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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nonlinear optics in 2D materials: From classical to quantum

Nonlinear optics has long been a cornerstone of modern photonics, enabling a wide array of technologies, from frequency conversion to the generation of ultrafast light pulses. Recent breakthroughs in two-dimensional (2D) materials have opened a frontier in this field, offering new opportunities for both classical and quantum nonlinear optics. These atomically thin materials exhibit strong light–matter interactions and large nonlinear responses, thanks to their tunable lattice symmetries, strong resonance effects, and highly engineerable band structures. In this paper, we explore the potential that 2D materials bring to nonlinear optics, covering topics from classical nonlinear optics to nonlinearities at the few-photon level. We delve into how these materials enable possibilities, such as symmetry control, phase matching, and integration into photonic circuits. The fusion of 2D materials with nonlinear optics provides insights into the fundamental behaviors of elementary excitations—such as electrons, excitons, and photons—in low-dimensional systems and has the potential to transform the landscape of next-generation photonic and quantum technologies.

2D materials↗
DOE OSTI2024

Emergence of two distinct phase transitions in monolayer CoSe2 on graphene

Abstract Dimensional modifications play a crucial role in various applications, especially in the context of device miniaturization, giving rise to novel quantum phenomena. The many-body dynamics induced by dimensional modifications, including electron-electron, electron-phonon, electron-magnon and electron-plasmon coupling, are known to significantly affect the atomic and electronic properties of the materials. By reducing the dimensionality of orthorhombic CoSe 2 and forming heterostructure with bilayer graphene using molecular beam epitaxy, we unveil the emergence of two types of phase transitions through angle-resolved photoemission spectroscopy and scanning tunneling microscopy measurements. We disclose that the 2 × 1 superstructure is associated with charge density wave induced by Fermi surface nesting, characterized by a transition temperature of 340 K. Additionally, another phase transition at temperature of 160 K based on temperature dependent gap evolution are observed with renormalized electronic structure induced by electron-boson coupling. These discoveries of the electronic and atomic modifications, influenced by electron-electron and electron-boson interactions, underscore that many-body physics play significant roles in understanding low-dimensional properties of non-van der Waals Co-chalcogenides and related heterostructures. Graphical Abstract

36 MATERIALS SCIENCE↗
DOE OSTI2025

Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design

Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data, for ML training. In this study, we report a data-efficient, deep-learning framework for molecular discovery that integrates a coarse-grained functional-group representation with a self-attention mechanism to capture intricate chemical interactions. Our approach exploits group-contribution concepts to create a graph-based intermediate representation of molecules, serving as a low-dimensional embedding that substantially reduces the data demands typically required for training. Using a self-attention mechanism to learn the subtle but highly relevant chemical context of functional groups, the method proposed here consistently outperforms existing approaches for predictions of multiple thermophysical properties. In a case study focused on adhesive polymer monomers, we train on a limited dataset comprising only 6,000 unlabeled and 600 labeled monomers. The resulting chemistry prediction model achieves over 92% accuracy in forecasting properties directly from SMILES strings, exceeding the performance of current state-of-the-art techniques. Furthermore, the latent molecular embedding is invertible, enabling the design pipeline to automatically generate new monomers from the learned chemical subspace. We illustrate this functionality by targeting several properties, including high and low glass transition temperatures (Tg), and demonstrate that our model can identify new candidates with values that surpass those in the training set. The ease with which the proposed framework navigates both chemical diversity and data scarcity offers a promising route to accelerate and broaden the search for functional materials.

