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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Baryon fraction from the BAO amplitude: a consistent approach to parameterizing perturbation growth

Galaxy clustering constrains the baryon fraction Omega_b/Omega_m through the amplitude of baryon acoustic oscillations and the suppression of perturbations entering the horizon before recombination. This produces a different pre-recombination distribution of baryons and dark matter. After recombination, the gravitational potential responds to both components in proportion to their mass, allowing robust measurement of the baryon fraction. This is independent of new-physics scenarios altering the recombination background (e.g. Early Dark Energy). The accuracy of such measurements does, however, depend on how baryons and CDM are modeled in the power spectrum. Previous template-based splitting relied on approximate transfer functions that neglected part of information. We present a new method that embeds an extra parameter controlling the balance between baryons and dark matter in the growth terms of the perturbation equations in the CAMB Boltzmann solver. This approach captures the baryonic suppression of CDM prior to recombination, avoids inconsistencies, and yields a clean parametrization of the baryon fraction in the linear power spectrum, separating out the simple physics of growth due to the combined matter potential. We implement this framework in an analysis pipeline using Effective Field Theory of Large-Scale Structure with HOD-informed priors and validate it against noiseless LCDM and EDE cosmologies with DESI-like errors. The new scheme achieves comparable precision to previous splitting while reducing systematic biases, providing a more robust way to baryon-fraction measurements. In combination with BBN constraints on the baryon density and Alcock-Paczynski estimates of the matter density, these results strengthen the use of baryon fraction measurements to derive a Hubble constant from energy densities, with future DESI and Euclid data expected to deliver competitive constraints.

Crespi, Andrea [U. Waterloo (main); Waterloo U., I↗
DOE OSTI2020

A Rapid Population Assessment Method for Wild Pigs Using Baited Cameras at 3 Study Sites

ABSTRACT Reliable and efficient population estimates are a critical need for effective management of invasive wild pigs ( Sus scrofa ). We evaluated the use of 10‐day camera grids for rapid population assessment (RPA) of wild pigs at 3 study sites that varied in vegetation communities and wild pig densities. Study areas included Buck Island Ranch, Florida; Tejon Ranch, California; and the Savannah River Site, South Carolina, USA, during 2016–2018. Rapid population assessments grids were composed of baited camera traps spaced approximately 500 or 750 m apart. Two RPA grids were deployed per study site and each grid was deployed twice (4–6 months apart) to assess changes in response to season or population control efforts. We assessed the ability of RPA grids to track population trends, how camera number influenced estimate precision, and how relative abundance indices related to density estimates. We detected changes in occupancy probability, detection probability, and N‐mixture estimates following removal operations and between seasons, but the ability of RPA grids to track population trends was dependent on the statistical method used and number of cameras traps. Increasing the number of cameras traps used in RPA grids increased precision, and these results can be used in determining survey design and estimate choice. We found that estimates of occupancy probability, detection probability, and N‐mixture estimates were positively correlated with spatially explicit capture–recapture density estimates. Thus, these less labor‐intensive estimates from RPA grids showed potential to index the relative abundance of wild pigs in some systems. Our evaluation of RPAs indicates that using study‐specific combinations of statistical method and number of cameras can provide a useful tool for monitoring wild pig presence, tracking population trends, and evaluating the effectiveness of management actions. © 2020 The Wildlife Society.

Schlichting, Peter E.↗
DOE OSTI2022

Deep Learning of Dark Energy Spectroscopic Instrument Mock Spectra to Find Damped Lyα Systems

We have updated and applied a convolutional neural network (CNN) machine-learning model to discover and characterize damped Ly α systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99% for spectra that have signal-to-noise ratios (S/N) above 5 per pixel. The classification accuracy is the rate of correct classifications. This accuracy remains above 97% for lower S/N ≈1 spectra. This CNN model provides estimations for redshift and H i column density with standard deviations of 0.002 and 0.17 dex for spectra with S/N above 3 pixel -1 . Also, this DLA finder is able to identify overlapping DLAs and sub-DLAs. Further, the impact of different DLA catalogs on the measurement of baryon acoustic oscillations (BAO) is investigated. The cosmological fitting parameter result for BAO has less than 0.61% difference compared to analysis of the mock results with perfect knowledge of DLAs. This difference is lower than the statistical error for the first year estimated from the mock spectra: above 1.7%. We also compared the performances of the CNN and Gaussian Process (GP) models. Our improved CNN model has moderately 14% higher purity and 7% higher completeness than an older version of the GP code, for S/N > 3. Both codes provide good DLA redshift estimates, but the GP produces a better column density estimate by 24% less standard deviation. A credible DLA catalog for the DESI main survey can be provided by combining these two algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Evaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST)

Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the results of a comprehensive experiment comparing twelve photo-z algorithms applied to mock data produced forLarge Synoptic Survey Telescope The Rubin Observatory Legacy Survey of Space and Time (lsst) Dark Energy Science Collaboration (desc). By supplying perfect prior information, in the form of the complete template library and a representative training set as inputs to each code, we demonstrate the impact of the assumptions underlying each technique on the output photo-z PDFs. In the absence of a notion of true, unbiased photo-z PDFs, we evaluate and interpret multiple metrics of the ensemble properties of the derived photo-z PDFs as well as traditional reductions to photo-z point estimates. Additionally, we report systematic biases and overall over/under-breadth of the photo-z PDFs of many popular codes, which may indicate avenues for improvement in the algorithms or implementations. Furthermore, we raise attention to the limitations of established metrics for assessing photo-z PDF accuracy; though we identify the conditional density estimate (CDE) loss as a promising metric of photo-z PDF performance in the case where true redshifts are available but true photo-z PDFs are not, we emphasize the need for science-specific performance metrics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Numerical simulation of the hot-tail runaway electron production mechanism using CQL3D and comparison with Smith–Verwichte analytical model

Abstract The hot-tail mechanism of runaway electron (RE) production (Harvey et al 2000 Phys. Plasmas 7 4590) is the primary source of RE in the case of rapidly cooling tokamak plasma. Quantifying this mechanism is very important as it can provide most of the post-thermal-quench (TQ) current, or a seed current for the secondary source of RE through the avalanche mechanism. An analytic model which omits pitch-angle scattering is often used in literature for estimating the hot-tail RE density (Smith and Verwichte 2008 Phys. Plasmas 15 072502). In the present study, we use the CQL3D bounce-averaged Fokker–Planck code (Harvey and McCoy 1992 Proc. IAEA Technical Committee Meeting on Advances in Simulation and Modeling of Thermonuclear Plasmas p 527) to test the limits of validity of the model. In particular, we examine the cases of Z = 1 and Z = 18 ions, for sets of different initial temperature, density, electric field and the characteristic time of temperature decay. We show that for Z = 1 plasma, the ratio of RE density computed by CQL3D to that estimated from the model is within 0.6–6.0 in studied cases. For the Z = 18 case, this factor is systematically a much smaller number, typically 0.02–0.6. We suggest a simple correction to the model that narrows down the range of this ratio to 0.3–3.8 in all of the cases, including Z = 1 and Z = 18 plasmas.

Physics↗
DOE OSTI2026

Identified charged hadron production in Au+Au collisions at $\sqrt{s_{NN}}$ = 54.4 GeV with the STAR detector

Here, we present results on the production of 𝜋±, 𝐾±, 𝑝, and $\bar{𝑝}$ in Au+Au collisions at $\sqrt{𝑠_{N⁢N}}$ = 54.4~GeV using the STAR detector at RHIC, at mid-rapidity (|𝑦|< 0.1). Invariant yields of these particles as a function of transverse momentum are shown. We determine bulk properties such as integrated particle yields (𝑑 ⁢𝑁 /𝑑 ⁢𝑦 ), mean transverse momentum (⟨𝑝 𝑇 ⟩), particle ratios, which provide insight into the particle production mechanisms. Additionally, the kinetic freeze-out parameters (𝑇 kin and ⟨𝛽 𝑇 ⟩), which provide information about the dynamics of the system at the time of freeze-out, are obtained. The Bjorken energy density (𝜖 𝐵⁢𝐽 ), which gives an estimate of the energy density in the central rapidity region of the collision zone at the formation time 𝜏, is calculated and presented as a function of multiplicity for various energies. The results are compared with those from the models such as A Multi-Phase Transport (AMPT) and Heavy Ion Jet INteraction Generator (HIJING) for further insights.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Ab initio electronic density in solids by many-body plane-wave auxiliary-field quantum Monte Carlo calculations

