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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Novel alkali intercalated and acid-exfoliated biochars with enhanced surface areas for contaminant adsorption applications

Cost-effective and eco-friendly adsorbents are essential in environmental engineering and biochar is a promising material from the perspective. A novel and efficient surface modification approach involving alkali intercalation and acid exfoliation was designed in this study to enhance the physicochemical properties of biochar. Here, the alkali intercalation process utilizes potassium hydroxide (KOH), while acid exfoliation involves varying HNO 3 , H 2 SO 4 , and H 3 PO 4 concentrations. A simple two-stage pyrolysis process was employed to facilitate the intercalation-exfoliation modification. The modified biochars were characterized using BET, SEM, XRD, etc., to understand physicochemical properties. To quantify the effectiveness of the modifications, adsorption of malachite green dye as a model moiety was investigated. Dye removal sorption rates exceeding 99 % were recorded in the case of the biochars modified through a two-step process using KOH and 0.1MH 3 PO 4 . Specifically, the highest contaminant removal of 99.9 % was recorded when 60 mg of the KOH-0.1MH 3 PO 4 biochar was employed, which is significantly higher than unmodified biochar’s 45.41 % removal at a higher dosage of 100 mg. Moreover, the adsorption kinetics revealed that all the modified biochars attained the maximum removal concentrations (~99 % removal) in a mere 300 min, indicating a tenfold improvement in adsorption rate from unmodified biochar's requirement of over 5000 min. The results achieved through this study provide a cost-effective, fast, and environment-friendly technology for enhancing the adsorption characteristics and performance of biochars toward contaminant removal.

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

Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$

Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current-voltage characteristic (I-V curve), the acquisition of which involves specific measurement devices and costly methods. Thus, I-V curves of the PV system level are often not available. Here this paper proposes a methodology (PVPRO) to estimate these I-V curve parameters using only operation (string-level DC voltage and current) and weather data (irradiance and temperature). PVPRO first performs multi-stage data pre-processing to remove noisy data. Next, the time-series DC data are used to fit an equivalent circuit single-diode model (SDM) to estimate the circuit parameters by minimizing the differences between the measured and estimated values. In this way, the time evolutions of the SDM parameters are obtained. We evaluate PVPRO on synthetic datasets and find an excellent estimation of both SDM and the key I-V parameters (e.g., open-circuit voltage, short-circuit current, maximum power, etc.) with an average relative error of 0.55%. The performance, especially the extracted degradation rate of parameters, is robust to various measurement noises and the presence of faults. In addition, PVPRO is applied to a 271 kW PV field system. The relative error between the real and estimated operation voltage and current is less than 1%, suggesting that degradation trends are well captured. PVPRO represents a promising open-source tool to extract the time-series degradation trends of key PV parameters from routine operation data.

14 SOLAR ENERGY↗
DOE OSTI2020

Probabilistic evolution of stochastic dynamical systems: A meso-scale perspective

Stochastic dynamical systems arise naturally across nearly all areas of science and engineering. Typically, a dynamical system model is based on some prior knowledge about the underlying dynamics of interest in which probabilistic features are used to quantify and propagate uncertainties associated with the initial conditions, external excitations, etc. From a probabilistic modeling standing point, two broad classes of methods exist, i.e. macro-scale methods and micro-scale methods. Classically, macro-scale methods such as statistical moments-based strategies are usually too coarse to capture the multi-mode shape or tails of a non-Gaussian distribution. Micro-scale methods such as random samples-based approaches, on the other hand, become computationally very challenging in dealing with high-dimensional stochastic systems. In view of these potential limitations, a meso-scale scheme is proposed here that utilizes a meso-scale statistical structure to describe the dynamical evolution from a probabilistic perspective. The significance of this statistical structure is twofold. First, it can be tailored to any arbitrary random space. Second, it not only maintains the probability evolution around sample trajectories but also requires fewer meso-scale components than the micro-scale samples. To demonstrate the efficacy of the proposed meso-scale scheme, a set of examples of increasing complexity are provided. Connections to the benchmark stochastic models as conservative and Markov models along with practical implementation guidelines are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Leveraging computational thermodynamics to guide SiC-ZrC chemical vapor deposition process development

