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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Computational synthesis of 2D materials: A high-throughput approach to materials design

2D materials find promising applications in next-generation devices, however, large-scale, low-defect, and reproducible synthesis of 2D materials remains a challenging task. Here, to assist in the selection of suitable substrates for the synthesis of as-yet hypothetical 2D materials, we have developed an open-source high-throughput workflow package, Hetero2d, that searches for low-lattice mismatched substrate surfaces for any 2D material and determines the stability of these 2D-substrate heterostructures using density functional theory (DFT) simulations. Hetero2d automates the generation of 2D-substrate heterostructures, the creation of DFT input files, the submission and monitoring of computational jobs on supercomputing facilities, and the storage of relevant parameters alongside the post-processed results in a MongoDB database. We demonstrate the capability of Hetero2d in identifying stable 2D-substrate heterostructures for four 2D materials, namely 2H-MoS 2 , 1T- and 2H-NbO 2 , and hexagonal-ZnTe, considering 50 cubic elemental substrates. We find Cu, Hf, Mn, Nd, Ni, Pd, Re, Rh, Sc, Ta, Ti, V, W, Y, and Zr substrates sufficiently stabilize the formation energies of these 2D materials, with binding energies in the range of ~0.1–0.6 eV/atom. Upon examining the z-separation, the charge transfer, and the electronic density of states at the 2D-substrate interface, we find a covalent type bonding at the interface which suggests that these substrates can be used as contact materials for the 2D materials. Hetero2d is available on GitHub as an open-source package under the GNU license.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An Investigation of Thermal Properties of 2D Materials [Dissertation]

Studying the thermal conductivity of 2D materials is important due to the applications of 2D materials in fields such as thermal management, thermoelectricity, renewable energy, and sensors. As such, measurements of the thermal conductivity of these 2D materials become important to measure. Thermal conductivity is often difficult to measure for 2D materials due to their atomically thin nature and many experimental methods for doing so requiring contact with the sample, which can alter the thermal properties. A non-contact method for calculating the thermal conductivity of 2D materials supported on substrates in order to model the thermal conductivity of 2D materials for devices, is proposed and experimentally performed in this dissertation. The optothermal Raman technique is a useful non-contact diagnostic technique useful in determining the thermal conductivity of 2D materials. The optothermal Raman typically does not account for heat losses due to convection or radiation or substrate resistance, which are shown to be important factors to consider when developing an optothermal Raman model. Additionally, the calculation of the interfacial thermal conductance between the bottom surface of the sample and the top surface of the substrate, plays an important role in determining the final value of the thermal conductivity of a supported sample, and will yield differing results based on whether or not the conductance is calculated using an approach such as the Diffuse Mismatch Model (DMM) or calculated directly by varying the laser heating profile (usually done by changing the laser objective). This is shown to be the case for both graphene on Ni, graphene on Cu, and SnSe 2 on Cu. In addition to experimentally calculating the thermal conductivity of a 2D material with the optothermal Raman technique, the thermal conductivity of 2D materials can also be calculated using computational methods. The three-phonon method is a method which can be used to simulate phonon scattering processes and determine the thermal conductivity of semiconductors, wherein phonon scattering is the dominant mechanism which determines the thermal conductivity. The three-phonon method uses relaxation times for phonon scattering with other phonons, electrons, and other material system elements, such as isotopes or material defects, in order to create a single-mode relaxation time approximation (SMRTA), which is used to calculate the final value of the thermal conductivity. An important consideration when determining the thermal conductivity of a 2D material using this method is the device geometry, which is reflected in this work as the phonon-boundary scattering relaxation time. This inclusion is important along with the inclusion of phonon-electron scattering in accurately determining the thermal conductivity of a 2D material. In both the optothermal Raman experiments and the three-phonon method computations, strain is shown to have a demonstrable effect on the thermal conductivity of 2D materials. When a 1.1% strain was applied to the mechanical properties of SnSe, the three-phonon processes yielded a lower thermal conductivity than the no-strain case. For the optothermal Raman experiments, the strain induced in the Cu substrate and transferred to a single-layer graphene (SLG) sample yields a trend where the thermal conductivity of the SLG decreases with respect to strain applied. In the case where the interfacial thermal conductance was calculated directly, the conductance increased with respect to strain applied. This presents strain as a reliable and viable method for tuning the thermal properties of 2D materials for device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Beyond Graphene: Low-Symmetry and Anisotropic 2D Materials

Low-symmetry 2D materials—such as ReS 2 and ReSe 2 monolayers, black phosphorus monolayers, group-IV monochalcogenide monolayers, borophene, among others—have more complex atomistic structures than the honeycomb lattices of graphene, hexagonal boron nitride, and transition metal dichalcogenides. The reduced symmetries of these emerging materials give rise to inhomogeneous electron, optical, valley, and spin responses, as well as entirely new properties such as ferroelasticity, ferroelectricity, magnetism, spin-wave phenomena, large nonlinear optical properties, photogalvanic effects, and superconductivity. Novel electronic topological properties, nonlinear elastic properties, and structural phase transformations can also take place due to low symmetry. Lastly, the “Beyond Graphene: Low-Symmetry and Anisotropic 2D Materials” Special Topic was assembled to highlight recent experimental and theoretical research on these emerging materials.