Han, Ming [Univ. of Chicago, IL (United States)]↗
DOE OSTI2025

Physics-informed latent neural operator for real-time predictions of time-dependent parametric PDEs

Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between infinite-dimensional function spaces. However, when applied to systems with high-dimensional input-output mappings arising from large numbers of spatial and temporal collocation points, these models often require heavily overparameterized networks, leading to long training times. Latent DeepONet addresses some of these challenges by introducing a two-step approach: first learning a reduced latent space using a separate model, followed by operator learning within this latent space. While efficient, this method is inherently data-driven and lacks mechanisms for incorporating physical laws, limiting its robustness and generalizability in data-scarce settings. Here, in this work, we propose PI-Latent-NO, a physics-informed latent neural operator framework that integrates governing physics directly into the learning process. Our architecture features two coupled DeepONets trained end-to-end: a Latent-DeepONet that learns a low-dimensional representation of the solution, and a Reconstruction-DeepONet that maps this latent representation back to the physical space. By embedding PDE constraints into the training via automatic differentiation, our method eliminates the need for labeled training data and ensures physics-consistent predictions. The proposed framework is both memory and compute-efficient, exhibiting near-constant scaling with problem size and demonstrating significant speedups over traditional physics-informed operator models. We validate our approach on a range of parametric PDEs, showcasing its accuracy, scalability, and suitability for real-time prediction in complex physical systems.

Latent representations↗
DOE OSTI2026

Two-Dimensional Perovskite Single-Nanowire Photodetectors

High-performance microphotodetectors require materials that combine strong light–matter interaction, fast charge transport, and ambient stability. Here, we demonstrate single-nanowire devices based on the 2D perovskite (TPA3) 2 PbBr 4 , synthesized via a controlled slow-cooling self-assembly process that yields defect-minimized, anisotropic nanowires with smooth facets. These microphotodetectors exhibit ultralow dark currents (∼10 –15 A), high responsivity (up to 156 mA W –1 ), and exceptional specific detectivity (∼10 11 Jones) under near-UV (405 nm) illumination, with rise and fall times in the millisecond regime. The superior detectivity is primarily driven by the suppression of thermal noise through the material’s ultralow dark current, while the millisecond temporal response is governed by high-intensity trap-filling dynamics. The devices maintain stable operation over 4000 s of continuous on/off cycling and show remarkable ambient stability over weeks, attributed to dense crystal packing and robust organic cation layers. Furthermore, the influence of nanowire thickness on the charge collection efficiency is systematically elucidated through optical penetration depth analysis, highlighting design principles for optimizing low-dimensional perovskite photodetectors. This study introduces single 2D perovskite nanowires as a versatile platform for miniaturized, high-performance optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evolutionary inverse design of defects at graphene 2D lateral interfaces

Grain boundaries (GBs) in two-dimensional (2D) materials often have a profound impact on various material properties from mechanical to optical to electronic, yet predicting all possible GB formations is a challenge. Here, we introduce a workflow based on an evolutionary algorithm for exploring possible GBs formed at a lateral 2D interface. In a departure from conventional genetic algorithm based structure optimization methods, we perform genetic operations in the near interface region that allow us to be computationally efficient. We benchmark our method using graphene, which is a well-studied 2D material with a wide range of point defects. An empirical potential was used as the surrogate of the evolutionary search. More than 11.5 × 106 structures in total were evaluated for 128 GB orientations, and for each orientation, the ten best structures are recorded. A subset of low energy GBs predicted by empirical potential based search was relaxed by first-principles calculations and used to validate the energetic rank order. With the validated formation energy, we rank-ordered the best 128 GB structures and performed a detailed statistical analysis of primitive rings to find the correlation between the ring distribution and the formation energy. We found that for low energy GBs (below 0.5eV/Å), Stone–Wales defects will dominate, while structures with a higher energy (0.5–1.1eV/Å) show an increasing population of heptagons and nine-membered rings to form seven-nine defect pairs. For structures with energy higher than 1.1eV/Å, the percentage of octagons and nine-membered rings increases, which indicates that these two types of rings are not energetically favorable. Our proposed methodology is broadly applicable to explore defective low dimensional materials and represents a powerful tool that enables a systematic search of GBs of lateral interfaces for 2D materials.