We present accurate many-body results of the electronic densities in several solid materials, including Si, NaCl, and Cu. These results are obtained using the ab initio auxiliary-field quantum Monte Carlo (AFQMC) method working in a plane-wave basis with norm-conserving, multiple-projector pseudopotentials. AFQMC has been shown to be an excellent many-body total energy method. Computation of observables and correlation functions other than the ground-state energy requires back-propagation, whose adaption and implementation in the plane-wave basis AFQMC framework are discussed in the present paper. This development allows us to compute correlation functions, electronic densities, and interatomic forces, paving the way for geometry optimizations and calculations of thermodynamic properties in solids. Finite supercell size effects are considerably more subtle in the many-body framework than in independent-electron calculations. We analyze the convergence of the electronic density, and obtain best estimates for the thermodynamic limit. The densities from several typical density functionals are benchmarked against our near-exact results. The electronic densities we obtained can also be used to help construct improved density functionals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting Biological Cleanliness: An Empirical Bayes Approach for Spacecraft Bioburden Accounting

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
DOE OSTI2020

Vadose Zone Flow and Transport Parameters Data Package for the Hanford Site Composite Analysis

This report provides a description of the basis for the development and implementation of a conceptual model for vadose zone flow and transport for the Hanford Site composite analysis (CA) groundwater pathway analysis. The parameterization for a numerical model is intimately linked to the conceptual model framework. This report describes the basis for the selection of hydraulic and transport parameters for the hydrostratigraphic units (HSUs) identified in the 200 East and 200 West Areas. The following three-step process was used to develop the hydraulic properties and transport parameters for the CA modeling: 1. Breakdown of existing database on hydraulic properties by HSUs 2. Constitutive model parameters for laboratory, core-scale hydraulic properties 3. Upscaling for macroscopic, field-scale flow, and transport parameters This document provides data and information on the following items: A brief description and technical basis for the conceptual model selected to represent vadose zone flow and transport for the CA modeling. Variation in sediment particle size distribution for representative sites in the 200 East and West Areas. A summary of effective (upscaled) moisture retention, and saturated and unsaturated hydraulic conductivity estimates for the HSUs in the 200 East and West Areas. A summary of effective transport parameters, including sediment bulk density and macrodispersivity estimates for various HSUs. The 200 East Area B Complex perched water aquifer hydraulic properties

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Rapid recovery of invasive wild pig (Sus scrofa) populations following density reduction

Abstract Trapping is an effective strategy for control of invasive wild pig (Sus scrofa), but eradication of populations via trapping alone typically is impractical throughout much of the species’ introduced range. Consequently, recovery of wild pig populations to pre-trapping levels following control is a major impediment to success of long-term control. In this study, we conducted camera-trap surveys to monitor recovery of two wild pig populations immediately following density reductions achieved via trapping on two sites on the Savannah River Site, SC. We used spatial capture-recapture models to estimate wild pig density during seven 3 week periods spanning 12 months to: (1) determine the time required for populations to recover to pre-trapping levels; and (2) evaluate trends in population growth, density, and distribution during recovery. Recovery of both wild pig populations started immediately after trapping ceased, with populations reaching pre-trapping levels in 3 and 5 months. Threeweek population growth rates for each wild pig population during recovery averaged 1.28 (range = 1.11–1.39 on site 1) and 1.24 (range = 0.64–1.92 on site 2), which corresponded to a 345% and 132% increase in abundance (an increase of 141 and 126 individual wild pigs on site 1 and 2, respectively) of each population by the last survey period. Rapid recovery and growth beyond pre-trapping levels of wild pig populations likely were driven by residual wild pigs not removed by trapping and compensatory reproduction and immigration. Our study is one of the first to provide information on how quickly wild pig populations can recover following overall density reductions of 54–68% and indicates practitioners should be prepared to reinitiate trapping efforts in as little as 3 months to prevent recovery of wild pig populations following control.

