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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Raman enhancement induced by exciton hybridization in molecules and 2D materials

Abstract Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for trace-level fingerprinting. Recently, layered two-dimensional (2D) materials have gained significant interest as SERS substrates for providing stable, uniform, and reproducible Raman enhancement with the potential for trace-level detection. Yet, the development of effective 2D SERS substrates is still hindered by the lack of fundamental understanding of the coupling mechanism between target molecules and substrates. Here, we report a systematic excitation-dependent Raman spectroscopy investigation on the coupling between 2D materials such as SnS 2 , MoS 2 , WSe 2 , and graphene and small organic molecules like rhodamine 6G (Rh 6G). Strong coupling between SnS 2 and Rh 6G is found due to their degenerate excitons through Raman excitation profiles (REP), leading to the enhancement of Rh 6G vibrational modes that are observable down to 10 −13 M. Our study shows that exciton coupling in the substrate-adsorbate complex plays a vital role in the Raman enhancement effect, opening a new route for designing SERS substrates for high sensitivity.

Materials Science↗
DOE OSTI2024

Structural and physical properties of two distinct 2D lead halides with intercalated Cu( II )

Transition metal cation intercalation between the layers of two-dimensional (2D) metal halides is an underexplored research area. In this work we focus on the synthesis and physical property characterizations of two layered hybrid lead halides: a new compound [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 and the previously reported [Cu(O 2 C–(CH 2 ) 3 –NH 3 ) 2 ]PbBr 4 . These compounds exhibit 2D layered crystal structures with incorporated Cu 2+ between the metal halide layers, which is achieved by combining Cu(II) and lead bromide with suitable amino acid precursors. The resultant [Cu(O 2 C–(CH 2 ) 3 –NH 3 ) 2 ]PbBr 4 adopts a 2D layered perovskite structure, whereas the new compound [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 crystallizes with a new structure type based on edge-sharing dodecahedral PbBr5O3 building blocks. [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 is a semiconductor with a bandgap of 3.25 eV. It shows anisotropic charge transport properties with a semiconductor resistivity of 1.44 × 10 10 Ω cm (measured along the a-axis) and 2.17 × 10 10 Ω cm (along the bc-plane), respectively. The fabricated prototype detector based on this material showed response to soft low-energy X-rays at 8 keV with a detector sensitivity of 1462.7 μCGy –1 cm –2 , indicating its potential application for ionizing radiation detection. Finally, these encouraging results are discussed together with the results from density functional theory calculations, optical, magnetic, and thermal property characterization experiments.

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

Federated learning for 2D synchrotron x-ray diffractometry: a cross-institutional approach for phase quantification of Ti–6Al–4V alloy

High-energy Two dimensional (2D) synchrotron x-ray diffractometry provides important insights into the atomistic structure and phase evolution of materials, yet traditional analysis methods remain complex, knowledge-intensive, and computationally demanding. Deep-learning models offer a powerful alternative for automating their analysis. Institutions that hold these datasets may be unwilling to share their data due to privacy and security policies, as well as the challenges associated with large-scale data transfer. As a result, models trained on local datasets often perform well only on their own data but exhibit bias and poor generalization across different instruments or facilities. To overcome these limitations, we explore federated learning (FL) for 2D synchrotron diffractograms, enabling collaborative model training without exchanging raw data. In this study, 2D synchrotron diffractograms of Ti–6Al–4V alloy collected from two independent facilities are used to train convolutional neural networks for predicting the β-phase volume fraction. Experimental results show that federated global models significantly outperform locally trained models in terms of generalization and achieve accuracy comparable to centralized trained models. These findings demonstrate the potential of FL to enable secure, cross-institutional collaboration and enhance the scalability of deep-learning-based materials characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Engineering 2D Square Lattice Hubbard Models in 90° Twisted GeX/SnX (X =S, Se) Moiré Superlattices

