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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon

GD-1 is among the longest, coldest stellar streams in the Milky Way, making it an ideal target for probing dark matter substructure through dynamical heating. We present a catalog of 608 spectroscopically confirmed GD-1 members from the first three years of Dark Energy Spectroscopic Instrument (DESI) observations. This constitutes the largest homogeneous spectroscopic sample of GD-1, doubling the number of members previously available only through heterogeneous compilations combining multiple surveys with different systematics. Using these data, we derive updated stream tracks in sky position, proper motion, and radial velocity that extend over $100^\circ$ of the stream. We apply a Gaussian mixture model to decompose the stream into a dynamically cold thin component ($σ_V = 2.49\pm 0.28$ km s$^{-1}$, width $= 0.23\pm0.01^\circ$) and a kinematically hot cocoon ($σ_V = 6.13\pm0.75$ km s$^{-1}$, width $= 2.18\pm0.17^\circ$). The cocoon contains $\sim30\%$ of members and its velocity dispersion is consistent with $\sim11$ Gyr of heating by cold dark matter subhalos. We also detect a large proper motion dispersion ($41.36\pm4.98$ km s$^{-1}$) along the stream direction in the cocoon component. This feature indicates a significant line-of-sight distance spread in the cocoon, and its origin will be further explored in a forthcoming paper. These measurements demonstrate the power of DESI spectroscopy for characterizing the multi-component phase-space structure of stellar streams and constraining small-scale dark matter substructure.

Jarvis, Emma [Toronto U.] (ORCID:0009000656127336)↗
DOE OSTI2025

The Role of Snowmelt and Subsurface Heterogeneity in Headwater Hydrology of a Mountainous Catchment in Colorado: A Model‐Data Integration Approach

Mountainous headwater streams are sustained by both snowmelt‐driven streamflow and groundwater discharge in the Upper Colorado River Basin. However, predicting headwater stream discharge magnitude and peak flow timing is challenging in mountainous terrains, where snowmelt rates vary with vegetation type and elevation, and heterogeneous subsurface physical properties influence groundwater storage and its release. We used a model‐data integration approach to investigate the roles of snowmelt and subsurface structure in stream discharge and groundwater level. We ran an ensemble of 100 integrated surface‐subsurface hydrologic models for a mountainous headwater catchment near Crested Butte, Colorado, USA. We also evaluated and calibrated these models against observed data sets, including snow depth measurements using distributed temperature probes, stream discharge, and groundwater levels. Calibration with multiple data sources using neural density estimators has further constrained uncertainty in subsurface properties and snowmelt rates. Results indicated that observed slower snowmelt rates in evergreen forests delayed the peak flow and baseflow onset. In upstream areas with lower subsurface permeability, water was stored within the subsurface but was not released as interflow or shallow groundwater flow, and thereby not contributing to downstream streamflow during recession limb periods. Double peaks in groundwater occurred in areas with spatial subsurface heterogeneity, in our case due to the contrast between granodiorite and Mancos shale. These process‐based insights into groundwater and snowmelt dynamics in mountainous headwaters will help improve predictions of headwater hydrology.

Wang, Lijing [University of Connecticut, Storrs, C↗
DOE OSTI2025

Structural switching dynamically controls the doubly pseudoknotted Rous sarcoma virus–programmed ribosomal frameshifting element

A hallmark of retrovirus replication is the translation of two different polyproteins from one RNA through programmed –1 frameshifting. This is a mechanism in which the actively translating ribosome is induced to slip in the 5′ direction at a defined codon and then continues translating in the new reading frame. Programmed frameshifting controls the stoichiometry of viral proteins and is therefore under stringent evolutionary selection. Forty years ago, the first frameshifting stimulatory element was discovered in the Rous sarcoma virus. The ~120 nt RNA segment was predicted to contain a pseudoknot, but its 3D structure has remained elusive. Now, we have determined cryoEM and X-ray crystallographic structures of this classic retroviral element, finding that it adopts a butterfly-like double-pseudoknot fold. One “wing” contains a dynamic pyrimidine-rich helix, observed crystallographically in two conformations and in a third conformation via cryoEM. The other wing encompasses the predicted pseudoknot, which interacts with a second unexpected pseudoknot through a toggle residue, A2546. This key purine switches conformations between structural states and tunes the stability of interacting residues in the two wings. We find that its mutation can modulate frameshifting by as much as 50-fold, likely by altering the relative abundance of different structural states in the conformational ensemble of the RNA. Taken together, our structure–function analyses reveal how a dynamic double pseudoknot junction stimulates frameshifting by taking advantage of conformational heterogeneity, supporting a multistate model in which high Shannon entropy enhances frameshifting efficiency.

