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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Diamine chelates for increased stability in mixed Sn–Pb and all-perovskite tandem solar cells

Perovskite tandem solar cells show promising performance but non-radiative recombination and its progressive worsening with time, especially in the mixed Sn–Pb low-bandgap layer, limit performance and stability. Here, in this study, we find that mixed Sn–Pb perovskite thin films exhibit a compositional gradient, with an excess of Sn on the surface – and we show this gradient exacerbates oxidation and increases the recombination rate. We find that diamines preferentially chelate Sn atoms, removing them from the film surface and achieving a more balanced Sn:Pb stoichiometry, making the surface of the film resistive to the oxidation of Sn. The process forms an electrically resistive low-dimensional barrier layer, passivating defects and reducing interface recombination. Further improving the homogeneity of the barrier layer using 1,2-diaminopropane results in more uniform distribution and passivation. Tandems achieve a power conversion efficiency of 28.8%. As a result, encapsulated tandems retain 90% of initial efficiency following 1000 hours of operating at the maximum power point under simulated one-sun illumination in air without cooling.

14 SOLAR ENERGY↗
DOE OSTI2021

Enhanced superconductivity and ferroelectric quantum criticality in plastically deformed strontium titanate

The properties of quantum materials are commonly tuned using experimental variables such as pressure, magnetic field and doping. Here we explore a different approach using irreversible, plastic deformation of single crystals. We show that compressive plastic deformation induces low-dimensional superconductivity well above the superconducting transition temperature (Tc) of undeformed SrTiO3, with evidence of possible superconducting correlations at temperatures two orders of magnitude above the bulk Tc. The enhanced superconductivity is correlated with the appearance of self-organized dislocation structures, as revealed by diffuse neutron and X-ray scattering. We also observe deformation-induced signatures of quantum-critical ferroelectric fluctuations and inhomogeneous ferroelectric order using Raman scattering. Our results suggest that strain surrounding the self-organized dislocation structures induces local ferroelectricity and quantum-critical dynamics that strongly influence Tc, consistent with a theory of superconductivity enhanced by soft polar fluctuations. Our results demonstrate the potential of plastic deformation and dislocation engineering for the manipulation of electronic properties of quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Unconventional excitonic states with phonon sidebands in layered silicon diphosphide

Complex correlated states emerging from many-body interactions between quasiparticles (electrons, excitons and phonons) are at the core of condensed matter physics and material science. In low-dimensional materials, quantum confinement affects the electronic, and subsequently, optical properties for these correlated states. Here, by combining photoluminescence, optical reflection measurements and ab initio theoretical calculations, we demonstrate an unconventional excitonic state and its bound phonon sideband in layered silicon diphosphide (SiP 2 ), where the bound electron–hole pair is composed of electrons confined within one-dimensional phosphorus–phosphorus chains and holes extended in two-dimensional SiP 2 layers. The excitonic state and emergent phonon sideband show linear dichroism and large energy redshifts with increasing temperature. Our ab initio many-body calculations confirm that the observed phonon sideband results from the correlated interaction between excitons and optical phonons. With these results, we propose layered SiP2 as a platform for the study of excitonic physics and many-particle effects.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elementary excitations of single-photon emitters in hexagonal boron nitride

Single-photon emitters serve as building blocks for many emerging concepts in quantum photonics. The recent identification of bright, tunable and stable emitters in hexagonal boron nitride (hBN) has opened the door to quantum platforms operating across the infrared to ultraviolet spectrum. Although it is widely acknowledged that defects are responsible for single-photon emitters in hBN, crucial details regarding their origin, electronic levels and orbital involvement remain unknown. Here we employ a combination of resonant inelastic X-ray scattering and photoluminescence spectroscopy in defective hBN, unveiling an elementary excitation at 285 meV that gives rise to a plethora of harmonics correlated with single-photon emitters. We discuss the importance of N π* anti-bonding orbitals in shaping the electronic states of the emitters. Importantly, the discovery of elementary excitations in hBN provides fundamental insights into quantum emission in low-dimensional materials, paving the way for future investigations in other platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Circuit quantum electrodynamics detection of induced two-fold anisotropic pairing in a hybrid superconductor–ferromagnet bilayer

Abstract Hybrid systems represent one of the frontiers in the study of unconventional superconductivity and are a promising platform to realize topological superconducting states. These materials are challenging to probe using many conventional measurement techniques because of their mesoscopic dimensions, and therefore require new experimental probes so that they can be successfully characterized. Here, we demonstrate a probe that enables us to measure the superfluid density of micrometre-size superconductors using microwave techniques drawn from circuit quantum electrodynamics. We apply this technique to a superconductor–ferromagnet bilayer and find that the proximity-induced superfluid density is two-fold anisotropic within the plane of the sample. It also exhibits power-law temperature scaling that is indicative of a nodal superconducting state. These experimental results are consistent with the theoretically predicted signatures of induced triplet pairing with a nodal p -wave order parameter. Moreover, we observe modifications to the microwave response at frequencies near the ferromagnetic resonance, suggesting a coupling between the spin dynamics and induced superconducting order in the ferromagnetic layer. Our experimental technique can be employed more widely, for example to study fragile unconventional superconductivity in low-dimensional materials such as van der Waals heterostructures.