Zhang, Jianan↗
DOE OSTI2023

Structure and Magnetic Properties of Pseudo-1D Chromium Thiolate Coordination Polymers

The synthesis, structure, and magnetic properties of two novel, pseudo-one-dimensional (1D) chromium thiolate coordination polymers (CPs), CrBTT and Cr2BDT3, are reported. The structures of these materials were determined using X-ray powder diffraction revealing highly symmetric 1D chains embedded within a CP framework. The magnetic coupling of this chain system was measured by SQUID magnetometry, revealing a switch from antiferromagnetic to ferromagnetic behavior dictated by the angular geometrical constraints within the CP scaffold consistent with the Goodenough–Kanamori–Anderson rules. Intrachain magnetic coupling constants J NN of –32.0 and +5.7 K were found for CrBTT and Cr 2 BDT 3 , respectively, using the 1D Bonner–Fisher model of magnetism. The band structure of these materials has also been examined by optical spectroscopy and density functional theory calculations revealing semiconducting behavior. Furthermore, our findings here demonstrate how CP scaffolds can support idealized low-dimensional structural motifs and dictate magnetic interactions through tuning of geometry and inter-spin couplings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Is 3D/2D Passivation a Secret to Success for Polycrystalline Thin-Film Solar Cells?

Three leading thin-film photovoltaic (PV) technologies - cadmium telluride (CdTe), CuIn1-xGaxSe2 (CIGS), and perovskite solar cells (PSCs) - are all polycrystalline, but otherwise appear to have little in common. A comprehensive examination of these technologies, however, reveals a common theme: the formation of two-dimensional (2D) van der Waals materials at three-dimensional (3D) absorber interfaces and grain boundaries. In CdTe, the 2D compound is CdCl2; in CIGS, it is XInSe2 (X= K, Rb, Cs) with X depending on the heavy-alkali post-deposition treatment used; and in lead halide PSCs, PbI2 forms naturally, but many new, more stable, 2D perovskites have also been incorporated. Generally, these 2D interfacial materials are present not by design, but instead have evolved from their 3D counterparts during standard device processing. Here, new data, together with evidence compiled from the literature, are presented to illustrate both the existence of 3D/2D interfaces in CdTe, CIGS, and PSCs, and their correlation with improved passivation and device performance. This suggests that 3D/2D passivation may be a heretofore unappreciated key to successful polycrystalline thin-film PV. Finally, the desired attributes of successful low-dimensional layers are presented with rational design strategies for next generation polycrystalline solar cells.

3D/2D↗
DOE OSTI2022

Controlling magnetic exchange and anisotropy by nonmagnetic ligand substitution in layered 𝑀⁢P⁢𝑋 3 (𝑀 = Ni, Mn; 𝑋 = S, Se)

Recent discoveries in two-dimensional magnetism have intensified the investigation of van der Waals magnetic materials and further improved our ability to tune their magnetic properties. Tunable magnetism has been widely studied in antiferromagnetic metal thiophosphates 𝑀⁢P⁢𝑋 3 . Substitution of metal ions 𝑀 has been adopted as an important technique to engineer the magnetism in 𝑀⁢P⁢𝑋 3 . In this work, we have studied the previously unexplored chalcogen 𝑋 substitutions in 𝑀⁢P⁢𝑋 3 (𝑀 = Mn/Ni; 𝑋 = S/Se). We synthesized the single crystals of MnP⁢S 3−𝑥 ⁢Se 𝑥 (0 ≤ 𝑥 ≤ 3) and NiP⁢S 3−𝑥 ⁢Se 𝑥 (0 ≤ 𝑥 ≤ 1.3) and investigated the systematic evolution of the magnetism with varying 𝑥. Our study reveals the effective tuning of magnetic interactions and anisotropies in both MnPS 3 and NiPS 3 upon Se substitution. Such efficient engineering of the magnetism provides a suitable platform to understand the low-dimensional magnetism and develop future magnetic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Posterior comparison of model dynamics in several hybrid turbulence model forms