Science & Technology - Other Topics↗
DOE OSTI2021

Ion correlations drive charge overscreening and heterogeneous nucleation at solid–aqueous electrolyte interfaces

Significance Ion distributions at charged solid–water interfaces, referred to as the electrical double layer (EDL), are poorly understood at high ion concentrations, in part due to the lack of molecular-scale descriptions of the interactions between adsorbed hydrated ions. Here, direct visualization of the salinity-dependent evolution of EDL structure reveals molecular origins of nonclassical transformation of the EDL, in which charge overscreening and heterogeneous nucleation are driven by ion–ion correlations at the interfaces. This manifestation of the atomistic basis of nonclassical behaviors provides a much-needed understanding of the impact of ion cooperativity at charged interfaces for the development of predictive models for element transport in natural environments and advanced technologies for material growth and synthesis in saline environments.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multi-scale structural analysis of swift heavy ion-irradiated ZrO 2 and HfO 2

The radiation-induced monoclinic-to-tetragonal phase transition in ZrO 2 and HfO 2 has been the subject of many investigations, but the transformation pathways and underlying structural mechanisms are still not well understood. In this study, microcrystalline powder samples of ZrO 2 and HfO 2 were irradiated with 946 MeV and 1470 MeV Au ions to a wide fluence range up to 3 × 10 13 ions/cm 2 . To characterize beam-induced structural modifications across all spatial length scales, complementary experimental techniques such as synchrotron X-ray diffraction and spallation neutron total scattering were used. The phase evolution of the tetragonal polymorph with increasing ion fluence is accurately described by a heterogeneous track-overlap model that incorporates both direct- and double-impact processes. These damage accumulation processes are an expression of a core-shell ion track morphology that depends on irradiation conditions and target material. Neutron pair distribution function analysis revealed that ion-beam-induced tetragonal ZrO 2 is merely a configurational average of short-range orthorhombic (Pbcn) domains stabilized by a dense network of domain walls. Furthermore, this knowledge is critical for a better understanding of how crystalline-to-crystalline phase transformations proceed at the atomic scale under extreme conditions.

Monoclinic-to-tetragonal phase transformation↗
DOE OSTI2022

Crystallization pathways and interfacial drivers for the formation of hierarchical architectures

The development of structural hierarchy on various length scales during crystallization process is ubiquitous in biological systems and is also observed in synthetic nanomaterials. The driving forces for the formations of complex architectures range from local interfacial interactions, that modify interfacial speciation, local supersaturation, and nucleation barriers, to macroscopic interparticle forces. Although it is enticing to interpret the formation of hierarchical architectures as the assembly of independently nucleated building blocks, often crystallization pathways follow monomer-by-monomer addition with structural complexity arising from interfacial chemical coupling and strongly correlated fluctuation dynamics in the electric double layers. Here, the mechanism of the development of structural hierarchy through heterogeneous nucleation, coupled interfacial nucleation and assembly, and oriented attachment of independently nucleated particles is discussed. In this article, the emphasis is made on the discussion of the underlying interfacial forces and chemical coupling that drives crystallization pathways towards the formation of structural hierarchy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Theoretical Modeling of Electrochemical Proton-Coupled Electron Transfer

Proton-coupled electron transfer (PCET) plays an essential role in a wide range of electrocatalytic processes. Here, a vast array of theoretical and computational methods have been developed to study electrochemical PCET. These methods can be used to calculate redox potentials and pKa values for molecular electrocatalysts, proton-coupled redox potentials and bond dissociation free energies for PCET at metal and semiconductor interfaces, and reorganization energies associated with electrochemical PCET. Periodic density functional theory can also be used to compute PCET activation energies and perform molecular dynamics simulations of electrochemical interfaces. Various approaches for maintaining a constant electrode potential in electronic structure calculations and modeling complex interactions in the electric double layer (EDL) have been developed. Theoretical formulations for both homogeneous and heterogeneous electrochemical PCET spanning the adiabatic, nonadiabatic, and solvent-controlled regimes have been developed and provide analytical expressions for the rate constants and current densities as functions of applied potential. The quantum mechanical treatment of the proton and inclusion of excited vibronic states have been shown to be critical for describing experimental data, such as Tafel slopes and potential dependent kinetic isotope effects. The calculated rate constants can be used as input to microkinetic models and voltammogram simulations to elucidate complex electrocatalytic processes.