Because of the large-period superlattices emerging in moiré two-dimensional (2D) materials, electronic states in such systems exhibit low energy flat bands that can be used to simulate strongly correlated physics in a highly tunable setup. While many investigations have thus far focused on moiré flat bands and emergent correlated electron physics in triangular, honeycomb, and quasi-one-dimensional lattices, tunable moiré realizations of square lattices subject to strong correlations remain elusive. Here, in this work, we propose a feasible scheme to construct moiré square lattice systems by twisting two or more layers of 2D materials in a rectangular lattice by 90°. We demonstrate the concept with twisted GeX/SnX (X =S, Se) moiré superlattices and calculate their electronic structures from first principles. We show that the lowest conduction flat band in these systems can be described by a square lattice Hubbard model with parameters which can be controlled by varying the choice of host materials, number of layers, and external electric fields. In particular, twisted double bilayer GeSe realizes a square lattice Hubbard model with strong frustration due to the next-nearest-neighbor hopping that could host unconventional superconductivity, in close analogy to the Hubbard model for copper-oxygen planes of cuprate high-temperature superconductors. The presented scheme uses 90° twisted 2D materials with rectangular unit cells as a promising platform for realizing the physical phenomena of square lattice Hubbard models, establishing a new route for studying its rich phase diagram of magnetism, charge order, and unconventional superconductivity in a highly tunable setting.

2-dimensional systems↗
DOE OSTI2025

Sequential multidimensional heteroepitaxy of chalcogen-sharing 3D ZnSe and 2D MoSe 2 with quasi van der Waals interface engineering

Two-dimensional (2D) materials are emerging as a promising platform for epitaxial growth, largely free from the constraints of lattice constant and thermal expansion coefficient mismatches. Among them, transition metal dichalcogenides (TMDs), known for their superior electrical properties, are ideal for ultrathin semiconductor applications. Their unique epitaxial characteristics enable seamless integration with 3D materials, facilitating the development of gate stacks and heterojunction devices. In this regard, developing a process for growing high-quality 3D epitaxial materials before and after the growth of 2D TMDs and understanding the 2D/3D interface are crucial. This study demonstrates the sequential growth of fully epitaxial ZnSe/MoSe 2 /ZnSe heterostructures using metal-organic chemical vapor deposition. ZnSe and MoSe 2 , sharing chalcogen elements, enable large-area quasi van der Waals epitaxy with sharp interfaces without intermediate phase. Multiscale analysis involving transmission electron microscopy and density functional theory calculation reveals lattice commensurability, van der Waals gaps, termination, and interfacial reconstruction. Understanding these interactions is crucial for advancing multidimensional integration of 2D and 3D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

2D Polyhedral Template Matching for Atomic Resolution Microscopy

SAND2024-13879O The 2D Polyhedral Template Matching for Atomic Resolution Microscopy is a suite of functions for analyzing atomic resolution electron microscopy images using the 2D polyhedral template matching (2D-PTM) method. This software analyzes atomic resolution microscopy data from electron microscopic imaging or scanning probe microscopies. The primary application is for identifying different crystal phases, crystal orientations, and defect structures obtained in such atomic resolution images. Written in MATLAB and starting from an atomic resolution image, the code identifies the positions of atomic intensity peaks. It then matches predefined structural templates to the local atomic environments. Outputs include the local structural identification, the template scaling factor and rotation angle, root-mean-squared deviation (RMSD), and centrosymmetry parameter.