Hybrid turbulence models that can accurately reproduce unsteady three-dimensional flow physics across the entire range of grid scales and turbulence dynamics from Reynolds-averaged Navier–Stokes (RANS), through large-eddy simulation (LES), down to direct numerical simulations (DNS) are of increasing interest to the turbulence modeling community. However, despite decades of research and development, the basic tasks of eliminating poor-performing hybrid RANS-LES models and accelerating adoption of superior models through well-designed validation and verification have yet to occur. As a step in this direction, in this work we evaluate thirteen different hybrid RANS-LES models via systematic grid refinement of decaying homogeneous isotropic turbulence. We further derive a novel mathematical framework for assessing the energy partitioning dynamics of each Hybrid RANS-LES model, wherein model-to-model variations in energy partitioning can be interpreted as different feedback mechanisms operating on a low-dimensional nonlinear dynamical system. We found that model forms similar to the flow simulation methodology—also often termed very-large eddy simulation—are dynamically inconsistent with DNS at all resolutions. Additionally, we found a strong dynamical similarity in the feedback mechanisms of all models related to detached eddy simulation and partially averaged Navier–Stokes that is inherent to their general model forms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Emergence of Topologically Nontrivial Spin-Polarized States in a Segmented Linear Chain

The synthesis of new materials with novel or useful properties is one of the most important drivers in the fields of condensed matter physics and materials science. Discoveries of this kind are especially significant when they point to promising future basic research and applications. Van der Waals bonded materials comprised of lower-dimensional building blocks have been shown to exhibit emergent properties when isolated in an atomically thin form. Here, we report the discovery of a transition metal chalcogenide in a heretofore unknown segmented linear chain form, where basic building blocks each consisting of two hafnium atoms and nine tellurium atoms (Hf 2 Te 9 ) are van der Waals bonded end-to-end. First-principle calculations based on density functional theory reveal striking crystal-symmetry-related features in the electronic structure of the segmented chain, including giant spin splitting and nontrivial topological phases of selected energy band states. In this work, atomic-resolution scanning transmission electron microscopy reveals single segmented Hf 2 Te 9 chains isolated within the hollow cores of carbon nanotubes, with a structure consistent with theoretical predictions. Van der Waals-bonded segmented linear chain transition metal chalcogenide materials could open up new opportunities in low-dimensional, gate-tunable, magnetic and topological crystalline systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Interplay of structure and magnetism in LuFe 4 ⁢Ge 2 tuned by hydrostatic pressure

Lu⁢Fe 4 ⁢Ge 2 crystallizes in the Zr⁢Fe 4 ⁢Si 2 -type structure, hosting chains of Fe tetrahedra giving rise to geometric frustration and low dimensionality. The compound orders antiferromagnetically at around 36 K accompanied by a simultaneous structural transition from a tetragonal phase to an orthorhombic phase. The hydrostatic pressure dependence of the magnetic and structural transitions is investigated using electrical transport, AC magnetic susceptibility, AC calorimetry, M⁢össbauer, muon-spin relaxation (μ⁢SR), and x-ray-diffraction measurements. External pressure suppresses the first-order transition to the antiferromagnetic phase (AFM1) around 1.8 GPa. The structural transition is largely unaffected by pressure and remains between 30 to 35 K for pressures up to 2 GPa. A second antiferromagnetic phase (AFM2) is observed at higher pressures. The transition from the paramagnetic to the AFM2 phase is of second-order nature and appears to be connected to the structural transition. The magnetic volume fraction obtained from μ⁢SR and M⁢össbauer measurements reveal that the entire sample undergoes magnetic ordering in both magnetic phases. In addition, similar low-temperature muon-precession frequencies in AFM1 and AFM2 phases point at similar ordered moments and magnetic structures in both phases. Our results further indicate enhanced magnetic fluctuations in the pressure-induced AFM2 phase. The experimental observations together with density functional theory calculations suggest that the magnetic- and structural-order parameters in Lu⁢Fe 4 ⁢Ge 2 are linked by magnetic frustration, causing the simultaneous magnetostructural transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Static and dynamic properties of the frustrated spin-$\frac{1}{2}$ depleted-kagome antiferromagnet Cu 7 (TeO 3 ) 2 (SO 4 ) 2 (OH) 6

