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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 217 records · Page 12

Enhancing Chiroptoelectronic Activity in Chiral 2D Perovskites via Chiral–Achiral Cation Mixing

Rational design of chiral two-dimensional hybrid organic–inorganic perovskites is crucial to achieve chiroptoelecronic, spintronic, and ferroelectric applications. Here, in this study, an efficient way to manipulate the chiroptoelectronic activity of 2D lead iodide perovskites is reported by forming mixed chiral (R- or S-methylbenzylammonium (R-MBA + or S-MBA + )) and achiral (n-butylammonium (nBA + )) cations in the organic layer. The strongest and flipped circular dichroism signals are observed in (R/S-MBA 0.5 nBA 0.5 ) 2 PbI 4 films compared to (R/S-MBA) 2 PbI 4 . Moreover, the (R/S-MBA 0.5 nBA 0.5 ) 2 PbI 4 films exhibit pseudo-symmetric, unchanged circularly polarized photoluminescence peak as temperature increases. First-principles calculations reveal that mixed chiral–achiral cations enhance the asymmetric hydrogen-bonding interaction between the organic and inorganic layers, causing more structural distortion, thus, larger spin-polarized band-splitting than pure chiral cations. Temperature-dependent powder X-ray diffraction and pair distribution function structure studies show the compressed intralayer lattice with enlarged interlayer spacing and increased local ordering. Overall, this work demonstrates a new method to tune chiral and chiroptoelectronic properties and reveals their atomic scale structural origins.

2D perovskites↗

Excitonic Anisotropy in Single‐Crystalline 2D Silver Phenylchalcogenides

2D materials exhibiting in‐plane anisotropy enable new applications in directional energy transport and polarized optical response. Silver phenylchalcogenides (AgEPh) – including mithrene (AgSePh), tethrene (AgTePh), and thiorene (AgSPh) – represent an exciting new addition to this family, with optical response spanning the visible to near‐UV. Here, excitonic anisotropy is predicted and characterized in this family of materials using a combination of ab initio theory and optical micro‐spectroscopy of single‐crystalline flakes. Using density functional theory and GW with the Bethe–Salpeter equation calculations, it is revealed that all AgEPh compounds exhibit anisotropic electronic band structure and host multiple delocalized excitons with in‐plane anisotropy. Room‐temperature polarization‐resolved optical micro‐spectroscopy shows that orthogonally polarized excitons with similar energy lead to nearly isotropic absorption in AgSPh, whereas energy separation between excitonic resonances in AgSePh and AgTePh leads to strong absorption and emission anisotropy. Cryogenic reflectance micro‐spectroscopy further reveals exciton fine structure in AgSePh, reconciling the discrepancies between room‐temperature experiments and theoretical predictions. Finally, it is demonstrated that the optical response of thicker AgEPh crystals is influenced by photonic effects arising from finite crystal size. Overall, this work advances the understanding of the relationship between anisotropic structure, composition, and excitonic properties in AgEPh, providing a foundation for technological integration.

2D↗

Experimental Evidence of Free Carrier Generation in 2D Hybrid Organic–Inorganic Perovskites

Despite the significant potential of 2D hybrid organic–inorganic perovskites (2DHOIPs) for high-efficiency optoelectronics application-comparable to their 3D counterparts, the fundamental carrier photogeneration remains unclear. In contrast to conventional ultrafast optical property characterization, we use ultrafast photocurrent spectroscopy to investigate the early-time electrical properties of type-I and type-II 2DHOIPs by manipulating the quantum confinement and the dielectric quantum matching effect. We discovered that the high frequency dielectric quantum matching effect plays a major role in 2DHOIPs, demonstrated by their high carrier mobility (µ), near-unity photogeneration quantum yield (Φ), below-room temperature exciton binding energy (E b ), and approaching 3D space factor (DSF). Our work shows that the optoelectronic performances of 2DHOIPs are comparable to their counterparts of 3DHOIPs.