Bøttcher, C. G. L. (ORCID:0000000194898461)↗
DOE OSTI2021

An adaptive approach to machine learning for compact particle accelerators

Abstract Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML models were trained. For complex systems, re-training is only possible if the changes are slow relative to the rate at which large numbers of new input-output training data can be non-invasively recorded. In this work, we present an approach to deep learning for time-varying systems that does not require re-training, but uses instead an adaptive feedback in the architecture of deep convolutional neural networks (CNN). The feedback is based only on available system output measurements and is applied in the encoded low-dimensional dense layers of the encoder-decoder CNNs. First, we develop an inverse model of a complex accelerator system to map output beam measurements to input beam distributions, while both the accelerator components and the unknown input beam distribution vary rapidly with time. We then demonstrate our method on experimental measurements of the input and output beam distributions of the HiRES ultra-fast electron diffraction (UED) beam line at Lawrence Berkeley National Laboratory, and showcase its ability for automatic tracking of the time varying photocathode quantum efficiency map. Our method can be successfully used to aid both physics and ML-based surrogate online models to provide non-invasive beam diagnostics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Magnetic-field-induced Wigner crystallization of charged interlayer excitons in van der Waals heterostructures

Abstract Ever since its inception, coherent excited states of semiconductors have been the focus of semiconductor materials research to evolve into a vibrant field of low-dimensional solid-state physics. The field is gaining new momentum these days due to emerging transdimensional semiconductors such as van der Waals bound layers of transition metal dichalcogenides (TMDs) of controlled thickness. Here, we develop the theory of magnetic-field-induced Wigner crystallization for charged interlayer excitons (CIE) discovered recently in TMD heterobilayers. We derive the ratio of the potential interaction energy to the kinetic energy for the many-particle CIE system in the perpendicular magnetostatic field of an arbitrary strength and predict the crystallization effect in the strong field regime. We show that magnetic-field-induced Wigner crystallization and melting of CIEs can be observed in magneto-photoluminescence experiments with TMD bilayers of systematically varied electron-hole doping concentrations. Our results advance the capabilities of this new generation of transdimensional quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Additive-assisted synthesis and optoelectronic properties of (CH 3 NH 3 ) 4 Bi 6 I 22

Hybrid organic-inorganic halides containing Bi and Sb generally exhibit higher stability and lower toxicity compared to Pb analogues. Here, in this work, synthesis, crystal and electronic structures and optical properties of a brand-new methylammonium bismuth iodide, (MA) 4 Bi 6 I 22 (MA + = CH 3 NH 3 + ), are reported. Interestingly, we find that the presence of the HgI2 is necessary for the targeted preparation of (MA) 4 Bi 6 I 22 . (MA) 4 Bi 6 I 22 contains isolated [Bi 6 I 22 ] 4- clusters made of six edge-sharing octahedral BiI6 units, which are separated by MA + cations in its 0D crystal structure. A relatively low optical band gap of 1.9 eV was estimated for (MA) 4 Bi 6 I 22 based on diffuse reflectance measurements. An intense photoluminescence peak emerges at 636 nm at low temperatures that supports the assigned band gap value. Electronic structure calculations show the presence of flat bands in the valence and conduction bands, consistent with the low-dimensional structure of (MA) 4 Bi 6 I 22 , and slightly indirect nature of the bandgap. Our findings suggest that the use of facilitator moieties such as HgI 2 may provide a pathway to obtaining alternative methylammonium bismuth iodides to (MA) 3 Bi 2 I 9 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective

We present a perspective for accelerating biomass manufacturing via digitalization. We summarize the challenges for manufacturing and identify areas where digitalization can help. A profound potential in using lignocellulosic biomass and renewable feedstocks, in general, is to produce new molecules and products with unmatched properties that have no analog in traditional refineries. Discovering such performance-advantaged molecules and the paths and processes to make them rapidly and systematically can transform manufacturing practices. Furthermore, we discuss retrosynthetic approaches, text mining, natural language processing, and modern machine learning methods to enable digitalization. Laboratory and multiscale computation automation via active learning are crucial to complement existing literature and expedite discovery and valuable data collection without a human in the loop. Such data can help process simulation and optimization select the most promising processes and molecules according to economic, environmental, and societal metrics. We propose the close integration between bench and process scale models and data to exploit the low dimensionality of the data and transform the manufacturing for renewable feedstocks.