Medlin, Douglas↗
DOE OSTI2025

2D reactive transport model of shale chemical weathering and biogeochemical fluxes along a mountainous hillslope, East River Watershed, Colorado: Input files and simulation results

This data package contains input files and simulation results for a two-dimensional (2D) reactive transport model used to quantitatively analyze the coupled hydrological and biogeochemical processes governing shale weathering and associated biogeochemical fluxes under realistic environmental conditions in the high-elevation East River Watershed. These data support the conclusions presented in Stolze et al. (Water Resources Research, under review), "Model-based interpretation of solute exports and carbon partitioning during shale weathering in a mountainous hillslope". The model simulates atmospheric-subsurface gas exchange, subsurface water flow, and shale weathering processes under dynamic, year-scale conditions along a shale-underlain hillslope located in the East River watershed. The simulations were performed using the PFLOTRAN flow and reactive transport code and executed on the Perlmutter supercomputer to leverage its large-scale parallel computing capabilities. The data package contains two zipped folders, "model_input_files" and "simulation_results", and one readme.txt file. "model_input_files" contains the necessary input files to run the calibrated base-base model presented in Stolze et al. (Water Resources Research, under review). "simulation_results" contains a single hdf5 file ("Output_2D_hillslope_model.h5") which includes the results of simulation performed using the base-case model. This file can be opened with HDFView 3.1.4, Python, or MATLAB. "readme.txt" contains relevant information about the base-case model and provides guidelines on how to run the associated input files provided in the folder "model_input_files". Furthermore, readme.txt provides information regarding the model results provided in "Output_2D_hillslope_model.h5" such as matrix dimensionality and output units. Field datasets used to evaluate model performance were collected at three monitoring wells located along a hillslope transect (PLM1, PLM2, and PLM3). Dissolved ion concentration data were collected from November 2016 to October 2021 for Ca, Mg, DIC, Na, K, SO4 (Dong et al., 2025 - dic_npoc_data_2014_2024.zip - DOI:10.15485/1660459; Williams et al., 2025 - anion_data_2014_2024.zip - DOI:10.15485/1668054; Dong et al., 2025 - cation_data_2014_2024.zip - DOI:10.15485/1668055). Note that we used the files named er_PLM1_xx_yy, er_PLM2_xx_yy, and er_PLM3_xx_yy where xx stands for the name of the aqueous species and yy stands for the depth where the measurements were performed. Soil water content ([0 - 1] m) and water table depth were collected from November 2016 to October 2021 (Wan et al., 2024 - Dynamic_water_table__depthsFig2b.csv and Soil_water_content_Fig4e.csv - DOI:10.15485/2322567). Gaseous CO2 concentration were collected from October 2020 to December 2021(Wan et al., 2024 - Soil_CO2_concentrations_Fig4h.csv - DOI:10.15485/2322567) Gaseous CO2 flux from the subsurface to the atmosphere were collected in the vicinity of PLM2 from October 2019 to May 2022 (Wu et al., 2025). Soil microbial biomass concentration was measured from August 2016 to June 2017 (Sorensen et al., 2019 - 2017_East_River_Pumphouse_Microbial_Biomass__1_.csv - DOI:10.15485/1577267) All field data are published as CSV files compatible with Microsoft Excel, MATLAB, and Python, or as text files. The coordinates of the monitoring wells and the CO2(g) flux sensor in the coordinate system WGS84 are: -PLM1: [38.9197710 ; -106.9492750] -PLM2: [38.9201580 ; -106.9487170] -PLM3: [38.9207843 ; -106.9483668] -PLM4: 38.9210060 ; -106.9479528] -CO2(g) flux sensor: [38.9199180 ; -106.9489906] ------------------------------------------------------------------------------------------- This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy User Facility using NERSC award BER-ERCAP 23980, BER-ERCAP 28550, and BER-ERCAP 33789.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗
DOE OSTI2025

Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient quantum well IR photodetectors

