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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing spectroscopy and microscopy with emerging methods in photon correlation and quantum illumination

Quantum optics has led to important advancements in our ability to prepare and detect correlations between individual photons. Its principles are increasingly translated into nanoscale characterization tools, furthering methods in spectroscopy, microscopy and metrology. Here, in this Review, we discuss the rapid progress in this field driven by advanced technologies of single-photon detectors and quantum-light sources, including time-resolved single-photon counting cameras, superconducting nanowire single-photon detectors and entangled photon sources of increasing brightness. We emphasize emerging applications in super-resolution microscopy, measurements below classical noise limits and photon-number-resolved spectroscopy—a powerful paradigm for the characterization of nanoscale electronic materials. We conclude by discussing key technological challenges and future opportunities in materials science and bionanophotonics alike.

Tsao, Chieh [University of California, Berkeley, C↗
DOE OSTI2024

Direct Conversion of CO 2 to Olefins over a Cr 2 O 3 /ZSM-5@CaO Cooperative and Bifunctional Material Under Isothermal Conditions

Direct conversion of point-source CO 2 into fine chemicals over cooperative and bifunctional materials (BFMs) – composed of adsorbents and catalysts – has emerged as a promising approach to improve the energy efficiency of the carbon capture and conversion processes. In this study, a bifunctional material consisting of Cr 2 O 3 /ZSM-5 catalyst and CaO adsorbent was developed and tested in the CO 2 -oxidative dehydrogenation of propane (CO 2 –ODHP) for reactive capture of CO 2 in a fixed bed reactor. First, CaO was prepared using two distinct methods: solid-state and citrate sol–gel. The citrate sol–gel method resulted in small and finely-distributed CaO particles, allowing more accessible sites for CO 2 adsorption. Consequently, a high CO 2 adsorption capacity of ~14 mmol/g was achieved with fast adsorption kinetics compared to CaO prepared by the solid-state method. The CaO adsorbent was then combined with the Cr 2 O 3 /ZSM-5 catalyst for BFM synthesis and tested in the CO 2 –ODHP process, targeting propylene production. The BFM was extensively characterized to provide insights into the BFM’s surface chemistry, morphology, and reaction mechanism in the reactive capture process of CO 2 –ODHP. The results revealed that under isothermal adsorption–reaction conditions at 600 °C, a propane conversion of 22.5%, a propylene selectivity of 55.3%, and an olefin selectivity of 67.3% were achieved. The excellent propylene selectivity was attributed to the catalyst acidity and redox property of the Cr 2 O 3 /ZSM-5 catalyst, which facilitated the reaction pathway of propane dehydrogenation in the process of CO 2 –ODHP. Overall, this study renders Cr 2 O 3 /ZSM-5@CaO as promising BFMs with high CO 2 capture capacity and catalytic activity for integrated CO 2 capture and conversion in the ODHP reaction.

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

Understanding Differences in Water Adsorption Isotherms: Structural Variations, Force Fields, and Monte Carlo Simulation Approaches

Accurate prediction of water adsorption in micro- and mesoporous materials with hydrophobic pores is essential for the design and characterization of advanced adsorbent materials for separation and energy applications. Here, we assess the reproducibility and consistency of water adsorption isotherms in two microporous all-silica MFI zeolite structures (MFI-K and MFI-O) using two different zeolite force fields and three simulation approaches: grand canonical Monte Carlo (GCMC), Gibbs ensemble Monte Carlo (GEMC), and transition matrix Monte Carlo (TMMC). We demonstrate that consistent treatment of the bulk fluid phase in GCMC and TMMC simulations is critical for reconciling isotherms across methods, and we construct simulation-based equations of state for the TIP4P water model to enable rigorous fugacity-to-pressure conversions. Large shifts in the isotherms are observed for two zeolite force fields developed using different parametrization strategies, with the GCS force field representing implicitly a defect-containing all-silica zeolite, whereas the TraPPE-zeo force field accurately represents an essentially defect-free all-silica zeolite. While water in the van Koningsveld structure of MFI exhibits a first-order phase transition and condensation-like step for adsorption near room temperature, water in the Olson structure of MFI displays continuous adsorption, attributed to differences in the adsorption free energy landscapes. Structural analysis reveals that small geometric variations, particularly Si–O–Si bond angles near the strongest adsorption sites, lead to these substantial differences in adsorption behavior. Furthermore, our results highlight the sensitivity of simulated water adsorption isotherms in hydrophobic frameworks to seemingly small differences in the framework structures, force field parametrization, and simulation approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mitigate Stress Corrosion Cracking (SCC) in High-strength Al Castings (CRADA 508)