Biodiversity & Conservation↗
DOE OSTI2022

Using ultrasonic attenuation in cortical bone to infer distributions on pore size

Here, in this work we infer the underlying distribution on pore radius in human cortical bone samples using ultrasonic attenuation data. We first discuss how to formulate polydisperse attenuation models using a probabilistic approach and the Waterman Truell model for scattering attenuation. We then compare the Independent Scattering Approximation and the higher-order Waterman Truell models’ forward predictions for total attenuation in polydisperse samples. Following this, we formulate an inverse problem under the Prohorov Metric Framework coupled with variational regularization to stabilize this inverse problem. We then use experimental attenuation data taken from human cadaver samples and solve inverse problems resulting in nonparametric estimates of the probability density function on pore radius. We compare these estimates to the “true” microstructure of the bone samples determined via microCT imaging. We find that our methodology allows us to reliably estimate the underlying microstructure of the bone from attenuation data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Continuum radiated power density $(P^{\textrm{C}}_{\textrm{rad}})$ and effective charge $(Z_{\textrm{eff}})$ estimates from multi-energy photon-counting measurements

Multi-energy soft x-ray pinhole cameras have been designed, built, calibrated, and operated at Madison symmetric Torus, Alcator C-Mod, and more recently at Tokamak a configuration variable and Tungsten Environment in Steady-State Tokamak (WEST), to measure plasma emission across multiple energy ranges. Here we describe a new methodology to estimate the local continuum radiated power density and the plasma effective charge (Z eff ) directly from photon-counting measurements of the line-free continuum emission (Bremsstrahlung and Radiative Recombination) in several energy bands between 11 and 18 keV. This capability is particularly valuable for confinement systems using metal plasma-facing components, where x-ray losses from interactions with the sputtered wall can represent a significant fraction of the total radiated power (P rad ). The approach leverages a well-characterized detector responsivity, modeled by a complementary error function, and interprets the differential multi-energy measurements between adjacent energy levels through the probability density function of a Gaussian distribution. The implementation of this diagnostic technique is currently under development on the WEST tokamak, aiming at the goal of providing real-time P rad and Z eff measurements during long-pulse operation (up to 1000 s) in the 2026 campaign.

WEST↗
DOE OSTI2022

A reforecasting-based dynamic reserve estimation for variable renewable generation and demand uncertainty

The installed capacity of renewables-based energy sources has been increasing in traditional power systems. In order to accommodate the increased variability and uncertainty associated with the deeper penetration of renewable sources like solar and wind, adjusted amounts of dynamic reserve are needed. Although probabilistic dynamic reserve estimation methods have been previously developed, most of them consider the uncertainty to be represented by parametric density functions that tend to perform poorly under extreme events and, moreover, neglect uncertainty introduced by the forecasting model itself. Toward addressing these limitations, this work presents, for the first time, a dynamic reserve estimation method for flexibility that incorporates nonparametric density estimation and a machine learning based reforecasting to provide a day-ahead prediction of the mean and spread of uncertainty around the base forecast. The prediction is, in turn, used to estimate the up and down reserve relative to the base forecast. Here, the present method takes various endogenous and exogenous features, including the calendar variables, as input to estimate the day-ahead reserve. Using a combination of reforecasting and dynamic reserve estimation techniques, the method is shown to adjust better to the dynamic nature of reserve requirements providing only what is needed to accommodate the expected deviations. Considering California Independent System Operator (CAISO) solar, wind and load data over an 18 month period, up to 67% reduction in the amount of reserve capacity needed for a one day reserve and reserve penalty for solar uncertainty is demonstrated. Additionally, the risk of reserve insufficiency in meeting the net demand is reduced by 20% with the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2026

photoD with Rubin ’s Data Preview 1: First stellar photometric distances and faint blue star deficits