Metal halide perovskite (MHP) multiple quantum wells which consist of multilayers of alternate organic and inorganic layers exhibit large exciton binding energies due to the dielectric confinement between the inorganic and organic layers. These naturally formed multiple quantum wells have strong spin-orbit coupling (SOC) due to the presence of heavy elements in their crystal structures. Although the fundamental properties of 2D MHPs are far from being entirely understood, it is widely accepted that their band edge absorption coefficient results from strong exciton interactions. However, studies demonstrating how different exciton interactions and doping effects influence electronic traps and disorder on the band edge absorption coefficient of 2D MHPs have not been demonstrated. Understanding these interactions in MHPs will allow us to access low energy optical transitions for the fabrication of solution processable short-to-mid-wavelength IR photodetectors (1 – 8 μm). Moreover, upon doping, it is possible to move the Fermi energy into the conduction band (CB) to favorably promote the transport of charges in a working device. Herein, we study the development of 2D MHPs having strong SOC, high carrier mobility, and tunable quantum well structures. Our studies shed light on the design and modulation of fundamental physical phenomena by carefully elucidating the role of dopants (n-type and p-type), exciton heterogeneity, orientation, structure, and bias stress effects on the performance of MHPs as potential IR photodetectors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Epitaxial 2D Magnet and Topological Insulator Heterostructures

I will discuss our latest advances on the epitaxial growth of 2D van der Waals (vdW) magnets and their integration with topological insulators (TI). This work is motivated by the realization of topological phases such as the quantum anomalous Hall effect and highly efficient spin-orbit torque produced by TIs. Our initial studies of MnSe2 growth on Bi2Se3 showed a tendency for the interdiffusion of Mn into the Bi2Se3. This ultimately led to the synthesis of MnBi2Se4 (MBS), a new magnetic TI. Interestingly, the vdW phase is not the thermodynamically stable phase and bulk crystals do not exist, so the epitaxial stabilization of MBS creates the opportunity to explore the magnetic and topological properties of this material. We find that MBS is a layered antiferromagnet, similar to MnBi2Te4, but a difference is that the magnetic moments lie in the plane of the film. Angle resolved photoemission experiments show the presence of a topological surface state with Dirac dispersion. For bilayers of 2D magnets and TIs, we have developed FGT films on Bi2Te3. We first optimized FGT by studying its growth on Ge(111) substrates, where we find that kinetic considerations play a major role. Using cross-sectional scanning transmission electron microscopy and scanning tunneling microscopy, we optimize the FGT films to have atomically smooth surfaces and abrupt interfaces with the Ge(111). Subsequently, we have developed the growth of FGT on Bi2Te3 for the integration of 2D magnets with Tis. Interestingly, we observe room temperature ferromagnetism in FGT/Bi2Te3 heterostructures by varying the growth conditions.

Kawakami, Roland↗
DOE OSTI2025

N‐Heterocyclic Carbene Functionalization of 2D Transition Metal Dichalcogenides via a Frustrated Lewis Pair Strategy

Molecular functionalization of 2D transition metal dichalcogenides (TMDs), which unites tailorability of organic molecules and robustness of inorganic solids, is important for tuning their surface properties. While it is common to leverage the electronic effect of organic ligands to functionalize TMDs, the corresponding steric hinderance has remained elusive and underexplored. Herein N‐heterocyclic carbene (NHC) functionalization of WS 2 is demonstrated via a frustrated Lewis pair (FLP) route, which exploits both the electronic and steric effect for TMD functionalization. The Lewis base, 1,3‐bis(2,4,6‐trimethylphenyl)imidazol‐2‐ylidene (IMes), is anchored to the sulfur vacancy sites (Lewis acid) of the WS 2 nanostructures with the hybrid‐interface‐mediated steric hinderance, mimicking the FLP chemistry and enabling dihydrogen cleavage at room temperature and atmospheric pressure. Solid‐state nuclear magnetic resonance (ssNMR) results reveal the local chemical environment of the activated hydrogen species, which can be transferred for room‐temperature hydrogenation reactions. Finally, the insights are useful for designing weak, non‐covalent bonds to modify the 2D surface of TMDs for a broad scope of applications.