The structural and magnetic properties of the two-dimensional spin-$\frac{1}{2}$ depleted-kagome compound Cu 7 (TeO 3 ) 2 (SO 4 ) 2 (OH) 6 are investigated using x-ray diffraction, magnetization, heat capacity, and 1 H Nuclear Magnetic Resonance (NMR) measurements. From the analysis of magnetic susceptibility, we found a large Curie-Weiss temperature [𝜃 CW = −50⁢(2)⁢K] and the coexistence of antiferromagnetic and ferromagnetic interactions. The value of 𝜃 CW gives an estimate of the average nearest-neighbor antiferromagnetic interaction of 𝐽/𝑘 B ≃ 66K. The NMR relaxation rates (1/𝑇 1 and 1/𝑇 2 ) exhibit a peak, providing evidence for a magnetic long-range order at 𝑇* ≃ 4K which appears to be canted antiferromagnetic type. Heat capacity also features a broad maximum at 𝑇* that moves towards higher temperatures with increasing magnetic field, reflecting defect induced Schottky anomaly. The frustration parameter 𝑓 𝑟 = |𝜃 CW |/𝑇* ≃ 12.5 renders the compound a highly frustrated low-dimensional magnet.

Akshay, K. U. [Indian Institute of Science Educati↗
DOE OSTI2025

Renormalization of states and quasiparticles in many-body downfolding

We explore the principles of many-body Hamiltonian complexity reduction via downfolding on an effective low-dimensional representation. We show that the renormalization factor provides a unique measure of the quality of the compression as it directly represents the projection between the approximate stationary state of the many-body Hamiltonian and the full many-body wavefunction. Hence, the renormalization factor is a measure of fidelity between the effective (reduced-rank) description and the full many-body treatment for arbitrary (i.e., ground and excited) states. When the entire problem is mapped on a system of interacting quasiparticles [Romanova et al., npj Comput. Mater. 9, 126 (2023)], the effective Hamiltonians can faithfully reproduce the physics only when a clear energy scale separation exists between the subsystems and their environment. We also demonstrate that it is necessary to include quasiparticle renormalization at distinct energy scales, capturing the distinct interaction between subsystems and their surrounding environments. Numerical results from simple, exactly solvable models highlight the limitations and strengths of this approach, particularly for ground and low-lying excited states. This work lays the groundwork for applying dynamical downfolding techniques to problems concerned with (quantum) interfaces.

Green-functions technique↗
DOE OSTI2025

Orbital-Selective Instabilities and Spin Fluctuations at the Verge of Superconductivity in Interlayer-Expanded Iron Selenide

Understanding electron correlation-driven instabilities and their coupling to structural phases is essential for deciphering multiorbital pairing in unconventional superconductors. We investigate Li x (C 5 H 5 N) y Fe 2 Se 2 (x ∼ 0.6; y ∼ 0.7−0.9), a tetragonal β-FeSe intercalate with a superconducting transition temperature (T c = 39 K) closely tied to an expanded Fe-layer spacing (∼11.4 Å). High-resolution synchrotron Xray diffraction and core-level absorption spectroscopy reveal subtle lattice distortions on cooling without a symmetry-breaking transition. Instead, the material exhibits negative thermal expansion (NTE) in the two-dimensional Fe network below T S ∼ 70 K, and stiffening of local Se−Fe−Se bond dynamics near T c . The spatially incoherent rearrangement of FeSe 4 tetrahedra and the site-local fluctuations, signal reduced electron correlations compared to those of parent β-FeSe (T c = 8 K). Complementary X-ray emission spectroscopy, a fast local probe of Fe 3d valence states, detects persistent local Fe spin moments below T S , unlike quenching in related systems. These findings indicate that decoupling of Fe planes leads to an electronically driven lattice instability. The latter emerges as NTE induced from weak, orbital-selective localization of in-plane Fe 3d states rather than conventional transverse vibrations. Governed by Hund’s coupling, this selectivity permits coexistence of local spin fluctuations with itinerant d-electrons critical for enhancing T c . These results suggest that intercalation-driven d-orbital differentiation moderates electron correlations, providing a pathway to optimize the superconductivity in low-dimensional quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Suppressing phase disproportionation in quasi-2D perovskite light-emitting diodes

