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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model

The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicting volume-dependent properties, such as energy storage capacity, due to the intrinsic vacuum within these materials. Although a plethora of experimental techniques, including but not limited to optical contrast, Raman spectroscopy, nonlinear optical spectroscopy, near-field optical imaging, and hyperspectral imaging, facilitate the measurement of 2D material thickness, comprehensive data for many materials remain elusive. Over the past decade, the exponential proliferation of 2D materials and their heterostructures has outstripped the capabilities of conventional experimental and computational approaches. In this evolving landscape, machine learning (ML) has emerged as an indispensable tool, offering a scalable approach to augment these traditional methodologies. Addressing the critical gap, we introduce THICK2D—Thickness Hierarchy Inference and Calculation Kit for 2D Materials. This Python-based computational framework harnesses an autogenerated thickness database, developed using large language models, and advanced ML algorithms to facilitate the rapid and scalable estimation of material thickness, relying solely on crystallographic data. To demonstrate the utility and robustness of THICK2D, we successfully used the toolkit to predict the thickness of more than 8000 2D-based materials, sourced from two extensive 2D materials databases. THICK2D is disseminated as an open-source utility, accessible on GitHub at https://github.com/gmp007/THICK2D, and archived on Zenodo at https://10.5281/zenodo.11216648.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗
DOE OSTI2026

Superlattice reflection signatures of the insulator–metal transition in V 3 O 5 thin films

Nanoelectronic systems that are inspired by the brain are increasingly looking to insulator–metal transition (IMT) materials as they can mimic the response characteristics of neurons to temperature changes so that these can be used in robotic and computational applications. V 3 O 5 has an insulator–metal transition at ∼430 or ∼80 K higher than VO 2 and provides a unique high-temperature opportunity for these types of applications. Here, in this work, we track the structural evolution of V 3 O 5 thin films across the IMT through conventional selected-area electron diffraction (SAED) and four-dimensional scanning TEM (4D-STEM), correlated with temperature-dependent resistance measurements. SAED patterns show reversible evidence of superlattice reflections associated with the IMT—present below T IMT and absent above it—consistent with the accompanying drop in resistance. At room temperature, nanobeam electron diffraction patterns further reveal three local configurations: (i) type I regions with clean patterns lacking superlattice reflections and spot splitting; (ii) type II regions exhibiting rows of superlattice reflections and split spots indicative of crystallographic variants; and (iii) type III regions with negligible superlattice reflections but larger spot splitting suggestive of overlapping domains of insulating and conducting phases likely driven by local lattice distortions. Upon heating, the superlattice reflections disappear between 413 and 453 K, concurrent with the resistance drop at T IMT , consistent with the emergence of a conducting phase. The overall diffraction geometry remains essentially unchanged up to 573 K, implying that relative domain orientations persist through the transition. These observations reveal nanoscale structural heterogeneity in V 3 O 5 thin films across the IMT and inform operation in regimes where mixed-phase textures are expected. A plausible indexing framework rationalizing the observed geometries is presented in the Discussion section, alongside its limitations and alternative interpretations.

25 ENERGY STORAGE↗
DOE OSTI2015

Penta-graphene: A new carbon allotrope

A 2D metastable carbon allotrope, penta-graphene, composed entirely of carbon pentagons and resembling the Cairo pentagonal tiling, is proposed in this paper. State-of-the-art theoretical calculations confirm that the new carbon polymorph is not only dynamically and mechanically stable, but also can withstand temperatures as high as 1000 K. Due to its unique atomic configuration, penta-graphene has an unusual negative Poisson’s ratio and ultrahigh ideal strength that can even outperform graphene. Furthermore, unlike graphene that needs to be functionalized for opening a band gap, penta-graphene possesses an intrinsic quasi-direct band gap as large as 3.25 eV, close to that of ZnO and GaN. Equally important, penta-graphene can be exfoliated from T12-carbon. When rolled up, it can form pentagon-based nanotubes which are semiconducting, regardless of their chirality. When stacked in different patterns, stable 3D twin structures of T12-carbon are generated with band gaps even larger than that of T12-carbon. Finally, the versatility of penta-graphene and its derivatives are expected to have broad applications in nanoelectronics and nanomechanics.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A new regime of nanoscale thermal transport: Collective diffusion increases dissipation efficiency