Aims. We investigate the utility of Rubin’s Data Preview 1 (DP1) for estimating stellar number density profiles across the Milky Way halo. Methods. We used stellar broad-band near-UV to near-IR ugrizy photometry released in Rubin’s DP1 to estimate distance and metallicity for blue main sequence stars brighter than r = 24 in three ~1.1 sq. deg. fields at southern Galactic latitudes. Results. Compared to TRILEGAL simulations of the Galaxy’s stellar content, we found a likely deficit of blue main sequence turn-off stars with 22 < r < 24. We interpreted this discrepancy as a signature of a steeper halo number density profile at galactocentric distances 10–50 kpc than the canonical ~1/r 3 profile assumed in TRILEGAL simulations. Conclusions. This interpretation is consistent with earlier suggestions based on observations of more luminous, but much less numerous, evolved stellar populations, along with a few pencil beam surveys of blue main sequence stars in the northern sky. These results bode well for the future Galactic halo exploration with Rubin’s Legacy Survey of Space and Time (LSST).

Galaxy: fundamental parameters↗
DOE OSTI2021

Atom Equivalent Energies for the Rapid Estimation of the Heat of Formation of Explosive Molecules from Density Functional Tight Binding Theory

Atom equivalent energies have been derived from which the gas-phase heat of formation of explosive molecules can be estimated from fast, semiempirical density functional tight binding total energy calculations. The root-mean-square deviation and maximum deviation of the heats of formation from the experimental values for the set of 45 energetic molecules compiled by Byrd and Rice [ J. Phys. Chem. A, 2006, 110, 1005–1013] are 10.4 and 25.5 kcal/mol, respectively, using 4 atom equivalent energies and 7.4 and 15.0 kcal/mol, respectively, using 7 atom equivalent energies. These errors are around a factor of 2–3 larger than those obtained from density functional theory calculations but are smaller than those obtained from other semiempirical electronic structure methods. Heats of formation calculated with density functional tight binding theory using the 4 and 7 atom equivalent energies, the Byrd and Rice scheme, and the atom pair contribution method for a new set of 531 energetic molecules that contain only carbon, hydrogen, nitrogen, and oxygen are provided.

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

Microstructures and mechanical properties of a modified 9Cr ferritic-martensitic steel in the as-built condition after additive manufacturing

A newly developed nano-structured high-Mn 9Cr ferritic-martensitic (FM) steel designed for additive manufacturing (Additive-manufactured Nanostructured Alloy, ANA) was fabricated via the direct energy deposition method. The as-printed ANA2 showed tensile properties (strength and elongation) and Charpy impact toughness (upper-shelf energy and ductile-brittle transition temperature) comparable to oxide-dispersion-strengthened (ODS) Eurofer and PM2000. Compared with wrought P91, the as-built ANA2 showed significantly higher yield strength but inferior Charpy impact toughness and ductility. Microstructural characterization revealed uniformly distributed sub-micron pores, an extremely high dislocation density, and a high density of ultrafine nano-structured precipitates in the matrix. The microstructures indicated the dislocations as the dominant strengthening element and the ultrafine precipitates as the primary contribution to estimated irradiation sink density. This work demonstrates the ability to exploit the unique consolidation properties of additive manufacturing to fabricate steels which marry the benefits of both ODS alloys and conventionally processed FM steels.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coherent Spins in van der Waals Semiconductor GeS 2 at Ambient Conditions

Optically active spin defects in van der Waals (vdW) materials have emerged as versatile quantum sensors, enabling applications for a wide range of quantum phenomena in condensed matter systems. Their ease of exfoliation and compatibility with device integration make them promising candidates for future quantum technologies. Here we report the observation and room-temperature coherent control of ensemble spin defects in the high-temperature crystalline phase of germanium disulfide (β-GeS 2 ), a two-dimensional (2D) semiconductor with low nuclear spin density. The defects exhibit spin-1/2 behavior, and their dynamics can be explained by a weakly coupled spin-pair model. We implement dynamical decoupling techniques to extend the coherence time (T 2 ) by a factor of 20. Finally, we use density functional theory (DFT) calculations to estimate the structures and spin densities of two possible spin defect candidates. This work will help to expand the field of quantum sensing with spin defects in 2D materials.

2D materials↗