2D materials↗
DOE OSTI2025

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗
DOE OSTI2020

A Scalable Method for Thickness and Lateral Engineering of 2D Materials

The physical properties of two-dimensional (2D) materials depend strongly on the number of layers. Hence, methods for controlling their thickness with atomic layer precision are highly desirable, yet still too rare, and demonstrated for only a limited number of 2D materials. Here we present a simple and scalable method for the continuous layer-by-layer thinning that works for a large class of 2D materials, notably layered germanium pnictides and chalcogenides. It is based on a simple oxidation/etching process, which selectively occurs on the topmost layers. Through a combination of atomic force microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy and X-ray diffraction experiments we demonstrate the thinning method on germanium arsenide (GeAs), germanium sulfide (GeS) and germanium disulfide (GeS 2 ). We use first-principles simulation to provide insights into the oxidation mechanism. Our strategy, which could be applied to other classes of 2D materials upon proper choice of the oxidation/etching reagent, could pave the way for the realization of 2D material-based devices, such as electronic or optoelectronic ones, where a precise control over the number of layers (hence over the material’s physical properties) is needed. We also show that when used in combination with lithography, our method can be used to make precise patterns in the 2D materials.

2D materials↗
DOE OSTI2022

Understanding, discovery, and synthesis of 2D materials enabled by machine learning

Machine learning (ML) is becoming an effective tool for studying 2D materials. Taking as input computed or experimental materials data, ML algorithms predict the structural, electronic, mechanical, and chemical properties of 2D materials that have yet to be discovered. Such predictions expand investigations on how to synthesize 2D materials and use them in various applications, as well as greatly reduce the time and cost to discover and understand 2D materials. This tutorial review focuses on the understanding, discovery, and synthesis of 2D materials enabled by or benefiting from various ML techniques. Here, we introduce the most recent efforts to adopt ML in various fields of study regarding 2D materials and provide an outlook for future research opportunities. The adoption of ML is anticipated to accelerate and transform the study of 2D materials and their heterostructures.

2D Materials↗
DOE OSTI2021

Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials

Abstract Mechanical behavior of 2D materials such as MoS 2 can be tuned by the ancient art of kirigami. Experiments and atomistic simulations show that 2D materials can be stretched more than 50% by strategic insertion of cuts. However, designing kirigami structures with desired mechanical properties is highly sensitive to the pattern and location of kirigami cuts. We use reinforcement learning (RL) to generate a wide range of highly stretchable MoS 2 kirigami structures. The RL agent is trained by a small fraction (1.45%) of molecular dynamics simulation data, randomly sampled from a search space of over 4 million candidates for MoS 2 kirigami structures with 6 cuts. After training, the RL agent not only proposes 6-cut kirigami structures that have stretchability above 45%, but also gains mechanistic insight to propose highly stretchable (above 40%) kirigami structures consisting of 8 and 10 cuts from a search space of billion candidates as zero-shot predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Toward non-Si electronics: From remote epitaxy to layer splitting of 2D materials for mixed dimensional heterostructures

The current electronics has been mainly dominated by Si-based devices due to their mature processing system and exceptional cost-effectiveness. However, next generation electronics needs novel functionalities that cannot be realized by Si because of intrinsic limitation of Si. Accordingly, demand for non-Si electronics has been getting substantially high. Unfortunately, current methodology requires extremely high cost for non-Si materials, which impedes the progress in developing the non-Si based electronics. Here, I will discuss about our group’s efforts to address this issue. Our team recently conceived a new crystalline growth, termed as “remote epitaxy”, which can copy/paste crystalline information from substrates remotely through graphene, thus generating single-crystalline films on graphene. As interfacial binding energy is attenuated by inserting graphene at interface, the single-crystalline films can be easily exfoliated from the slippery graphene surface. Also, the graphene-coated substrates can be, in principle, reused infinitely to produce single-crystalline films. Thus, the remote epitaxy can produce non-Si semiconductor films with unprecedented cost efficiency while allowing additional flexible device functionality required for current ubiquitous electronics. Next, I will discuss about a layer splitting technique which can be a potential solution to overcome the problem in obtaining large-scale and monolayer 2D materials. A 2D material-based heterostructure has been intensively studied because of its unique device functionalities and novel physics. However, it is extremely challenging to secure large-scale and monolayer 2D materials because of following issues: 1) poor scalability for laboratory fabrication processes of 2D heterostructures and 2) lack of well-defined control parameters for kinetics of 2D materials and predictable number of layers of 2D materials. To resolve this issue, we conceived a new approach called “layer-resolved splitting” which obtains multiple monolayer from multilayer 2D materials by controlling interfacial toughness contrast. As this method is versatile and universal, we can, in principle, apply to all 2D materials. We succeeded in having large-scale, monolayer 2D materials through our approach and, thereby 2D heterostructures were demonstrated for functional devices. Lastly, I would like to discuss opportunities of mixed-dimensional heterostructure demonstrated by remote epitaxy and layer-resolved splitting. As they produce freestanding 3D bulk films and 2D atomic layers, a new type of 3D/2D heterostructures can be realized where a new physics and new device architecture are revealed. Therefore, I believe that a new opportunity will be discovered through the mixed-dimensional heterostructures.