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

Determining the Conformation of Supported Complexes Using an 17 O TEDOR-like NMR Experiment

Dynamic nuclear polarization surface-enhanced nuclear magnetic resonance (NMR) spectroscopy has enabled the determination of the three-dimensional configuration of surface sites, in particular supported metal complexes of relevance to single-site heterogeneous catalysis. These approaches have chiefly leveraged the application of NMR double-resonance experiments that either reveal the complex conformation via point-to-point intramolecular distances between spin-labeled atoms or the complex-surface orientation via distances between the spins and the surface plane. Either method typically requires expensive isotope labeling and each reports on different structural features. The application of an experiment that simultaneously reveals both types of distances with chemical resolution would be ideal. Here, in this article, we describe an 17 O{ 1 H} pseudo-3D correlation experiment that achieves this goal. Specifically, Si–O–Si and Si–O–M oxygens are well-resolved by 17 O NMR; therefore, distances can be simultaneously measured radially, between Si– 17 O–M and the 1 H’s of the ligands, and vertically to the Si– 17 O–Si linkages of the silica support. We demonstrate the experiment using supported yttrium and zirconium complexes. Good agreement is obtained when comparing the experimental results to theoretical predictions from density functional theory calculations, highlighting the reliability of this relatively simple experiment.

alkyls↗
DOE OSTI2025

Solvation directed morphological control in metal oxide nanostructures

The development of structural hierarchy on various length scales during the crystallization process is ubiquitous in biological systems and minerals and is common in synthetic nanomaterials. The driving forces for the formation of complex architectures range from local interfacial interactions, that modify interfacial speciation, local supersaturation, and nucleation barriers, to macroscopic interparticle forces. Although it is enticing to interpret the formation of hierarchical architectures as the assembly of independently nucleated building blocks, crystallization pathways often follow monomer-by-monomer addition with structural complexity arising from interfacial chemical coupling and strongly correlated fluctuation dynamics in the electric double layers. Here, we show that the development of structural hierarchy through heterogeneous nucleation is driven by dipolar and solvation forces. Specifically, coupled simulations and experimental studies revealed that dipole build-up along the slow growth direction can trigger twinning and the development of branched architectures. Enthalpic solvation interactions were shown to either enhance or reduce the dipole moment of the nanoparticles and, thereby, control crystal morphology and architecture. The systematic studies of chemical coupling between different solvents and undercoordinated surface atoms of the growing nanocrystals revealed the mechanism of dimensionality control and the development of structural hierarchy without ligands or structure-directing agents.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Evaluating Limits of Machine Learning-Assisted Raman Spectroscopy in Classification of Biological Samples

Machine learning (ML)-assisted Raman spectroscopy has become a powerful analytical tool for the classification and identification of analytes; however, technical challenges impacting its detection accuracy have not been thoroughly investigated. This study explores experimental factors affecting classification performance. Among the evaluated ML models, ML algorithms show minimal impact on classification accuracy. Instead, experimental factors, including spectral similarity between tested samples and data quality, dominate detection performance. Increases in spectral noise and spectral similarity significantly reduce classification accuracy. In well-controlled samples with low experimental noise, ML-assisted Raman spectroscopy can discriminate lipid mixtures with a composition difference of 1.85 mol %. To assess the effect of biological heterogeneity, we analyzed single-cell Raman spectra from Saccharomyces cerevisiae strains carrying single, double, or triple gene mutations. Intrinsic cell-to-cell variability introduced substantial spectral differences, severely reducing the accuracy of multiclass classification of these genetically similar strains at the single-cell level. Averaging Raman spectra across multiple cells improved classification accuracy by reducing this spectral variability. We also assess the effectiveness of transfer learning across different Raman spectrometers, specifically by applying an ML model trained on one instrument to another Raman spectrometer. Transfer learning can be improved with proper instrument calibration, highlighting the importance of instrument standardization. Overall, our results demonstrate that data quality and spectral similarity are the primary bottlenecks in ML-assisted Raman spectroscopy. Careful attention to sample preparation, data acquisition, measurement conditions, and instrument calibration is critical to achieving robust and reliable classification performance.