Understanding thermal transport from nanoscale heat sources is important for a fundamental description of energy flow in materials, as well as for many technological applications including thermal management in nanoelectronics and optoelectronics, thermoelectric devices, nanoenhanced photovoltaics, and nanoparticle-mediated thermal therapies. Thermal transport at the nanoscale is fundamentally different from that at the macroscale and is determined by the distribution of carrier mean free paths and energy dispersion in a material, the length scales of the heat sources, and the distance over which heat is transported. Past work has shown that Fourier’s law for heat conduction dramatically overpredicts the rate of heat dissipation from heat sources with dimensions smaller than the mean free path of the dominant heat-carrying phonons. In this work, we uncover a new regime of nanoscale thermal transport that dominates when the separation between nanoscale heat sources is small compared with the dominant phonon mean free paths. Surprisingly, the interaction of phonons originating from neighboring heat sources enables more efficient diffusive-like heat dissipation, even from nanoscale heat sources much smaller than the dominant phonon mean free paths. This finding suggests that thermal management in nanoscale systems including integrated circuits might not be as challenging as previously projected. In conclusion, we demonstrate a unique capability to extract differential conductivity as a function of phonon mean free path in materials, allowing the first (to our knowledge) experimental validation of predictions from the recently developed first-principles calculations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗
DOE OSTI2016

Physically founded phonon dispersions of few-layer materials and the case of borophene

By building physically sound interatomic force constants,we offer evidence of the universal presence of a quadratic phonon branch in all unstrained 2D materials, thus contradicting much of the existing literature. Through a reformulation of the interatomic force constants (IFCs) in terms of internal coordinates, we find that a delicate balance between the IFCs is responsible for this quadraticity. We use this approach to predict the thermal conductivity of Pmmn borophene, which is comparable to that of MoS 2 , and displays a remarkable in-plane anisotropy. Ultimately, these qualities may enable the efficient heat management of borophene devices in potential nanoelectronic applications

36 MATERIALS SCIENCE↗
DOE OSTI2016

Graphene engineering by neon ion beams

Achieving the ultimate limits of materials and device performance necessitates the engineering of matter with atomic, molecular, and mesoscale fidelity. While common for organic and macromolecular chemistry, these capabilities are virtually absent for 2D materials. In contrast to the undesired effect of ion implantation from focused ion beam (FIB) lithography with gallium ions, and proximity effects in standard e-beam lithography techniques, the shorter mean free path and interaction volumes of helium and neon ions offer a new route for clean, resist free nanofabrication. Furthermore, with the advent of scanning helium ion microscopy, maskless He + and Ne + beam lithography of graphene based nanoelectronics is coming to the forefront. Here, we will discuss the use of energetic Ne ions in engineering graphene devices and explore the mechanical, electromechanical and chemical properties of the ion-milled devices using scanning probe microscopy (SPM). By using SPM-based techniques such as band excitation (BE) force modulation microscopy, Kelvin probe force microscopy (KPFM) and Raman spectroscopy, we demonstrate that the mechanical, electrical and optical properties of the exact same devices can be quantitatively extracted. Additionally, the effect of defects inherent in ion beam direct-write lithography, on the overall performance of the fabricated devices is elucidated.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Thermal transport properties of MoS 2 and MoSe 2 monolayers

Isolation of single to few layer transition metal dichalgogenides open alternate venues in application of 2 dimensional materials to nanoelectronics. Either for general overheating issues or specific application in thermoelectric devices, the characterization of the thermal transport in these new low dimensional materials is needed for their efficient implementation. In this study, lattice thermal conductivities of single layer MoS 2 and MoSe 2 are evaluated using classical molecular dynamics method. The interactions between atoms are defined by Stillinger-Weber type empirical potentials that are developed to represent structural, mechanical, and vibrational properties of the given materials. In parameterization of the potentials, a stochastic optimization algorithm, namely particle swarm optimization is utilized. The final parameter sets produce quite consistent results with DFT in terms of lattice parameters, bond distances, elastic constants and vibrational properties of both single layer MoS 2 and MoSe 2 . The predicted thermal properties of both materials are in very good agreement with earlier first principles calculations. The discrepancies between calculations and experimental measurements are most likely to be caused by pristine nature of the structures in our simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Sub-10 nm patterning with DNA nanostructures: a short perspective