2D perovskite↗

Unconventional Anomalous Hall Effect Driven by Self‐Intercalation in Covalent 2D Magnet Cr 2 Te 3

Covalent 2D magnets such as Cr 2 Te 3 , which feature self-intercalated magnetic cations located between monolayers of transition-metal dichalcogenide material, offer a unique platform for controlling magnetic order and spin texture, enabling new potential applications for spintronic devices. Here, it is demonstrated that the unconventional anomalous Hall effect (AHE) in Cr 2 Te 3 , characterized by additional humps and dips near the coercive field in AHE hysteresis, originates from an intrinsic mechanism dictated by the self-intercalation. This mechanism is distinctly different from previously proposed mechanisms such as topological Hall effect, or two-channel AHE arising from spatial inhomogeneities. Crucially, multiple Weyl-like nodes emerge in the electronic band structure due to strong spin-orbit coupling, whose positions relative to the Fermi level is sensitively modulated by the canting angles of the self-intercalated Cr cations. These nodes contribute strongly to the Berry curvature and AHE conductivity. This component competes with the contribution from bands that are less affected by the self-intercalation, resulting in a sign change in AHE with temperature and the emergence of additional humps and dips. The findings provide compelling evidence for the intrinsic origin of the unconventional AHE in Cr 2 Te 3 and further establish self-intercalation as a control knob for engineering AHE in complex magnets.

2D magnets↗

Direct‐Write Printed Contacts to Layered and 2D Materials

Advancements in fabrication methods have shaped new computing device technologies. Among these methods, depositing electrical contacts to the channel material is fundamental to device characterization. Novel layered and 2D materials are promising for next-generation computing electronic channel materials. Direct-write printing of conductive inks is introduced as a surprisingly effective, significantly faster, and cleaner method to contact different classes of layered materials, including graphene (semi-metal), MoS 2 (semiconductor), Bi-2212 (superconductor), and Fe 5 GeTe 2 (metallic ferromagnet). Based on the electrical response, the quality of the printed contacts is comparable to what is achievable with resist-based lithography techniques. These devices are tested by sweeping gate voltage, temperature, and magnetic field to show that the materials remain pristine post-processing. This work demonstrates that direct-write printing is an agile method for prototyping and characterizing the electrical properties of novel layered materials.

2D materials↗

Structure and Dynamics of Imidazolium in an Ionic Liquid-PEGDA Iongel via IR, 2D-IR, and NMR Spectroscopy

Fourier transform infrared (FTIR) absorption spectroscopy, ultrafast two-dimensional infrared (2D-IR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and density functional theory (DFT) calculations show that, in iongels composed of 1-ethyl-3-methylimidazolium bis(trifluoromethyl\-sulfonyl)imide ([C 2 C 1 Im][Tf 2 N]}) and cross-linked poly(ethylene glycol)diacrylate (cl-PEGDA), imidazolium cations solvate PEGDA chains in tight and loose complexes. H/D isotope substitution at the 2-position of the imidazolium ring simplifies the CH-stretching vibrational bands. Tight complexes are characterized by stronger, directional hydrogen bonding interactions between the 2-position of the imidazolium ring and the ethereal oxygens. The loose complexes resemble bulk ionic liquid (IL) non-specifically perturbed by the PEGDA chains.

ionic liquids, carbon dioxide, cross-linked PEGDA,↗

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗

A dynamic 2D Borehole Thermal Energy Storage (BTES) model for enhanced computational efficiency