Bae, Sang-Hoon↗
DOE OSTI2021

Work Function Engineering of 2D Materials: The Role of Polar Edge Reconstructions

2D materials have attracted tremendous interest as functional materials because of their diverse and tunable properties, especially at their edges. A material’s work function is a critical parameter in many electronic devices; however, a fundamental understanding and a path toward large alterations of the work function in 2D materials still remain elusive. Here in this paper, we report the first evidence for anisotropy of the work function in 2D MoS 2 from first-principles calculations. We also demonstrate large work-function tunability (in the range of 3.45–6.29 eV) choosing the 2H phase of MoS 2 as a model system by sampling various edge configurations. We furthermore reveal the origin of this work function anisotropy and tunability by extending the existing work function relation to the local dipole moment at surfaces of 3D materials to those at edges in 2D materials. We then use machine-learning approaches to correlate work function with edge structures. These results pave the way for intrinsic edge engineering for electronic and catalytic applications.

36 MATERIALS SCIENCE↗
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 OSTI2021

Intercalation as a versatile tool for fabrication, property tuning, and phase transitions in 2D materials

Recent advances in two-dimensional (2D) materials have led to the renewed interest in intercalation as a powerful fabrication and processing tool. Intercalation is an effective method of modifying the interlayer interactions, doping 2D materials, modifying their electronic structure or even converting them into starkly different new structures or phases. Herein, we discuss different methods of intercalation and provide a comprehensive review of various roles and applications of intercalation in next-generation energy storage, optoelectronics, thermoelectrics, catalysis, etc. The recent progress in intercalation effects on crystal structure and structural phase transitions, including the emergence of quantum phases are also reviewed.

2D materials↗
DOE OSTI2024

Colloquium : Sliding and pinning in structurally lubric 2D material interfaces

A plethora of two-dimensional (2D) materials have been introduced in physics and engineering in the past two decades. Their robust, membranelike sheets permit (mostly require) deposition, giving rise to solid-solid dry interfaces whose mobility, pinning, and general tribological properties under shear stress are currently being understood and controlled, both experimentally and theoretically. Here, in this Colloquium simulated case studies of twisted graphene systems are used as a prototype workhorse tool to demonstrate and discuss the general picture of 2D material interface sliding. First highlighted is the crucial mechanical difference, often overlooked, between small and large incommensurabilities, which corresponds to, for example, small and large twist angles in graphene interfaces. In both cases, focusing on flat, structurally lubric or “superlubric” geometries, the generally separate scalings with the area of static friction in pinned states and of kinetic friction during sliding are elucidated and reviewed, tangled as they are with the effects of velocity, temperature, load, and defects. The roles of island boundaries and elasticity are also discussed, and compared when possible to results in the literature for systems other than graphene. It is proposed that the resulting picture of pinning and sliding should be applicable to interfaces in generic 2D materials that are of importance for the physics and technology of existing and future bilayer and multilayer systems.

2-dimensional systems↗
DOE OSTI2024

A metastable pentagonal 2D material synthesized by symmetry-driven epitaxy

Most two-dimensional (2D) materials experimentally studied so far have hexagons as their building blocks. Only a few exceptions, such as PdSe 2 , are lower in energy in pentagonal phases and exhibit pentagons as building blocks. Although theory has predicted a large number of pentagonal 2D materials, many of these are metastable and their experimental realization is difficult. Here, in this paper, we report the successful synthesis of a metastable pentagonal 2D material, monolayer pentagonal PdTe 2 , by symmetry-driven epitaxy. Scanning tunnelling microscopy and complementary spectroscopy measurements are used to characterize this material, which demonstrates well-ordered low-symmetry atomic arrangements and is stabilized by lattice matching with the underlying Pd(100) substrate. Theoretical calculations, along with angle-resolved photoemission spectroscopy, reveal monolayer pentagonal PdTe 2 to be a semiconductor with an indirect bandgap of 1.05 eV. Our work opens an avenue for the synthesis of pentagon-based 2D materials and gives opportunities to explore their applications such as multifunctional nanoelectronics.