2D materials↗
DOE OSTI2025

Boosting Hydrogenation of CO 2 Using Cationic Cu Atomically Dispersed on 2D γ‐Al 2 O 3 Nanosheets

The continuous development of novel catalytic approaches is crucial for advancing efficient CO 2 hydrogenation processes. Drawing inspiration from single-atom catalysis and 2D materials, we designed a new 2D single-atom catalyst with excellent thermal stability by thermally treating Cu-adsorbed γ-AlOOH nanosheets, which yielded a Cu/γ-Al 2 O 3 catalyst with high activity in the hydrogenation of CO 2 -yielding methanol (CH 3 OH), dimethyl ether (DME), and CO as products. The active Cu sites are monodispersed and highly stable due to their cationic oxidation state and their substitution for pentacoordinated aluminum (Al P ) sites on particle surfaces. This study demonstrates an efficient approach for achieving a high CO 2 hydrogenation rate (30.45 mol mol −1 h −1 ) using a catalyst system that lacks metallic Cu centers, traditionally considered essential for H₂ dissociation, and employs what was previously thought to be an inert metal oxide (γ-Al 2 O 3 ) for CO and CH 3 OH production. Ongoing mechanistic studies aim to elucidate the synergy between cationic Cu single atoms and γ-Al 2 O 3 , a Lewis acid support, in facilitating hydrogen (H 2 ) activation and methanol formation.

2D catalyst↗
DOE OSTI2025

Self‐Lubricating Tribo‐Catalytic Activity of 2D High Entropy Alloy Nanoflakes

High Entropy Alloys (HEAs) have garnered attention due to their remarkable tribological attributes. Predominantly, failure mechanisms in HEAs emanate from stress‐induced dislocations, culminating in crack propagation and film delamination. In this study, we report on the synthesis of 2D HEA of (MoWNbTaV) 0.2 S 2 which facilitates shear‐induced energy dissipation at sliding interfaces. The ball‐on‐disk tribological investigations demonstrate unprecedentedly low average coefficients of friction (0.076) and wear rates (10 −9 mm 3 (N∙m) −1 ) under high contact pressures (0.936 GPa) within ambient conditions. Employing multi‐scale characterizations alongside molecular dynamic simulations, we elucidate that the presence of the HEA triggers tribocatalytic activity under high contact pressures emerging as a pivotal factor in extending lubricant lifespan during tribological tests. The resilient lubriciousness coupled with the facile spray coating methodology of (MoWNbTaV) 0.2 S 2 in ambient environments paves the way for the development of a new class of solid lubricants based on 2D HEA.

2D solid lubricant↗
DOE OSTI2025

Understanding the Effects of Inhomogeneities at the Back Interface of CdTe‐Based Solar Cells Using 2D Modeling

One-dimensional modeling cannot capture lateral inhomogeneities in CdTe-based devices. Here, we use 2D modeling to investigate the role of varying energetics at the back interface. We consider improvements in the back interface layer (BIL) through either reducing back surface recombination velocity (BSRV) or decreasing the downward band bending near the back interface. We show that when the BSRV is reduced, but strong downward band bending remains, there is no change in the device performance until the BSRV of 90% of the back interface is improved by the BIL. On the other hand, any coverage with a BIL that improves band bending results in device improvements. We use band bending, back interface recombination current densities, and voltage dependent current flow through the device to understand these improvements. The modeling shows that lateral flow of carriers greatly affects device performance, which is not captured in parallel diode modeling, and demonstrates improved understanding with 2D modeling.