Fungi↗
DOE OSTI2024

Evaluating Possible Formation Mechanisms of Criegee Intermediates during the Heterogeneous Autoxidation of Squalene

Organic molecules in the environment oxidatively degrade by a variety of free radical, microbial, and biogeochemical pathways. A significant pathway is heterogeneous autoxidation, in which degradation occurs via a network of carbon and oxygen centered free radicals. Recently, we found evidence for a new heterogeneous autoxidation mechanism of squalene that is initiated by hydroxyl (OH) radical addition to a carbon–carbon double bond and apparently propagated through pathways involving Criegee Intermediates (CI) produced from β-hydroxy peroxy radicals (β-OH-RO 2 •). It remains unclear, however, exactly how CI are formed from β-OH-RO 2 •, which could occur by a unimolecular or bimolecular pathway. Combining kinetic models and multiphase OH oxidation measurements of squalene, we evaluate the kinetic viability of three mechanistic scenarios. Scenario 1 assumes that CI are formed by the unimolecular bond scission of β-OH-RO 2 •, whereas Scenarios 2 and 3 test bimolecular pathways of β-OH-RO 2 • to yield CI. Scenario 1 best replicates the entire experimental data set, which includes effective uptake coefficients vs [OH] as well as the formation kinetics of the major products (i.e., aldehydes and secondary ozonides). Finally, although the unimolecular pathway appears to be kinetically viable, future high-level theory is needed to fully explain the mechanistic relationship between CI and β-OH-RO 2 • in the condensed phase.

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

Abrupt reduction in shipping emission as an inadvertent geoengineering termination shock produces substantial radiative warming

Abstract Human activities affect the Earth’s climate through modifying the composition of the atmosphere, which then creates radiative forcing that drives climate change. The warming effect of anthropogenic greenhouse gases has been partially balanced by the cooling effect of anthropogenic aerosols. In 2020, fuel regulations abruptly reduced the emission of sulfur dioxide from international shipping by about 80% and created an inadvertent geoengineering termination shock with global impact. Here we estimate the regulation leads to a radiative forcing of $$+0.2\pm 0.11$$ + 0.2 ± 0.11 Wm −2 averaged over the global ocean. The amount of radiative forcing could lead to a doubling (or more) of the warming rate in the 2020 s compared with the rate since 1980 with strong spatiotemporal heterogeneity. The warming effect is consistent with the recent observed strong warming in 2023 and expected to make the 2020 s anomalously warm. The forcing is equivalent in magnitude to 80% of the measured increase in planetary heat uptake since 2020. The radiative forcing also has strong hemispheric contrast, which has important implications for precipitation pattern changes. Our result suggests marine cloud brightening may be a viable geoengineering method in temporarily cooling the climate that has its unique challenges due to inherent spatiotemporal heterogeneity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra: Modeling Archive

This dataset is a model archive of the paper Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra (in prep) to support a modeling study investigating how projected increases in Arctic temperature and precipitation will jointly influence hydrologic conditions in ice-rich tundra landscapes. With this dataset, this study is to address the research question: Will Arctic tundra landscapes become wetter or drier with increasing precipitation and temperature in the future when thaw-induced ground subsidence and associated microtopographic evolution are represented? The simulations focus on ice-wedge polygon tundra, a widespread form of ice-rich permafrost terrain that is highly sensitive to thaw-driven landscape change. This dataset contains model input and output data for four study watersheds in Alaska: Anaktuvuk, Utqiagvik (formerly Barrow), Brooks Foothills, and Prudhoe Bay. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.5), a physics-rich integrated surface–subsurface hydrologic model. For each watershed, ten modeling cases were performed representing two landscape evolution conditions (with subsidence and without subsidence) combined with five climate forcing scenarios derived from Shared Socioeconomic Pathways (SSP5, SSP5 with precipitation trend, SSP2, SSP2 with precipitation trend, and SSP2 with double precipitation trend). Particularly, for each watershed under the forcing SSP2 with precipitation trend, there are two additional simulations considering spatially heterogeneous subsidence distributions: one assumes randomly distributed scaling and the other includes elevation dependent distribution scaling. These simulations span 1980–2099 and include spin-up runs (1980–2009) followed by transient projections (2010–2099). To facilitate reproducibility of simulations, all datasets are organized by watershed. For each study watershed, the dataset contains: (1) Pre-partitioned mesh files for 32-core modeling (.par.32.XX), located in EACH_WATERSHED/mesh/basin; and also a non-partitioned mesh file (.exo) located in EACH_WATERSHED/mesh; (2) Climate forcings corresponding to the five SSP scenarios (.h5), located in EACH_WATERSHED/data; (3) Final states (.h5) from column spin-up modeling used to initialize historical watershed-scale spin-up runs from 1980 to 2009, located in EACH_WATERSHED/PreSpinupHistorical; (4) Final states (.h5) of historical watershed-scale spin-up runs from 1980 to 2009 used to initialize projection runs, located in EACH_WATERSHED/Spinup_daymetERA5; (5) ATS modeling input files (.xml), located in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/inputfiles; (6) ATS modeling output files (.dat), located in in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/combined_obs; (7) For the Brooks Foothills watershed, additional spatial model outputs are provided (.h5) for selected years (2033 and 2093) used to generate spatial figures in this study, located in Brooksfoothills/EACH_SIMULATION_SCENARIO/results-WITH/WITHOUT_SUBSIDENCE-year2033/2093. All data files with suffix .h5 can be accessible through Python h5py, and all data files with suffix of .dat can be imported by Python pandas. Mesh file with .exo can be visualized through Paraview or read by Python netCDF. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION↗
DOE OSTI2025