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

Resolving buried optoelectronic features in metal halide perovskites via modulation spectroscopy studies

As research on both bulk and low dimensional metal halide perovskites (MHPs) continues to grow, the tools necessary to gain insights into their exotic and highly convoluted optoelectronic features must also expand. Electroabsorption (EA) is a modulation spectroscopy technique that is exceptionally valuable at deconvoluting overlapping spectral features as well as discerning between different electronic environments in semiconductors. This review outlines the critical shortcomings of traditional optical spectroscopy in determining essential properties such as the bandgap and exciton binding energy. In this report we provide a brief overview of the working principles of EA, focusing on the differences between bound and unbound charge carriers that result in unique behavior when interacting with an applied electric field. We discuss key studies highlighting the unique characterization available when coupling EA spectroscopy with traditional steady-state optical tools to investigate interesting and complex optical features in MHPs. We conclude that EA is a crucial tool for pushing the boundaries of our understanding of the optoelectronic properties of MHP thin films. When other optical characterization methods fall short in the richness of data provided, EA can bridge the knowledge gap to provide a complete optoelectronic characterization of novel MHPs and deepen the understanding of current structures and compositions as a function of their structural and morphological dimensionality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Tailoring capping-layer composition for improved stability of mixed-halide perovskites

Incorporating a low dimensional (LD) perovskite capping layer on top of a perovskite absorber, improves the stability of perovskite solar cells (PSCs). However, in the case of mixed-halide perovskites, which can undergo halide segregation into single-halide perovskites, a systematic study of the capping layer's effect on mixed-halide perovskite absorber is still lacking. This study bridges this gap by investigating how the 1D perovskite capping layers on top of MAPb(I x Br 1–x ) 3 (x = 0, 0.25, 0.5, 0.75, 1) absorbers affect the films' stability. We utilize a new method, dissimilarity matrix, to investigate the image-based stability performance of capping-absorber pair compositions across time. This method overcomes the challenge of analyzing various film colors due to bandgap difference in mixed-halide perovskites. We also discover that the intrinsic absorber stability plays an important role in the overall stability outcome, despite the capping layer's support. Within the 55 unique capping-absorber pairs, we observe a notable 1D perovskite material, 1-methoxynaphthalene-2-ethylammonium chloride (2MeO–NEA–Cl or 9-Cl), that improves the stability of MAPbI 3 and MAPb(I 0.5 Br 0.5 ) 3 by at least 8 and 1.5 times, respectively, compared to bare films under elevated humidity and temperature. Surface photovoltage results also show that the accumulation of electrostatic charges on the film surface depends on the capping layer type, which could contribute to the acceleration/deceleration of degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A graph neural network-state predictive information bottleneck (GNN-SPIB) approach for learning molecular thermodynamics and kinetics

Molecular dynamics simulations offer detailed insights into atomic motions but face timescale limitations. Enhanced sampling methods have addressed these challenges but even with machine learning, they often rely on pre-selected expert-based features. Here, in this work, we present a Graph Neural Network-State Predictive Information Bottleneck (GNN-SPIB) framework, which combines graph neural networks and the state predictive information bottleneck to automatically learn low-dimensional representations directly from atomic coordinates. Tested on three benchmark systems, our approach predicts essential structural, thermodynamic and kinetic information for slow processes, demonstrating robustness across diverse systems. The method shows promise for complex systems, enabling effective enhanced sampling without requiring pre-defined reaction coordinates or input features.

Zou, Ziyue↗
DOE OSTI2025

Ultra broadband yellow emitting lead-free metal halide perovskite like compounds with near-unity emission quantum yields

Metal halide perovskites (MHPs) are interesting semiconductor materials with potential for use in optoelectronic and photonic devices. Their practical applications are hindered due to the negative environmental effects of the lead ions (Pb 2+ ) used in these materials and stability issues. Exploring new environmentally friendly materials with lead-free metal halides and investigating the factors affecting their optical properties and stability are essential. The broadband emission and high (near-unity; ~100%) photoluminescence quantum yield (PLQY) of low-dimensional copper(I) halides make them great candidates for the next-generation luminescent materials for lighting applications. Here, a Cu(I) iodide based organic/inorganic hybrid halide (benzo-15-crown-5) 2 NaH 2 OCu 4 I 6 (BCNCI) with a zero-dimensional (0D) cluster was prepared. The BCNCI has a broadband yellow emission peaked at 548 nm with a near-unity PLQY (99.1%) upon excitation at 365 nm (ultraviolet). Upon excitation at 450 nm (blue), a high PLQY of 82% was also achieved. The luminescence mechanism was discussed in detail. Interestingly, BCNCI exhibits ultra-broad band excitation in the 300–500 nm range, which matches commercially available UV and blue-emitting chips. Compared to commercial YAG:Ce 3+ phosphors, the emission spectrum is sufficiently broad to cover the visible spectral region. This work illustrates a good example of developing an environmentally friendly white light source, using high-performance copper halides with adequate broadband excitation and emission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Enhancing generative molecular design via uncertainty-guided fine-tuning of variational autoencoders