Development of high strength, corrosion resistant, aluminum alloys is important to a number of industries, including automotive, aerospace, power, etc. Understanding how processing methods such as casting, chemistry, additives and recycle content affect an alloy’s microstructure and performance in real world environments is crucial to their implementation. One major concern is how the repeated exposure to saline solutions can be detrimental to the structural integrity of aluminum alloy components. This study was undertaken as a collaboration between Eck Industries and PNNL to investigate the stress corrosion cracking (SCC) and corrosion behavior of aluminum alloys. This work examines the SCC response of three different materials set. First is cast A206 Al alloy produced by three different casting techniques (i.e., permanent mold, and sand casting with and without chill) and with or without nano forming additives as potential grain refiners. The second materials set comprises Al alloy tubes extruded by PNNL’s ShAPE process and produced using raw material with three different ratios of twitch and pre-consumer Al 6061 scrap. Finally, the third materials set comprises two Al-Si-Mg-Fe alloys with controlled Si% and Fe% to mimic recycle grade Al alloys. The corrosion behavior of these materials was characterized using SCC testing and scanning electrochemical cell microscopy (SECCM) technique; mechanical behavior was characterized using tensile testing, and microstructure was characterized using optical and electron microscopy techniques. Of the A206 Al alloys, the samples with nano forming additives performed poorly compared to those without. The best SCC performance (i.e. least degradation in mechanical properties) was demonstrated by A206 alloy sand cast with chill while the permanent mold sample showed the worst SCC performance. The SECCM was performed on A206 alloy sand cast with chill to understand the effect of microstructure and determine the location-dependent corrosion properties on grain boundaries (GB) and inside grains (IG) on the sample. The corrosion potential and current measured on GB and IG at various points on the sample established that the GB locations are more cathodic and corrosive than the IG locations. Further work needs to be conducted to investigate the mechanisms behind the observed dependence of SCC on casting technique and nano forming additives. Among the ShAPE extruded tubes, SECCM data suggests the decreasing order of tendency to corrode as follows: 100% twitch > 75% twitch > 50% twitch. Finally, both variants of the Al-Si-Mg-Fe alloys showed a large volume fraction of Fe- and Si-containing intermetallics and additional work is needed to discern differences in their respective corrosion responses. In summary, correlating local electrochemical behavior (e.g. via SECCM) with micro/nanostructure, in conjunction with bulk mechanical behavior, can help identify the right fabrication method and alloy chemistry to minimize SCC issues in Al alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Constrained GAN-Generated X-Ray CT Data For Self-Supervised And Foundation-Model Segmentation Of Concrete Microstructures

Three-dimensional characterization of materials using X-ray computed tomography (XCT) is challenging due to the complexity of internal structures, noise, and variations in resolution. Traditional computer vision models often struggle to accurately segment these images, particularly in domain-specific applications like materials science. While supervised deep learning approaches have been developed to address the limitations of conventional algorithms, they typically require large amounts of labeled training data and often fail to generalize across different datasets. Self-supervised, few-and zero-shot learning methods have gained prominence in natural image processing and segmentation tasks, but their application to scientific imaging remains limited due to the unique structural complexity, noise, and textural artifacts present in materials science data. In this work, we investigate how domain adaptation, leveraging physics-based and GAN-generated synthetic data, impacts segmentation performance. We introduce a modified Contrastive Unpaired Translation (CUT) model designed to generate realistic labeled data, which can be used for training, pre-training, and fine-tuning segmentation models for real XCT microstructure data. We evaluate the performance of two segmentation approaches: a self-supervised network (SSL-ALPNet) and a foundation model (Segment Anything Model), assessing their improvements when pre-trained and/or fine-tuned on the synthesized data. Our results demonstrate that leveraging synthetic data significantly enhances segmentation performance, particularly in challenging materials science applications.