Dynamic behavior of molecular Pd-acetate trimers and dimers in heterogeneous vinyl acetate synthesis

Vinyl acetate monomer (VAM) is a crucial intermediate in the production of various polymers. While molecular Pd-acetate trimers and dimers, such as Pd 3 (OAc) 6 and K 2 Pd 2 (OAc) 6 , are known to form on potassium acetate (KOAc)-promoted PdAu catalysts during heterogeneous VAM synthesis, their mechanistic role remains unclear. Here, we study the dynamics of different Pd-acetate species by utilizing in situ and operando crystallographic and spectroscopic characterizations combined with computational modeling on monometallic Pd model catalysts. The promoter-free catalyst expectedly shows low catalytic activity and VAM selectivity, corresponding to the complete reduction of Pdn(OAc) 2n species to form Pd 0 and PdC x nanoparticles. Conversely, noticeable quantities of K n Pd 2 (OAc) n+4 species remain on the KOAc-promoted catalyst, leading to smaller nanoparticle formation with 10 times the activity and double the selectivity for VAM. This study reveals that molecular Pd-acetate trimers and dimers are significant indicators of catalytic performance and highlights their structurally dynamic nature in heterogeneous vinyl acetate chemistry.

Jacobs, Hunter P. [Rice Univ., Houston, TX (United↗
DOE OSTI2022

Media for culturing epithelial cells

A method of growing primary human epithelial cells, in particular human epithelial cells using a basal formula containing individual (a) amino acids, (b) vitamins, (c) trace elements, and (d) other organics such as linoleic acid. The basal medium may be a mixture of amino acids, vitamins, and salts that constitute the basic media that is used to culture epithelial cells over a number of population doublings, e.g., over at least one week, while maintaining a normal phenotype and exerting low stress on the cultured cells, and maintaining lineage heterogeneity.

LaBarge, Mark A.↗
DOE OSTI2023

Solving complex nanostructures with ptychographic atomic electron tomography

Abstract Transmission electron microscopy (TEM) is essential for determining atomic scale structures in structural biology and materials science. In structural biology, three-dimensional structures of proteins are routinely determined from thousands of identical particles using phase-contrast TEM. In materials science, three-dimensional atomic structures of complex nanomaterials have been determined using atomic electron tomography (AET). However, neither of these methods can determine the three-dimensional atomic structure of heterogeneous nanomaterials containing light elements. Here, we perform ptychographic electron tomography from 34.5 million diffraction patterns to reconstruct an atomic resolution tilt series of a double wall-carbon nanotube (DW-CNT) encapsulating a complex ZrTe sandwich structure. Class averaging the resulting tilt series images and subpixel localization of the atomic peaks reveals a Zr 11 Te 50 structure containing a previously unobserved ZrTe 2 phase in the core. The experimental realization of atomic resolution ptychographic electron tomography will allow for the structural determination of a wide range of beam-sensitive nanomaterials containing light elements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantum Electrodynamics Coupled-Cluster at Scale: High-Performance Implementation for Complex Systems

Coupled-cluster theory (CC) is a highly accurate and versatile method for simulating complex interactions within quantum systems. The extension of CC theory to model mixed electron-photon processes with quantum electrodynamics (QED) has improved our capability to predict cavity-modified chemistry, a field where photons are used as cost-effective and eco-friendly alternatives to catalyze/inhibit chemical reactions. However, calculations with CC methods, even without incorporating QED effects, are often prohibitively expensive. Simulations of larger systems require scalable infrastructures that exist for traditional CC methods but not for QED-CC methods. As such, we present a GPU-enabled, high-performance, open-source implementation of the quantum electrodynamics coupled-cluster method with single and double excitations (QED-CCSD) within the ExaChem quantum chemistry software package. ExaChem relies on the Tensor Algebra for Many-body Methods (TAMM) infrastructure: a parallel heterogeneous tensor library designed to achieve scalable performance on modern heterogeneous supercomputing platforms. Furthermore, we discuss theoretical foundations, algorithmic details, and numerical benchmarks to showcase the larger systems that ExaChem can simulate and how the integration of photonic degrees-of-freedom alters their ground-state properties.

Basis sets↗