DNA is the hereditary material that contains our unique genetic code. Since the first demonstration of two-dimensional (2D) nanopatterns by using designed DNA origami ~10 years ago, DNA has evolved into a novel technique for 2D and 3D nanopatterning. It is now being used as a template for the creation of sub-10 nm structures via either 'top-down' or 'bottom-up' approaches for various applications spanning from nanoelectronics, plasmonic sensing, and nanophotonics. This paper starts with an histroric overview and discusses the current state-of-the-art in DNA nanolithography. Finally, emphasis is put on the challenges and prospects of DNA nanolithography as the next generation nanomanufacturing technique.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Phase transition in bilayer MoS 2 under tensile loading: a molecular dynamics study

Abstract Molybdenum disulfide (MoS 2 ), especially single-layer MoS 2 , has been experimentally and computationally discovered to exist in several different polymorphs exhibiting various electronic and mechanical properties. The morphology of MoS 2 can be tuned through strain engineering. Molecular dynamics simulations are conducted to systematically study the phase transition of single-layer MoS 2 and bilayer MoS 2 under the uniaxial tensile condition at room temperature. The roles of edge and S-line vacancy are investigated. Phase transitions are always triggered near the edge and vacancy sites. The initiation of the metastable T″ phase can release the tensile stress in the lattice, followed by I4/mmm phase initiation, regardless of the edge conditions. The growth of the I4/mmm phase can cause the local buckling of the MoS 2 plane. With a tilted S-line vacancy, I4/mmm phase is first initiated to reduce the local shear stress accumulated near the vacancy line. Overall, the phase transition mechanism of single layer and bilayer MoS 2 under the uniaxial tensile loading is provided, which guides the future strain engineering of MoS 2 in nanoelectronics applications.

Materials Science↗
DOE OSTI2025

Aging studies on chemical vapor deposition and mechanically exfoliated molybdenum disulfide flakes heated in ambient air

The structural integrity of atomically thin two-dimensional molybdenum disulfide (MoS 2 ) is crucial for high-temperature applications, including nanoelectronics and optoelectronics. This study explores the structural stability and electrical performance, under extended thermal exposure in air, of MoS 2 flakes synthesized via chemical vapor deposition (CVD) and mechanical exfoliation. The MoS 2 flakes, both CVD-grown and mechanically exfoliated, were subjected to heating at 200 °C with a relative humidity of 60(±5)% for a prolonged period and investigated with atomic force microscopy and Raman spectroscopy. This study shows that CVD-grown flakes developed noticeable cracks after prolonged heating, whereas mechanically exfoliated flakes mostly retained their structural integrity. Also, both types of flakes showed a decrease in layer thickness and lateral size over time, with mechanically exfoliated flakes exhibiting a comparatively smaller reduction in substrate coverage area. In addition, MoS 2 -based two-terminal devices were subjected to heating at 150 °C for approximately 1100 h, and their electrical characterization revealed a steady rise in current during constant voltage (5 V) conditions. This study enhances our understanding of MoS 2 stability and provides guidance for improving the reliability of MoS 2 -based devices in high-temperature electronic applications.

2D materials↗
DOE OSTI2021

Epitaxial growth of monolayer PdTe 2 and patterned PtTe 2 by direct tellurization of Pd and Pt surfaces

Two-dimensional (2D) palladium ditelluride (PdTe 2 ) and platinum ditelluride (PtTe 2 ) are two Dirac semimetals, which have fascinating quantum properties such as superconductivity, magnetism and topological order and show the promising applications in future nanoelectronics and optoelectronics. However, the synthesis of PdTe 2 and PtTe 2 monolayers (MLs) is hindered by a strong interlayer coupling and orbital hybridization. Here, in this study, we demonstrate an efficient synthesis of PdTe 2 and PtTe 2 MLs Large-area and high quality MLs of PdTe 2 and patterned PtTe 2 were epitaxially grown on the Pd(111) and Pt(111) surfaces by direct telurization in ultra-high vacuum. This was confirmed by x-ray photoelectron spectroscopy, low energy electron diffraction and scanning tunnelling microscopy. PdTe 2 ML demonstrated high thermal stability showing no decomposition sign after annealing at 470 °C. A well-ordered (2 × 2) PtTe 2 structure with Kagome lattice was observed on Te/Pt(111) surface following annealing at 200 °C in UHV, where the (2 × 2) pattern was formed by Te atom vacancies. PtTe 2 multilayer film was prepared as well, and it demonstrated the excitation of the Dirac plasmons as measured by high-resolution electron energy loss spectroscopy. The direct tellurization offers the simple and reliable protocol for the preparation of the ML of PdTe 2 and patterned PtTe 2 , and this opens new opportunities for quantum phenomena research and for practical optoelectronics applications.