Ziabari, Amir [ORNL] (ORCID:000000034776457X)↗
DOE OSTI2026

Ultrasonic Resonance Techniques for Materials Research

Mechanical resonances are directly related to the physical behavior of a system at the bulk and microscopic levels. In materials science, resonant ultrasound spectroscopy (RUS) has long been a preferred nondestructive method to study mechanical resonances of solids and precisely measure quantitative material properties, namely elasticity. In recent years, advances in computational power and hardware have enabled RUS to be relevant for an increasing range of applications, such as advanced manufacturing. An extension of this technique, nonlinear RUS (NRUS), has been demonstrated to provide unmatched sensitivity to early-stage damage. NRUS was originally developed to probe geologic materials but has become a vital tool in nondestructive evaluation and materials research, offering a powerful means of quantifying and characterizing microstructural nonlinearity in a broad range of materials. This review summarizes recent developments and growth opportunities in RUS and NRUS techniques, modeling, and applications across a wide range of material systems including metals, composites, geomaterials, and explosives.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solar Spectrum Conversion for an Algae Bioreactor (CRADA Final Report)

This project focused on developing advanced optical coatings to improve solar energy utilization. The research aimed to create lanthanide-doped upconversion nanoparticles (UCNPs) capable of capturing unused near-infrared (NIR) light from the sun and converting it into visible light (blue and red photons) that can be used for photosynthesis. The primary goal was to identify, synthesize, and integrate highly efficient UCNPs into a transparent thin-film device. Through a comprehensive workflow involving computer simulations, high-throughput robotic synthesis, and detailed optical characterization, the project successfully developed a high-performance material. The key technical achievement was the creation of a core-shell UCNP (NaYF₄:20%Yb³⁺, 2%Er³⁺ coated with a 10 nm NaYF₄ shell) that demonstrated a quantum yield of 3.2% for converting 980 nm NIR light into visible light. Transparent thin films fabricated from these nanoparticles showed excellent optical properties, confirming their potential for practical applications. This research adds to the scientific understanding of energy transfer in lanthanide materials and demonstrates a technically effective method for creating efficient light-converting coatings. The primary benefit to the public lies in the potential for these coatings to enhance the efficiency of solar-driven processes, such as boosting the growth of algae in photobioreactors for biofuel production.

14 SOLAR ENERGY↗
DOE OSTI2026

Time at Temperature Experiments on Neutron Irradiated Zircaloy-2 using Conventional & Flash DSC

Dryout events in Boiling Water Reactors (BWRs) are currently treated by NRC regulations as automatic disqualification for continued fuel rod operation, even though this criterion does not account for the rate or duration of power increases, associated changes in material behavior, or the possibility of rewetting. Operational history from Anticipated Operational Occurrences (AOOs) shows that short, transient power excursions often demand only modest heat removal, and industry experience suggests that fuel can briefly enter dryout yet return to safe, stable operation. The lack of detailed understanding of the material response during such events motivates the present series of experiments. This study uses unique and innovative methods to investigate microstructural evolution in irradiated Zircaloy-2 exposed to high temperatures in inert environments. Differential Scanning Calorimetry (DSC) and FlashDSC are combined to build a comprehensive experimental framework capable of identifying the a–ß phase transformation in zirconium and examining defect annealing under steep thermal gradients. FlashDSC enables rapid heating and cooling of Focused Ion Beam (FIB)–prepared large-area lift-outs (LALOs) of irradiated Zircaloy-2 at rates of 1,000 K/s to peak temperatures of 600°C, 750°C, and 900°C. The goal is to determine whether these conditions produce measurable microstructural changes that could influence cladding performance in typical BWR environments. Microstructural characterization includes quantifying dislocation density and assessing secondary phase particle (SPP) size and distribution using Transmission Electron Microscopy (TEM). Ongoing analysis, such as diffraction pattern indexing and 4D STEM processing, will further refine these observations.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Development of Stable Solid Oxide Electrolysis Cells for Low-Cost Hydrogen Production