Here using the CALPHAD approach to understand zirconium carbide deposition, a series of phase equilibria were calculated from a custom thermodynamic database based on a literature source, and the equilibria were used to explore the potential chemical vapor deposition (CVD) processing space in the ZrCl 4 -CH 3 SiCl 3 -CH 4 -H 2 system as a function of pressure, temperature, and gas composition. Several gas ratios were considered. At a given ZrCl 4 :CH 3 SiCl 3 ratio within the range studied, the most important factor was found to be the ratios of CH 4 :ZrCl 4 , wherein the nature of the composition – carbide vs. silicide – could be controlled. A pure binary composition of ZrC and SiC is expected to form by increasing the initial amount of methane and decreasing the amount of hydrogen from values predicted purely based on thermodynamic equilibrium. Rietveld analysis of the x-ray diffractograms from corresponding experimental depositions confirmed that increasing the CH 4 :ZrCl 4 ratio increased the fraction of carbon-containing species (SiC, ZrC) and decreased the fraction of non-carbides (ZrSi, ZrSi 2 , etc.), as predicted from the CALPHAD results.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synthesis and characterization of isotopically barcoded nickel, molybdenum, and tungsten taggants for intentional nuclear forensics

Intentional nuclear forensics is a concept wherein the deliberate addition of benign and persistent material signatures to nuclear material can be used to reduce the time between the discovery of material outside of regulatory control and determination of its original provenance. One concept within intentional nuclear forensics involves the use of perturbed stable isotopes to generate unique isotope ratio “barcodes” to encode information (e.g., production batch, location, etc.) and track material throughout the nuclear fuel cycle. Synthesis of taggant species of nickel (Ni), molybdenum (Mo), and tungsten (W) was undertaken via a double-spike mechanism, wherein two highly enriched isotopes of interest per elemental taggant were mixed to form an enriched “double-spike” which was subsequently isotopically diluted with bulk material having a natural isotopic composition. Two taggant species perturbing isotopic ratios, alpha (α) and beta (β), for each of Ni, Mo, and W were synthesized. Independent measurements of double spikes and alpha and beta taggant species agreed within uncertainty and are clearly resolvable from natural compositions. High-precision analyses were independently performed by MC-ICP-MS at two U.S. National Laboratories, with consensus values and uncertainties calculated for all samples. Observed isotopic perturbations in the final taggant species measured on the order of hundreds to thousands of permille (‰) with respect to natural for isotope ratios of interest (e.g., 60 Ni/ 58 Ni, 100 Mo/ 98 Mo, 186 W/ 183 W). Discrepancies between modeled and measured isotopic compositions were observed and are largely attributed to imprecise vendor assay values for starting materials. Using measured starting material compositions as inputs for the mixing model improved the level of agreement between predicted and measured α and β taggant isotope ratios. Overall, characterization of all taggant species demonstrates that this “barcode” concept could have viability for use in nuclear forensics. Finally, it is expected that for any two-isotope mixing array dozens of isotopic barcodes could be encoded into a material system and subsequently resolved utilizing modern mass spectrometric methods.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Conducting polymer-based electrochemical sensors: Progress, challenges, and future perspectives

