is more complex than just a reflection of the fact that ionized gas is warm and neutral gas is cold: it holds for the transition at a fixed value of gas density, and gas at different densities transitions from the cold to the warm mode at different values of the neutral fraction, reflecting a non-trivial relationship between the ionization history and the evolving gas density PDF. Furthermore, the ‘emergence’ of the tight temperature–density relation in the warm mode is also approximately ‘universally’ controlled by the volume-weighted neutral fraction for any reionization history. In particular, the ‘emergence’ of the temperature–density relation (as quantified by the rapid decrease in its width) occurs when the neutral fraction is 10 –4 ≲ X HI ≲ 10 –3 for any reionization history. Our results indicate that the neutral fraction is a primary quantity controlling the various properties of the temperature–density relation, regardless of reionization history.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Parametrization, characterization, and optimization of double-bend achromat cell

We continue the study of single-particle dynamics in a more realistic cell, namely the double-bend achromat with three families of quadrupoles. The cell is parameterized with the optical parameters including the phase advances and the horizontal beta functions at its entry and center. At zero chromaticity, we find that the landscape of the dynamic aperture in the tune plane can be captured by a simple formula constructed from the effective Hamiltonian of 4th order. Furthermore, the optimal dynamic aperture can be found by simply minimizing the third-order driving terms with equal weight in the effective Hamiltonian.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Compositional phase stability of correlated electron materials within DFT+DMFT

Predicting the compositional phase stability of strongly correlated electron materials is an outstanding challenge in condensed matter physics, requiring precise computations of total energies. In this work, we employ the density functional theory plus dynamical mean-field theory (DFT+DMFT) formalism to address local correlations due to transition metal $\textit{d}$ electrons on compositional phase stability in the prototype rechargeable battery cathode material Li x CoO 2 , and detailed comparisons are made with the simpler DFT+$\textit{U}$ approach (i.e., the Hartree-Fock solution of the DMFT impurity problem). Local interactions are found to strongly impact the energetics of the band insulator LiCoO 2 , most significantly via the $E_g$ orbitals, which are partially occupied via hybridization with $\textit{O p}$ states. We find CoO 2 and Li 1/2 CoO 2 to be moderately correlated Fermi liquids with quasiparticle weights of 0.6–0.8 for the $T_{2g}$ states, which are most impacted by the interactions. Further, as compared to DFT+$\textit{U}$, DFT+DMFT considerably dampens the increase in total energy as $\textit{U}$ is increased, which indicates that dynamical correlations are important to describe this class of materials despite the relatively modest quasiparticle weights. Unlike DFT+$\textit{U}$, which can incorrectly drive Li x CoO 2 toward spurious phase separating or charge-ordered states, DFT+DMFT correctly captures the system's phase stability and does not exhibit a strong charge-ordering tendency. Most importantly, the error within DFT+$\textit{U}$ varies strongly as the composition changes, challenging the common practice of artificially tuning $\textit{U}$ within DFT+$\textit{U}$ to compensate the errors of Hartree-Fock. DFT+DMFT predicts the average intercalation voltage decreases relative to DFT, opposite to the result of DFT+$\textit{U}$, which would yield favorable agreement with experiment in conjunction with the overprediction of the voltage by the strongly constrained and appropriately normed DFT functional.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Majorana modes with side features in magnet-superconductor hybrid systems

Magnet-superconductor hybrid (MSH) systems represent promising platforms to host Majorana zero modes (MZMs), the elemental building blocks for fault-tolerant quantum computers. Theoretical description of such MSH structures is mostly based on simplified models, not accounting for the complexity of real materials. Here, based on density functional theory, we derive a superconducting 80-band model to study an MSH system consisting of a magnetic manganese chain on the s wave superconductor niobium. For a wide range of values of the superconducting order parameter, the system is a topological superconductor, with MZMs exhibiting non-universal spatial patterns and a drastic accumulation of spectral weight on both sides along the magnetic chain. These side feature states can be explained by an effective model which is guided by the ab initio results. Performing scanning tunneling spectroscopy experiments on the same system, we observe a spatial structure in the low-energy local density of states that is consistent with the theoretical findings. Our results open a first-principle approach to the discovery of topological superconductors.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Cavity electrodynamics of van der Waals heterostructures

Van der Waals heterostructures host many-body quantum phenomena that are tunable in situ using electrostatic gates. Their constituent two-dimensional materials and gates can naturally form plasmonic self-cavities, confining light in standing waves of current density due to finite-size effects. The plasmonic resonances of typical graphite gates fall in the gigahertz to terahertz range, corresponding to the same microelectronvolt to millielectronvolt energy scale as the phenomena in van der Waals heterostructures that they electrically control. This raises the possibility that the built-in cavity modes of graphite gates are relevant for shaping the low-energy physics of these heterostructures. However, probing these cavity-coupled electrodynamics is challenging as devices are notably smaller than the diffraction limit at the relevant wavelengths. Here we report on the intrinsic cavity conductivity of gate-tunable graphene heterostructures. As the carrier density is tuned, we observe coupling and spectral weight transfer between graphene and graphite plasmonic cavity modes in the ultrastrong coupling regime. We present an analytical model to describe the results and provide general principles for cavity design. Our findings show that intrinsic cavity effects are important for understanding the low-energy electrodynamics of van der Waals heterostructures and open a pathway for useful functionality through cavity control.

Electronic properties and materials↗