Electroluminescence efficiencies and stabilities of quasi-two-dimensional halide perovskites are restricted by the formation of multiple-quantum-well structures with broad and uncontrollable phase distributions. Here, we report a ligand design strategy to substantially suppress diffusion-limited phase disproportionation, thereby enabling better phase control. We demonstrate that extending the π-conjugation length and increasing the cross-sectional area of the ligand enables perovskite thin films with dramatically suppressed ion transport, narrowed phase distributions, reduced defect densities, and enhanced radiative recombination efficiencies. Consequently, we achieved efficient and stable deep-red light-emitting diodes with a peak external quantum efficiency of 26.3% (average 22.9% among 70 devices and cross-checked) and a half-life of ~220 and 2.8 h under a constant current density of 0.1 and 12 mA/cm 2 , respectively. Our devices also exhibit wide wavelength tunability and improved spectral and phase stability compared with existing perovskite light-emitting diodes. These discoveries provide critical insights into the molecular design and crystallization kinetics of low-dimensional perovskite semiconductors for light-emitting devices.

14 SOLAR ENERGY↗
DOE OSTI2020

Plasmon coupling in topological insulator multilayers

Topological insulators (TIs) house two-dimensional Dirac plasmons on their surfaces. In TI thin films, plasmons on the top and bottom surfaces couple electrostatically, giving rise to an acoustic and an optical plasmon mode. By extension, a superlattice comprising TI layers and trivially-insulating layers could house multiple complex plasmon modes which could be used to create a new type of Dirac metamaterial. In this paper, we synthesize TI superlattices, fabricate them into stripe arrays, characterize their optical and plasmonic properties, and model the samples using transfer matrices. Furthermore, we excite plasmon modes that couple to the phonons in the superlattice, resulting in hybrid plasmon phonon polaritons. These modes are modeled using an analytical Fano resonance model and the extracted resonant positions are reproduced by transfer matrix modeling. We also excite an epsilon-near-zero mode in the top dielectric material (Bi 0.5 In 0.5 ) 2 Se 3 . Understanding the behavior of the polariton modes in this complex system will lend insight into the many-body interaction in low-dimensional systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Half-ice, half-fire-driven ultranarrow phase crossover in one-dimensional decorated 𝑞-state Potts ferrimagnets: An AI-co-led exploration

OpenAI’s reasoning model o3-mini-high was used to carry out an exact analytic study of one-dimensional ferrimagnetic site- and bond-decorated 𝑞-state Potts models. We demonstrate that the finite-temperature ultranarrow phase crossover (UNPC), driven by a hidden “half-ice, half-fire” state recently discovered in the 𝑞=2 case (Ising model), persists for 𝑞>2. Moreover, we identify unique features for 𝑞>2, including the dome structure in the field-temperature phase diagram, and for large 𝑞 a secondary high-temperature UNPC to the fully disordered paramagnetic state. As the UNPC quickly approaches a genuine transition by enhancing 𝐽, the interaction between the backbone spins, two distinct behaviors emerge: In the site-decorated Potts model, 𝑇 0 is independent of 𝐽 and thus remains unchanged (Type-I UNPC), and in the bond-decorated Potts model with 𝑞>2, 𝑇 0 depends on 𝐽 and quickly shifts toward a finite temperature as 𝐽 increases (Type-II UNPC). These results establish a versatile framework for engineering controlled fast state-flipping switches in low-dimensional systems. Our nine-dan artificial intelligence (AI)-contribution framework assigns AI the meritorious status of AI-co-led discovery in this work.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