The project objective was to demonstrate a solid oxide cell-based steam electrolysis stack that exhibits robustness, reliability, endurance, hydrogen purity, and produces hydrogen at elevated pressure of 2 to 3 bar. Innovative materials and processing methods were evaluated to improve degradation characteristics. Performance improvement focused on nearly all layers involved in the cell and stack assembly. Primary attention was paid to zirconia-ceria interface resistance control via sintering optimization and decrease in degradation from the oxygen electrode by evaluating low strontium (Sr) or Sr-free composition for both the oxygen electrode and current collection layer. Stack robustness was addressed by validating redox tolerance of fuel electrode, confirming capability of cells to survive repeated thermal cycles, studying the effect of pressure on performance and degradation, evaluating the effect of contamination on fuel and oxygen electrode performance and degradation, and identifying mitigation strategies to improve performance. The characterization included evaluation of electrochemical performance and stability followed by microstructural analysis. At the cell level, performance and stability improvements were achieved by incorporating a Sr-free oxygen electrode and a denser oxygen electrode barrier layer. At the stack level, pressurized operation reduces demand on first stage compression, the redox tolerant fuel electrode mitigates risk from service interruptions, and improvements to interconnect coating alleviate chromium (Cr) contamination effects. The denser barrier layer was achieved by adding a sintering aid to the samaria-doped ceria (SDC) composition that reduced sintering temperature by 150 °C. The resulting density was on par with the baseline SDC barrier layer density and the lower sintering temperature resulted in less resistive phase formation during sintering. Button cell tests did not demonstrate a change in performance when exposed to silicon (Si) or manganese (Mn) impurities to the fuel electrode and Cr impurity to the oxygen electrode. More detailed study however is warranted. The project addressed SOEC performance and stability at the cell and stack levels through a systematic approach to known sources of degradation that were combined and tested in three stack tests using an electrolyte supported cell design to allow for evaluation of a variety of fuel and oxygen electrode compositions. STK-82 and STK-83 had identical compositions. STK-100 incorporated the best materials and processing variables developed under this and concurrent projects, and was tested at elevated pressure in steam electrolysis. • STK-82 recovered performance after redox and thermal cycling, demonstrating the robustness of the stack and seals. It exhibited stable performance in testing for 500 hours in SOEC mode, followed by 300 hours of cycling between SOEC and SOFC tests. Degradation during SOEC operation was 1.8 %/ 1,000 hours. • STK-83 generated hydrogen at >80% steam conversion, and oxygen above 98.5 % purity during pressurized operation. Both hydrogen and oxygen were generated at 3 barg pressure without the use of a pressure vessel. In addition to balanced pressure, electrolysis operation at 1 bar differential pressure across anode and cathode was also demonstrated to substantial the robustness of the cell and seal. • STK-100 measured at initial ambient pressure conditions showed an area specific resistance of 1.1 ohm-cm 2 , and STK-83 had 1.3 ohm-cm 2 .

08 HYDROGEN↗
DOE OSTI2024

The 300 Marines: characterizing the US Marines with perfect scores on their physical and combat fitness tests

Few US Marines earn perfect 300 scores on both their Physical Fitness Test (PFT) and Combat Fitness Test (CFT). The number 300 invokes the legendary 300 Spartans that fought at the Battle of Thermopylae, which inspired high physical fitness capabilities for elite ground forces ever since. Purpose: Determine distinguishing characteristics of the “300 Marines” (perfect PFT and CFT scores) that may provide insights into the physical and physiological requirements associated with this capability. These tests have been refined over time to reflect physical capabilities associated with Marine Corps basic rifleman performance. Materials and methods: Data were analyzed from US Marines, including 497 women (age, 29 ± 7 years; height 1.63 ± 0.07 m; body mass, 67.4 ± 8.4 kg) and 1,224 men (30 ± 8 years; 1.77 ± 0.07 m; 86.1 ± 11.1 kg). Marines were grouped by whether they earned perfect 300 scores on both the PFT and CFT (300 Marines) or not. We analyzed group differences in individual fitness test events and body composition (dual-energy x-ray absorptiometry). Results: Only 2.5% (n = 43) of this sample earned perfect PFT and CFT scores (n = 21 women; n = 22 men). Compared to sex-matched peers, 300 Marines performed more pull-ups, with faster three-mile run, maneuver-under-fire, and movement-to-contact times (each p < 0.001); 300 Marines of both sexes had lower fat mass, body mass index, and percent body fat (each p < 0.001). The lower percent body fat was explained by greater lean mass (p = 0.041) but similar body mass (p = 0.085) in women, whereas men had similar lean mass (p = 0.618), but lower total body mass (p = 0.025). Conclusion: Marines earning perfect PFT and CFT scores are most distinguished from their peers by their maneuverability, suggesting speed and agility capabilities. While both sexes had considerably lower percent body fat than their peers, 300 Marine women were relatively more muscular while men were lighter.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Extrusion‐Spheronization of Mock Energetic Materials