Conducting polymers are promising due to their unique properties, such as excellent electrical and optical properties, physical and chemical stability, high conductivity, and effective redox properties with high-temperature stability and biocompatibility. Due to these properties, conducting polymers are useful in diverse applications like sensors, batteries, oil industries, biosensors, biomedicines, catalysis, cancer treatment, etc. This review article aims to discuss the recent trends and analysis of conducting polymer-based electrochemical sensors in diverse areas with all required sensor characteristics, such as the derived limit of detection, utilized techniques for the sensing analysis and derived linear dynamic range with the stability of the sensors. Conducting polymers and their nanocomposites-based electrochemical sensors have demonstrated exceptional capabilities towards detecting various biomolecules, heavy metals, pesticides, and viruses like SARS-COV-2. Incorporation of redox mediators, use of conducting hydrogels, and molecular imprinting are promising strategies for better performance of the derived sensor. The article has demonstrated the existing challenges and limitations and provided solutions in the field. In the future, conducting polymers-based electrochemical sensors can be utilized in wearable sensors and integrated with IoT devices for better reach in real-time applications. They can also be made more accessible with precise control and data output by following specific methodologies. Utilizing green and sustainable conducting polymers can be crucial in advancing eco-friendly practices in the future. Conducting polymer-based electrochemical sensors has affectivity in neurochemical and pathogen sensing, which is essential for brain function and mental health.

42 ENGINEERING↗
DOE OSTI2020

The performance evaluation of direct detection electron energy-loss spectroscopy at 200 kV and 80 kV accelerating voltages

Direct electron detectors (DeDs) have been widely used for imaging studies because of their higher beam sensitivity, lower noise, improved pixel resolution, etc. However, there have been limited studies related to the performance in spectroscopic applications for the direct electron detection. Hereby, taking the advantage of the DeD installed on a high-performance electron energy-loss spectrometer, we systematically studied the performance of a DeD (Gatan's K2 IS) fitted on an aberration-corrected transmission electron microscope (TEM) equipped with an electron monochromator. Using SrTiO3 as the model system, the point spread function in the zero-loss region of the spectrum and the performance for core loss spectroscopy have been investigated under both 200 kV and 80 kV operating conditions. We demonstrate that the K2 detector can achieve an overall better performance at 200 kV than a charge coupled device (CCD) detector. At 80 kV, the K2 DeD is still better than a CCD, except for the relative broad tails of the zero-loss peak. The signal-to-noise ratio is very close for DeD and CCD under 80 kV. Based on our data obtained at different operating voltages, it is clear that DeD will benefit the microscopy community and boost the development of cutting-edge materials science studies by pushing the frontiers in electron energy-loss spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Atomic resolution scanning transmission electron microscopy at liquid helium temperatures for quantum materials

Fundamental quantum phenomena in condensed matter, ranging from correlated electron systems to quantum information processors, manifest their emergent characteristics and behaviors predominantly at low temperatures. This necessitates the use of liquid helium (LHe) cooling for experimental observation. Atomic resolution scanning transmission electron microscopy combined with LHe cooling (cryo-STEM) provides a powerful characterization technique to probe local atomic structural modulations and their coupling with charge, spin and orbital degrees-of-freedom in quantum materials. However, achieving atomic resolution in cryo-STEM is exceptionally challenging, primarily due to sample drifts arising from temperature changes and noises associated with LHe bubbling, turbulent gas flow, etc. In this work, we demonstrate atomic resolution cryo-STEM imaging at LHe temperatures using a commercial side-entry LHe cooling holder. Firstly, we examine STEM imaging performance as a function of He gas flow rate, identifying two primary noise sources: He-gas pulsing and He-gas bubbling. Secondly, we propose two strategies to achieve low noise conditions for atomic resolution STEM imaging: either by temporarily suppressing He gas flow rate using the needle valve or by acquiring images during the natural warming process. Lastly, we show the applications of image acquisition methods and image processing techniques in investigating structural phase transitions in Cr 2 Ge 2 Te 6 , CuIr 2 S 4 , and CrCl 3 . In conclusion, our findings represent an advance in the field of atomic resolution electron microscopy imaging for quantum materials and devices at LHe temperatures, which can be applied to other commercial side-entry LHe cooling TEM holders.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The effect of a transducer’s spatial averaging on an elastodynamic guided wave’s wavenumber spectrum