Progressing toward a future increasingly reliant on renewable energy sources, the development of effective, durable energy storage solutions becomes essential to balance supply and demand fluctuations. Borehole Thermal Energy Storage (BTES) is a long-duration thermal energy storage technology that captures excess heat generated from renewable energy sources and stores it underground for later use, enabling the efficient utilization of sustainable energy. This approach is particularly valuable in district energy networks when integrated with Ground Source Heat Pumps (GSHP) to provide stable heating and cooling. However, traditional three-dimensional (3D) numerical models of BTES systems demand extensive computational resources, limiting their practicality for real-time and large-scale applications. This study introduces a novel two-dimensional (2D) modeling approach that reduces computational costs while maintaining high accuracy. By employing a radial ring-based discretization method, the model simulates heat injection, retention, and retrieval dynamics over seasonal cycles. A new thermal-mass weighted-average temperature parameter is introduced to evaluate the performance of BTES systems. Model validation against FEFLOW simulations demonstrates a 17-fold improvement in computational speed compared to traditional Computational Fluid Dynamics (CFD) models while achieving a mean absolute percentage error (MAPE) of 2 % during charging and 4 % during discharging. Additionally, a trade-off analysis between computational efficiency and accuracy is conducted, ensuring the model's applicability for real-world scenarios. The findings of this research contribute to the development of computationally efficient BTES models, facilitating better optimization, control, and integration into renewable energy systems. This work provides a foundation for further studies in techno-economic analysis, multi-year performance evaluation, and real-time operational strategies for BTES applications, supporting a more sustainable energy future.

2D modeling↗

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗

Absorption dissymmetry factor enhancement: A data-driven approach to unravel the synthesis knobs of chiral 2D perovskites

Chiral 2D metal halide perovskites (MHPs) are promising for spin-optoelectronic applications, yet their absorption dissymmetry factor (g abs ) exhibits significant variability due to complex, co-dependent structural and experimental factors. Here, we established a data-driven framework using Pearson’s correlation, ANOVA, and Gaussian process regression to identify and model key synthesis “knobs” governing these properties. The analysis revealed that solvent choice is the primary factor driving variability. For acetonitrile-based films, g abs was maximized by optimizing annealing temperature and film thickness. Conversely, films from higher boiling point solvents showed complex dependencies on annealing temperature, excitonic integral intensity, and film texture. These statistical correlations provide a roadmap for the rational design of high-performance chiral MHPs and establish a foundation for future machine learning-driven material exploration.

ANOVA↗

Plasmons Enable Ultralow Threshold Solid-State Triplet Fusion Upconversion with a 2D Sensitizer

Solid-state triplet−triplet annihilation (TTA) upconversion has significant potential for application in light harvesting, optoelectronic devices, and bioimaging. However, the high optical powers required to achieve efficient upconversion have inhibited its adoption. In this work, we demonstrate plasmon-enhanced near-infrared (NIR)-to-blue TTA upconversion in a monolayer WSe2/organic heterojunction. Under far-field excitation, the device reaches a threshold of 19 mW/cm 2 and an external quantum efficiency (EQE) of 0.17% with an anti-Stokes shift of 1.1 eV. Plasmon excitation lowers the threshold to 0.9 mW/cm 2 and improves the EQE to 3.6%. We attribute the plasmon enhancement to surface plasmon polariton (SPP) near-field enhancement and dark-exciton absorption. Optimization of the WSe 2 transfer process is identified as a key factor for the device performance. This work demonstrates that plasmon excitation overcomes the low far-field absorption of 2D transition-metal dichalcogenide (TMD) sensitizers. Consequently, monolayer TMDs can achieve solid-state upconversion with a performance among the best reported.

2D materials↗

Strategy for Ultranarrow Light Down-Conversion for Displays Based on Bicolor-Emitting 2D Colloidal Heterostructures

The demand for ultranarrow spectral emission below 10 nm is critical for next-generation displays. Although current colloidal nanocrystals are successful in light down-conversion applications, they fall short in matching the stringent color purity requirements set by standards like Rec. 2020. Achieving such narrow linewidths through material engineering alone remains elusive, necessitating innovative light management strategies that avoid optical losses and maintain device efficiency. Here, in this work, we present a novel 2D colloidal heterostructure design, combining a CdSe core nanoplatelet, a CdS crown, and a CdZnS shell, to achieve bright bicolor emission in the solid state (green/red) emission with tunable intensity ratios controlled by excitation power (either optical or electrical). Integration of these nanoplatelets into a dielectric cavity further narrows the emission linewidth to sub-2 nm while enhancing the photoluminescence intensity by up to 200 times, meeting the Rec. 2020 color purity targets. This approach paves the way for a strategy avoiding complex laser-based solutions.