interfaces↗
DOE OSTI2025

Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods

The field of 2D materials has grown dramatically in the past two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computing applications. These 2D structures, which are often exfoliated from layered van der Waals materials, possess highly inhomogeneous electron densities and can possess short- and long-range electron correlations. The complexities of 2D materials make them challenging to study with standard mean-field electronic structure methods such as density functional theory (DFT), which relies on approximations for the unknown exchange-correlation functional. To overcome the limitations of DFT, highly accurate many-body electronic structure approaches such as diffusion Monte Carlo (DMC) can be utilized. In the past decade, DMC has been used to calculate accurate magnetic, electronic, excitonic, and topological properties in addition to accurately capturing interlayer interactions and cohesion and adsorption energetics of 2D materials. Here, this approach has been applied to 2D systems of wide interest, including graphene, phosphorene, MoS 2 , CrI 3 , VSe 2 , GaSe, GeSe, borophene, and several others. In this review article, we highlight some successful recent applications of DMC to 2D systems for improved property predictions beyond standard DFT.

2D materials↗
DOE OSTI2025

Ionic‐Liquid Free and Flexible Transistors Made of 2D Material Inks

The development of thin-film transistors (TFTs) using 2D materials is crucial for enabling scalable, low-cost, and flexible electronics. Currently, 2D TFTs with the highest performance have been achieved by using ionic-liquid gating (ILG), a technique suited for proof-of-concept studies. However, ILG suffers from slow switching speeds, temperature sensitivity, poor long-term stability, and integration challenges, making it unsuitable for practical use. Moreover, typical fabrication methods for 2D TFTs involve harsh conditions such as strong acids or high temperatures (>300 °C), limiting integration with flexible substrates. This work provides the first demonstration of an ILG-free, all-2D-material TFT fabricated onto a flexible substrate. Water-based graphene and hexagonal boron nitride (h-BN) inks are printed to deposit the electrodes and dielectric layers, respectively. The MoS 2 channel is produced via supramolecular interfacial self-assembly, yielding uniform, monolayer-rich films transferable to rigid and flexible substrates. The resulting TFTs operate below 3 V, exhibit negligible leakage current, and achieve field-effect mobilities up to 0.46 cm 2 V −1 s −1 (rising to 2.47 cm 2 V −1 s −1 with silver electrodes) measured under ambient conditions, while maintaining excellent mechanical flexibility. This work establishes a low-cost and scalable solution-processable platform for flexible electronics based on 2D materials that match requirements for practical applications.

2D materials↗
DOE OSTI2021

Realization of an Ideal Cairo Tessellation in Nickel Diazenide NiN 2 : High-Pressure Route to Pentagonal 2D Materials

Most of the studied two-dimensional (2D) materials are based on highly symmetric hexagonal structural motifs. In contrast, lower-symmetry structures may have exciting anisotropic properties leading to various applications in nanoelectronics. In this work we report the synthesis of nickel diazenide NiN 2 which possesses atomic-thick layers comprised of Ni 2 N 3 pentagons forming Cairo-type tessellation. The layers of NiN 2 are weakly bonded with the calculated exfoliation energy of 0.72 J/m 2 , which is just slightly larger than that of graphene. The compound crystallizes in the space group of the ideal Cairo tiling (P4/mbm) and possesses significant anisotropy of elastic properties. The single-layer NiN 2 is a direct-band-gap semiconductor, while the bulk material is metallic. Furthermore, this indicates the promise of NiN 2 to be a precursor of a pentagonal 2D material with a tunable direct band gap.

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

Emulating 2D Materials with Magnons

Spin waves (magnons) in two-dimensional (2D) materials have received increasing interest due to their unique states and potential for tunability. However, many interesting features of these systems, including Dirac points and topological states, occur at high frequencies, where experimental probes are limited. Here, we study a crystal formed by patterning a hexagonal array of holes in a perpendicularly magnetized thin film. Through simulation, we find that the magnonic band structure imitates that of graphene, but additionally has some kagomelike character and includes a few flat bands. Surprisingly, its nature can be understood using a nine-band tight-binding Hamiltonian. This clear analogy to 2D materials enables band-gap engineering in 2D, topological magnons along 1D phase boundaries, and spectrally isolated modes at 0D point defects. Interestingly, the 1D phase boundaries allow access to the valley degree of freedom through a magnonic analog of the quantum valley Hall insulator. These approaches can be extended to other magnonic systems, but are potentially more general due to the simplicity of the model, which resembles existing results from electron, phonon, photon, and cold-atom systems. This finding brings the physics of spin waves in 2D materials to more experimentally accessible scales, augments it, and outlines a few principles for controlling magnonic states.

Ferrimagnets↗