2D modelling↗
DOE OSTI2024

Modulation of Electrostatic Potential in 2D Crystal Engineered by an Array of Alternating Polar Molecules

The moiré potential in rotationally misfit two-dimensional (2D) heterostructures has been used to build artificial exciton and electron lattices, which have become platforms for realizing exotic electronic phases. Here, we demonstrate a different approach to create a superlattice potential in 2D crystals by using the near field of an array of polar molecules. Here, a bilayer of titanyl phthalocyanine (TiOPc), consisting of alternating out-of-plane dipoles, is deposited on monolayer MoS 2 . Time-resolved two-photon photoemission spectroscopy reveals a pair of interlayer exciton states with an energy difference of ~0.1 eV, which is consistent with the electrostatic potential modulation induced by the TiOPc bilayer as determined by density functional theory calculations. Because the symmetry and the period of this potential superlattice can be changed readily by using molecules of different shapes and sizes, molecule/2D heterostructures can be promising platforms for designing artificial exciton and electron lattices.

2D heterostructures↗
DOE OSTI2025

Humidity Disrupts Structural and Chiroptical Properties of Chiral 2D Perovskites

Chiral two-dimensional (2D) hybrid organic–inorganic metal halide perovskite semiconductors have emerged as an exceptional material platform with many design opportunities for spintronic applications. However, a comprehensive understanding of changes to the crystal structure and chiroptical properties upon exposure to atmospheric humidity has not been established. We demonstrate phase degradation to the 1D (MBA)PbI 3 (MBA = methylbenzylammonium) and the hypothetical (MBA) 3 PbI 5 ·H 2 O hydrate phases, accompanied by a reduction and disappearance of the chiroptical response. Firstprinciple simulations show that water molecules preferentially locate at the interface between the organic cations and the inorganic framework, thereby disrupting the hydrogen bonding, impacting both the structural chirality and stability of the material. These findings provide critical insights into phase degradation mechanisms and their impact on chiroptical activity in chiral 2D perovskites.

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

Air-Stable Room-Temperature Quasi-2D Tin Iodide Perovskite Microlasers

Quasi-2D tin iodide perovskites (TIPs) are promising lead-free alternatives for optoelectronic applications, but achieving stable lasing remains challenging due to their limited environmental stability. Here, we report air-stable, room-temperature lasing from quasi-2D TIP microcrystals as small as 4 μm. Incorporation of the organic spacer 5IPA3 significantly enhanced the stability of these materials compared with previously reported TIPs. Lasing was observed from both dielectric (n = 4) and plasmonic (n = 3 and n = 4) TIP microlasers. Under picosecond pumping, lasing was sustained for over 108 pump pulses in ambient conditions. These results represent a significant step toward practical photonic applications of tin-based perovskites.

crystals↗
DOE OSTI2025

Spontaneous Formation of Single-Crystalline Spherulites in a Chiral 2D Hybrid Perovskite

In two-dimensional (2D) chiral metal-halide perovskites (MHPs), chiral organic spacers induce structural chirality and chiroptical properties in the metal-halide sublattice. This structural chirality enables reversible crystalline-glass phase transitions in (S-NEA) 2 PbBr 4 , a prototypical chiral 2D MHP where NEA + represents 1-(1-naphthyl)ethylammonium. Here, in this study, we investigate two distinct spherulite states of (S-NEA) 2 PbBr 4 , exhibiting either radial-like or stripe-like banded patterns depending on the annealing conditions of the amorphous film. Despite similarities in optical absorption and photoluminescence, the stripe-like, banded spherulite exhibits higher crystallinity and improved optical transparency compared to those of radial-like spherulite. X-ray nanoprobe measurements reveal tilting-angle modulations in the octahedral plane of stripe-like spherulites, correlating with the film’s surface geometry. Transfer matrix calculations indicate that the optical contrast in stripe-like patterns, seen in bright-field optical microscopy, arises from optical interference effects, differing from the contrast mechanism observed in polymer spherulites. Ultrafast carrier dynamics experiments suggest that the stripe-like spherulites resemble single crystals more closely than radial-like spherulites, while electrical conductivity measurements show enhanced charge carrier transport in stripe-like spherulites. These findings offer insights into MHP spherulite states with a single composition but different morphologies, previously observed only in polymers, highlighting their potential for optoelectronic applications.

36 MATERIALS SCIENCE↗