The primary method for producing plastic bonded explosive (PBX) granules, or “prills”, has remained relatively unchanged for 70 years despite the complex nature of the process. In this work, we demonstrate the feasibility of using an extrusion‐spheronization technique to produce prills for PBX applications. We begin by detailing an inert formulation with similar properties of PBXs and then demonstrate the extrusion‐spheronization processing of these materials. A study is then performed where the spheronization process time of the extruded materials is varied and the resultant prills are morphologically characterized. Further, these prills are then pressed into high‐density articles and subject to compression testing to elucidate trends in process, properties, and performance. It was found that, for our formulation (95 wt.% melamine/5 wt.% polymer binder) and process, a spheronization time of 60 s yielded relatively uniform particles that exhibited improved poured, tapped, and pressed densities. Mechanical strength did not have a strong trend with process time as all spheronized materials had similar peak compression stress at failure. After further optimization, extrusion‐spheronization may be a promising path for future PBX formulation.

extrusion spheronization↗
DOE OSTI2026

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Data Science-Driven Discovery of Multimetallic Oxygen-cycle Electrocatalysts for Enhanced Energy Conversion

The overarching objective of this effort has been to combine state-of-the-art data science techniques, first principles analyses, and molecular-level characterization of electrocatalyst structure and reactivity to identify both in-situ mechanisms for degradation and transformation of electrocatalysts with highly complex catalytic structures and the impact of these transformations on catalytic activity. The primary catalysts of interest have been multielemental alloys, including high entropy alloys (HEA’s), which are characterized by a high degree of disorder and up to 20 different elements within a single nanoparticle. We have applied these strategies primarily to energy-critical oxygen cycle electrocatalytic reactions, including oxygen reduction (ORR), but we have also considered extensions to non-electrochemical chemistries such as ammonia synthesis and decomposition. We have made strong progress in the development of computational methods on both the level of machine learning methods development as well as first principles-based treatments of HEA’s, and we have leveraged these insights to propose promising HEA catalysts for the ORR. On the experimental side, we developed new HEA synthesis and characterization protocols relevant to these reactions and developed a database combining our experimental results with corresponding computational tools.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Egg yolk as a model for gelation: From rheometry to flow physics

Egg yolks are an excellent model for studying sol-gel transitions, particularly the power law viscoelasticity that defines the critical point of gelation. However, prior studies lack comprehensive datasets and fail to visualize flow behavior linked to temperature and time-dependent linear and nonlinear rheology. Here, we present a detailed dataset characterizing egg yolk viscoelasticity across temperature, time, and forcing amplitude using oscillatory shear, step strain, step stress, and constant high strain rate. Novel protorheology visualizations link rheological properties with observable flow behavior. Our findings highlight the nuanced determination of the critical gel point, emphasizing observation timescale dependencies. We compare methods to identify critical temperatures for gelation, including power law viscoelasticity, moduli crossover, diverging zero-shear viscosity, and emerging equilibrium elastic modulus, while visualizing flow consequences near these transitions. Egg yolk is an accessible, realistic, and nontoxic material relevant to the physicist and the chef alike, making it ideal for understanding the rheology of critical gels. By integrating protorheology photos and videos with rigorous rheometric data, we deepen the understanding of critical gels, with broader impacts for studying other materials with sol-gel transitions.