2D materials↗
DOE OSTI2021

Layer and material-type dependent photoresponse in Se 2 /WS 2 vertical heterostructures

Transition metal dichalcogenide (TMD) heterostructures are promising for a variety of applications in photovoltaics and photosensing. Successfully exploiting these heterostructures will require an understanding of their layer-dependent electronic structures. However, there is no experimental data demonstrating the layer-number dependence of photovoltaic effects (PVEs) in vertical TMD heterojunctions. Here, by combining scanning electrochemical cell microscopy (SECCM) with optical probes, we report the first layer-dependence of photocurrents in WSe 2 /WS 2 vertical heterostructures as well as in pristine WS 2 and WSe 2 layers. For WS 2 , we find that photocurrents increase with increasing layer thickness, whereas for WSe 2 the layer dependence is more complex and depends on both the layer number and applied bias (V b ). Further, we find that photocurrents in the WSe 2 /WS 2 heterostructures exhibit anomalous layer and material-type dependent behaviors. Our results advance the understanding of photoresponse in atomically thin WSe 2 /WS 2 heterostructures and pave the way to novel nanoelectronic and optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Artificial intelligence for advanced functional materials: exploring current and future directions

This perspective addresses the topic of harnessing the tools of artificial intelligence (AI) for boosting innovation in functional materials design and engineering as well as discovering new materials for targeted applications in energy storage, biomedicine, composites, nanoelectronics or quantum technologies. It gives a current view of experts in the field, insisting on challenges and opportunities provided by the development of large materials databases, novel schemes for implementing AI into materials production and characterization as well as progress in the quest of simulating physical and chemical properties of realistic atomic models reaching the trillion atoms scale and with near ab initio accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine learning-based interatomic potential development and phase transition analysis of ferroelectric hafnium dioxide

The ferroelectric phase (𝑃⁢𝑐⁢𝑎⁢2 1 , which is in orthorhombic symmetry) of hafnium dioxide (HfO 2 ) has gained much attention due to its potential applications in nanoelectronics and advanced memory devices. However, its complex phase behavior under external stimuli, such as pressure and temperature, remains a subject of intense investigation. This study focuses on developing a machine learning-based interatomic potential (MLIP) that is trained with data from density-functional theory (DFT) calculations to simulate phase transitions and mechanical properties of HfO 2 . The developed MLIP predicts lattice parameters, equations of state, bulk and shear moduli, and elastic constants that closely align with DFT predictions for several phases and at various pressures. Once validated, the MLIP is used to investigate the phase transitions of ferroelectric HfO 2 (𝑃⁢𝑐⁢𝑎⁢2 1 ) under both isobaric and constant stress conditions at elevated temperatures ranging from 200 to 2500 K. We used several complementary methods, including local symmetry identification, radial distribution function, and x-ray diffraction characterization, to identify interesting phase transitions among several competitive hafnia phases predicted from our simulations. The suggested methods uniformly reveal that under pure deviatoric condition, the system favors a transition from the orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase to a tetragonal (𝑃⁢4 2 /𝑛⁢𝑚⁢𝑐) phase, whereas a zero stress condition drives the system from the 𝑃⁢𝑐⁢𝑎⁢2 1 phase to another orthorhombic (𝑃⁢𝑏⁢𝑐⁢𝑛) phase. These findings provide crucial insights into stress and temperature-induced phase behavior of hafnia, guiding future experimental and theoretical studies for optimizing hafnia-based ferroelectric devices.