In recent years, deep generative models have been successfully applied to various molecular design tasks, particularly in the life and materials sciences. One critical challenge for pre-trained generative molecular design (GMD) models is to fine-tune them to be better suited for downstream design tasks that aim at optimizing specific molecular properties. However, redesigning and training an existing effective generative model from scratch for each new design task are impractical. Furthermore, the black-box nature of typical downstream tasks that involve property prediction makes it nontrivial to optimize the generative model in a task-specific manner. In this work, we propose an uncertainty-guided fine-tuning strategy that can effectively enhance a pre-trained variational autoencoder (VAE) for GMD through performance feedback in an active learning setting. The strategy begins by quantifying the model uncertainty of the generative model using an efficient active subspace-based UQ (uncertainty quantification) scheme. Next, the decoder diversity within the characterized model uncertainty class is explored to expand the viable space of molecular generation. The low-dimensionality of the active subspace makes this exploration tractable using a black-box optimization scheme, which in turn enables us to identify and leverage a diverse set of high-performing models to generate enhanced molecules. Empirical results across six target molecular properties using multiple VAE-based generative models demonstrate that our uncertainty-guided fine-tuning strategy consistently leads to improved models that outperform the original pre-trained models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Design principles of spacer cations for suppressing phase segregation in 2D halide perovskites

Suppression of photoinduced halide segregation in mixed halide perovskites remains a significant challenge for their application as wide bandgap semiconductors in solar cells. In addition to stability issues, halide segregation leads to a loss in power conversion efficiency in solar cells and a shift in emission wavelength in light-emitting devices. However, employing low-dimensional halide perovskites, such as two-dimensional (2D) or quasi-2D structures, offers a strategy to mitigate this segregation. Here, we have systematically studied how the molecular structure and binding configuration of spacer cations, ranging from linear alkyl chains to aromatic structures, affect photoinduced halide segregation across both Ruddlesden–Popper (RP) and Dion–Jacobson (DJ) frameworks in 2D mixed halide perovskites (Br : I = 50 : 50). Aromatic spacer cations within the DJ perovskite configuration were found to suppress segregation most effectively. For example, the halide segregation rate in a 2D mixed halide perovskite film with the DJ phase using the aromatic spacer cation 1,4-phenylenedimethanammonium (PDMA) was 9.3 × 10 −4 s −1 —an order of magnitude lower than that observed with linear 2D RP perovskites employing butylammonium (BA) as the spacer cation (6.1 × 10 −3 s −1 ). Spectroscopic studies detailing the influence of spacer cation selection in mixed halide perovskites for suppressing phase segregation are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Novel Partitioned Approach for Reduced Order Model—Finite Element Model (ROM-FEM) and ROM-ROM Coupling

Partitioned methods allow one to build a simulation capability for coupled problems by reusing existing single-component codes. In so doing, partitioned methods can shorten code development and validation times for multiphysics and multiscale applications. In this work, we consider a scenario in which one or more of the “codes” being coupled are projection-based reduced order models (ROMs), introduced to lower the computational cost associated with a particular component. We simulate this scenario by considering a model interface problem that is discretized independently on two non-overlapping subdomains. Here we then formulate a partitioned scheme for this problem that allows the coupling between a ROM “code” for one of the subdomains with a finite element model (FEM) or ROM “code” for the other subdomain. The ROM “codes” are constructed by performing proper orthogonal decomposition (POD) on a snapshot ensemble to obtain a low-dimensional reduced order basis, followed by a Galerkin projection onto this basis. The ROM and/or FEM “codes” on each subdomain are then coupled using a Lagrange multiplier representing the interface flux. To partition the resulting monolithic problem, we first eliminate the flux through a dual Schur complement. Application of an explicit time integration scheme to the transformed monolithic problem decouples the subdomain equations, allowing their independent solution for the next time step. We show numerical results that demonstrate the proposed method’s efficacy in achieving both ROM-FEM and ROM-ROM coupling.

de Castro, Amy↗