Marsh, Maxwell C. [Department of Mechanical Scienc↗
DOE OSTI2025

An Integrated High-Speed Microstructural Characterization Method Using Simultaneous XRD, Stereo-DIC, and PCI

High-speed characterization of the deformation mechanisms in polycrystalline metals requires the quantification of full strain fields and local microstructural evolutions simultaneously. In this paper, we present a novel experimental method to integrate phase-contrast imaging (PCI), stereographic digital image correlation (stereo-DIC), and full-ring X-ray diffraction (XRD) to allow for the simultaneous characterization of polycrystalline metals at 1MHz or higher. A Kolsky bar was integrated into the synchrotron X-ray source in Sector 32 ID-B at the Advance Photon Source (APS) at Argonne National Laboratory. When the sample is dynamically loaded, the diagnostic methods of full-ring XRD, PCI, and stereo-DIC are properly synchronized to record the deformation behavior at both continuum and microstructural scales as a function of the loading history. An advanced high-strength steel (AHSS) is used as a model material to demonstrate the capabilities of this new experimental method.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accurate and rapid acoustic damage characterization in complex structures using sparse sensor networks and deep learning models

Damage diagnosis in critical components is essential for ensuring the safety and reliability of operations across industries, spanning manufacturing, aerospace, and energy. Traditional acoustic nondestructive testing methods primarily focus on detecting defects through the direct scattering of single-mode incident waves from the damage, which limit their applicability to simple structures and small inspection areas. Our earlier research demonstrated that machine learning algorithms combined with sparse sensor networks can identify critical defect signatures even from multiply scattered, multi-mode acoustic signals, indicating the potential for improved defect inspection in complex, real-world structures. In this work, we demonstrate the successful implementation of this approach in a fixed sensor configuration to rapidly and accurately detect simulated defects in a geometrically complex, real-world structure, a brake rotor hub. Three different types of defects were physically simulated on the surface of the hub, and the collected data were used to train an autoencoder-based deep learning model. Two models were tested, one using single measurements and the other using multiple measurements taking advantage of the spatial distribution of the sensor network. After training, the multi-measurement model achieved 100 % accuracy in identifying, classifying, and locating unseen, unique damages. This work illustrates the potential of the proposed method for a wide range of industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Amino Acid Sequence Controls Enhanced Electron Transport in Heme-Binding Peptide Monolayers

Metal-binding proteins have the exceptional ability to facilitate long-range electron transport in nature. Despite recent progress, the sequence-structure–function relationships governing electron transport in heme-binding peptides and protein assemblies are not yet fully understood. In this work, the electronic properties of a series of heme-binding peptides inspired by cytochrome bc1 are studied using a combination of molecular electronics experiments, molecular modeling, and simulation. Self-assembled monolayers (SAMs) are prepared using sequence-defined heme-binding peptides capable of forming helical secondary structures. Following monolayer formation, the structural properties and chemical composition of assembled peptides are determined using atomic force microscopy and X-ray photoelectron spectroscopy, and the electronic properties (current density–voltage response) are characterized using a soft contact liquid metal electrode method based on eutectic gallium–indium alloys (EGaIn). Our results show a substantial 1000-fold increase in current density across SAM junctions upon addition of heme compared to identical peptide sequences in the absence of heme, while maintaining a constant junction thickness. These findings show that amino acid composition and sequence directly control enhancements in electron transport in heme-binding peptides. Overall, this study demonstrates the potential of using sequence-defined synthetic peptides inspired by nature as functional bioelectronic materials.

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

Charge Transfer in 2D Halide Perovskites and 2D/3D Heterostructures

Halide perovskites have emerged as a versatile class of materials, with applications spanning photovoltaics, light-emitting diodes, transistors, and photodetectors. The introduction of semiconducting ligands to form two-dimensional (2D) perovskites on the surface of three-dimensional (3D) perovskites in perovskite solar cells has been shown to enhance the performance and stability. To improve the interface properties between the 3D perovskite layer and charge carrier transport layers, understanding the charge transfer (CT) process in 2D perovskites is crucial. In this Perspective, we address common terminological inaccuracies in energy level descriptions, delineate methods for energy alignment characterization, and present practical instances of CT in 2D perovskite-incorporated solar cells. Furthermore, we emphasize the significance of precise terminology, appropriate measurement techniques, and rational design of 2D ligands to harness the full potential of 2D perovskites in optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