Ferroelectric HfO2↗
DOE OSTI2019

Engineering Nanoscale Thermal Transport: Size- and Spacing-Dependent Cooling of Nanostructures

Nanoscale thermal transport is becoming ever more technologically important with the development of next-generation nanoelectronics, nanomediated thermal therapies, and high efficiency thermoelectric devices. However, direct experimental measurements of nondiffusive heat flow in nanoscale systems are challenging, and first-principle models of real geometries are not yet computationally feasible. In recent work, we used ultrafast pulses of short-wavelength light to uncover a previously-unobserved regime of nanoscale thermal transport that occurs when the width and separation of heat sources are comparable to the mean free paths of the dominant heat-carrying phonons in the substrate. We now systematically compare thermal transport from gratings of metallic nanolines with different periodicities, on both silicon and fused-silica substrates, to map the entire nanoscale thermal transport landscape – from closely spaced through increasingly isolated to fully isolated heat-transfer regimes. By monitoring the surface profile dynamics with subangstrom sensitivity, we directly measure thermal transport from the nanolines into the substrate. This allows us to quantify for the first time how the nanoline separation significantly impacts thermal transport into the substrate, making it possible to reach efficiencies that are within a factor of 2 of the diffusive (i.e., thin-film) limit. We also show that partially isolated nanolines perform significantly worse, because cooling occurs in a regime that is intermediate between close-packed and fully isolated heat sources. This work thus confirms the surprising prediction that closely spaced nanoscale heat sources can cool more quickly than when far apart. In conclusion, these results show that our predictive model is validated by experiment over a broad parameter space, which is important for benchmarking theories that go beyond the Fourier model of heat diffusion, and for informed design of nanoengineered systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Correlation Between Corrugation-Induced Flexoelectric Polarization and Conductivity of Low-Dimensional Transition Metal Dichalcogenides

The tunability of polar and semiconducting properties of low-dimensional transition metal dichalcogenides (TMDs) have propelled them to the forefront of fundamental and applied physical research. These materials can vary their electrophysical properties from nonpolar to ferroelectric, and from direct-band semiconducting to metallic. In addition to classical controlling factors, such as field effect, composition, and doping, new degrees of freedom emerge in TMDs due to the curvature-induced electron redistribution and the associated changes in electronic properties. Here we theoretically explore the elastic and electric fields, flexoelectric polarization and free charge density for a TMD nanoflake placed on a rough substrate with a sinusoidal corrugation profile. Finite element modelling results for different flake thickness and corrugation depth yield insights into the flexoelectric nature of the out-of-plane electric polarization and establish the unambiguous correlation between the polarization and static conductivity modulation. The modulation is caused by the coupling between the deformation potential and inhomogeneous elastic strains, which evolve in the TMD nanoflake due to the adhesion between the flake surface and corrugated substrate. We reveal a pronounced maximum in the thickness dependences of the electron and hole conductivity of MoS 2 and MoTe 2 nanoflakes placed on a corrugated substrate, which opens the way for the optimization of their geometry towards significant improvement in their polar and electronic properties, necessary for advanced applications in nanoelectronics and memory devices. Specifically, the obtained results can be useful for the development of nanoscale straintronic devices based on the bended MoS 2 , MoTe 2 , and MoSTe nanoflakes, such as diodes and bipolar transistors with a bending-controllable sharpness of p-n junctions.

42 ENGINEERING↗
DOE OSTI2015

Designing Ferroelectric Field-Effect Transistors Based on the Polarization-Rotation Effect for Low Operating Voltage and Fast Switching

The effect of polarization rotation on the performance of metal-oxide-semiconductor field-effect transistors is investigated with a Landau-Ginzburg-Devonshire theory-based model. In this analytical model, the depolarization field, polarization rotations, and electrostatic properties of the doped silicon substrate are considered to illustrate the size effect of ferroelectric oxides and the stability of polarization in each direction. Based on this model, we provide guidance in designing electronic logic devices with low operating voltages and low active-energy consumption: First, we demonstrate that MOSFET operation could be achieved by polarization reorientation with a low operating voltage, if the thickness of the ferroelectric oxide is properly selected. Polarization reorientation can boost the surface potential of the silicon substrate, leading to a subthreshold swing S lower than 60mV/decade. We also demonstrate that, compared with polarization inversion, polarization rotation offers significant advantages, including a lower energy barrier and a wider range of transferability in nanoelectronic devices.

36 MATERIALS SCIENCE↗