2D nanocrystals↗

Polariton spectra under the collective coupling regime. II. 2D non-linear spectra

In our previous work [Mondal et al., J. Chem. Phys. 162, 014114 (2025)], we developed several efficient computational approaches to simulate exciton–polariton dynamics described by the Holstein–Tavis–Cummings (HTC) Hamiltonian under the collective coupling regime. Here, we incorporated these strategies into the previously developed Lindblad-partially linearized density matrix (⁠$\mathscr{L}$-PLDM) approach for simulating 2D electronic spectroscopy (2DES) of exciton–polariton under the collective coupling regime. In particular, we apply the efficient quantum dynamics propagation scheme developed in Paper I to both the forward and the backward propagations in the PLDM and develop an efficient importance sampling scheme and graphics processing unit vectorization scheme that allow us to reduce the computational costs from $\mathscr{O}$($\mathscr{K}$ 2 )$\mathscr{O}$(T 3 ) to $\mathscr{O}$($\mathscr{K}$)$\mathscr{O}$(T 0 ) for the 2DES simulation, where $\mathscr{K}$ is the number of states and T is the number of time steps of propagation. As a result, we further simulated the 2DES for an HTC Hamiltonian under the collective coupling regime and analyzed the signal from both rephasing and non-rephasing contributions of the ground state bleaching, excited state emission, and stimulated emission pathways.

2D non-linear spectra↗

ASb 3 Mn 9 O 19 (A = K or Rb): New Mn-Based 2D Magnetoplumbites with Geometric and Magnetic Frustration

Magnetoplumbites are one of the most broadly studied families of hexagonal ferrites, typically with high magnetic ordering temperatures, making them excellent candidates for permanent magnets. However, magnetic frustration is rarely observed in magnetoplumbites. Herein, the discovery, synthesis, and characterization of the first Mn-based magnetoplumbite, as well as the first magnetoplumbite involving pnictogens (Sb), ASb 3 Mn 9 O 19 (A = K or Rb) are reported. The Mn 3+ ( S = 2) cations, further confirmed by DC magnetic susceptibility and X-ray photoelectron spectroscopy, construct three geometrically frustrated sublattices, including Kagome, triangular, and puckered honeycomb lattices. Magnetic properties measurements revealed strong antiferromagnetic spin–spin coupling as well as multiple low-temperature magnetic features. Heat capacity data does not show any prominent λ-anomaly, suggesting minimal associated magnetic entropy. Moreover, neutron powder diffraction (NPD) implied the absence of long-range magnetic ordering in KSb 3 Mn 9 O 19 down to 3 K. However, several magnetic peaks are observed in RbSb 3 Mn 9 O 19 at 3 K, corresponding to an incommensurate magnetic structure. Interestingly, strong diffuse scattering is seen in the NPD patterns of both compounds at low angles and is analyzed by reverse Monte Carlo refinements, indicating short-range spin ordering related to frustrated magnetism as well as 2D magnetic correlations in ASb 3 Mn 9 O 19 (A = K or Rb).

2-D magnetic correlation↗

Mechanical Resonant Sensing of Spin Texture Dynamics in a 2D Antiferromagnet

Abstract The coupling between the spin degrees of freedom and macroscopic mechanical motions, including striction, shearing, and rotation, has attracted wide interest with applications in actuation, transduction, and information processing. Experiments so far have established the mechanical responses to the long‐range ordered or isolated single spin states. However, it remains elusive whether mechanical motions can couple to a different type of magnetic structure, the non‐collinear spin textures, which exhibit nanoscale spatial variations of spin (domain walls, skyrmions,etc.) and are promising candidates to realize high‐speed computing devices. Here, collective spin texture dynamics is detected with nanoelectromechanical resonators fabricated from 2D antiferromagnetic (AFM) MnPS 3 with 10 −9 strain sensitivity. By examining radio frequency mechanical oscillations under magnetic fields, new magnetic transitions are identified with sharp dips in resonant frequency. They are attributed to collective AFM domain wall motions as supported by the analytical modeling of magnetostriction and large‐scale spin‐dynamics simulations. Additionally, an abnormally large modulation in the mechanical nonlinearity at the transition field infers a fluid‐like response due to ultrafast domain motion. The work establishes a strong coupling between spin texture and mechanical dynamics, laying the foundation for electromechanical manipulation of spin texture and developing quantum hybrid devices.

Chemistry↗

Lattice Symmetry-Guided Charge Transport in 2D Supramolecular Polymers Promotes Triplet Formation

Singlet-to-triplet intersystem crossing (ISC) in organic molecules is intimately connected with their geometries: by modifying the molecular shape, symmetry selection rules pertaining to spin-orbit coupling can be partially relieved, leading to extra matrix elements for increased ISC. As an analog to this molecular design concept, the study finds that the lattice symmetry of supramolecular polymers also defines their triplet formation efficiencies. A supramolecular polymer self-assembled from weakly interacting molecules is considered. Its 2D oblique unit cell effectively renders it as a coplanar array of 1D molecular columns weakly bound to each other. Using momentum-resolved photoluminescence imaging in combination with Monte Carlo simulations, the study found that photogenerated charge carriers in the supramolecular polymer predominantly recombine as spin-uncorrelated carrier pairs through inter-column charge transfer states. This lattice-defined recombination pathway leads to a substantial triplet formation efficiency (≈60%) in the supramolecular polymer. These findings suggest that lattice symmetry of micro-/macroscopic structures relying on intermolecular interactions can be strategized for controlled triplet formation.

36 MATERIALS SCIENCE↗

On the Ordering Mechanism of Cu + in 2D van der Waals Multiferroic CuCrP 2 S 6

CuCrP 2 S 6 is a van der Waals multiferroic where the tunable Cu + sublattice underpins its exceptional ferroelectric and electronic switching properties. Yet, the microscopic mechanism governing Cu + ordering has remained elusive. Here, we combine single-crystal X-ray and neutron diffraction with pair distribution function analysis to uncover a temperature-driven evolution of Cu + ordering, giving rise to an incommensurate quasi-antipolar phase between the paraelectric and antiferroelectric states. The modulation originates from correlated Cu + occupancy redistribution coupled to breathing distortion of surrounding S 3 triangles, establishing a symmetry-adapted lattice distortion mode. Diffuse scattering persisting over 35 K above the transition confirms that the structural instability follows an order-disorder mechanism. The spontaneous off-centering of Cu + positions CuCrP 2 S 6 as a model platform for correlated order-disorder phenomena in 2D layered ferroics, and provides design principles for next-generation memory and logic devices.

ferroelectrics↗

Pathway Selectivity in 2D Electronic‐Vibrational Spectroscopy with Quantum Light

Abstract Pathway selectivity in quantum spectroscopy with entangled photons is a powerful spectroscopic tool. Phase‐matched signals involving classical light contain contributions from multiple material pathways, whereas quantum spectroscopy may allow the selection of individual pathways. 2D electronic‐vibrational spectroscopy (2DEVS) is a four‐wave mixing technique which employs visible and infrared entangled photons. It is showed how the three contributing pathways—ground state bleach, excited state absorption, and excited state emission—can be separated by photon‐number‐resolved coincidence measurements. Entangled photons thus reveal spectral features not visible in the classical signal, with an enhanced spectral resolution.

Jadoun, Deependra [Department of Chemistry Univers↗