Elastodynamic guided waves propagate in an elastic solid which makes it difficult, if not impractical, to place a receiving transducer in the direct path of the propagating wave (as one would for an acoustic wave in a fluid medium). Thus, to account for this, receiving transducers are often placed on the surface of the solid waveguide such that the transducer surface is parallel to the wave propagation direction. This transducer orientation introduces spatial averaging, which causes the received signal to have an altered signal amplitude and mode bias. We investigate both of these effects and present a simple model from which we derive a scaling-ratio expression that describes the effects of spatial averaging. Furthermore, we then test its performance using finite-element simulations that incorporate “real-world” assumptions (e.g., transient waves, piezoelectric effects, etc.). The results from the simulations demonstrate that the scaling-ratio can characterize the effects resulting from spatial averaging. The scaling-ratio expression will be particularly useful when designing experiments involving high frequency (small wavelength) guided waves. Lastly, the proposed scaling-ratio expression could be applied to other sensing methods, like Laser Doppler Vibrometry (LDV) or piezoelectric waveguides with inter-digitated transducers, because of its generality. However, the authors are careful to note that the scaling-ratio expression is not intended as a replacement of multi-physics analysis or good experimental design, and the effects of spatial averaging should be avoided whenever possible.

2DFFT↗
DOE OSTI2025

Tailored glycolysis of Nylon 6 to enable upcycling into high-strength adhesives

Nylon is a high-strength polyamide widely used in automotive, textiles, packaging, etc. However, its durability makes nylon waste difficult to manage, with recycling limited to mechanical grinding to make fillers. Here, we report a catalytic glycolysis approach to deconstruct Nylon 6 into controlled-length oligomers, enabling upcycling into value-added materials. A low-molecular-weight oligomer (M n = 1.8 kg/mol) was repolymerized with diepoxy-terminated poly(bisphenol A-co-epichlorohydrin) via mechanochemistry to create a high-performance adhesive. This copolymer achieves lap shear strengths over 22 MPa on steel and bonds steel to carbon fiber composites, nearly tripling the performance of commercial adhesives even at 90°C. Thermomechanical analyses show that the adhesive retains thermal stability similar to nylon 6 but melts at lower temperatures, allowing easier processing. The material can be reprocessed and reused without significant performance loss. This study demonstrates a strategy to convert nylon 6 waste into valuable materials, offering a sustainable path for difficult-to-recycle plastics.

Nylon waste↗
DOE OSTI2021

miR-31-5p promotes proliferation and inhibits apoptosis of goat hair follicle stem cells by targeting RASA1/MAP3K1 pathway

Highlights: • MAP3K1 was upregulated in hair follicle stem cells in response to overexpression miR-31–5p. • We confirmed RASA1 as a target gene of miR-31–5p. • Inhibition of miR-31–5p promotes apoptosis. • The miR-31–5p/RASA1/MAP3K1 axis regulates hair follicle stem cells activity via MAPK pathway. The Yangtze River Delta white goat is a sole goat species that can naturally produce superior-quality brush hair. It's worth to mention that study the developmental mechanism of goat hair follicle stem cells is vital for future breed preservation and molecular breeding. In this study, we successfully isolated hair follicle stem cells from the skin tissue of fetal sheep neck spine, and harvested superior-quality and normal-quality brush hair goat tissue. The expression of miR-31-5p in goat hair follicle stem cells was verified by qPCR and Western blot. The effects of overexpression or inhibition of miR-31-5p on the proliferation and apoptosis of hair follicle stem cells were detected by EdU, CCK-8, flow cytometry, etc. miR-31-5p can significantly improve cell proliferation and inhibit cell apoptosis by targeting RASA1 and upregulating MAP3K1 level, whereas miR-31-5p knockdown led to an opposite effect. These results reveal a miR-31-5p-associated regulatory network between miR-31-5p and RASA1/MAP3K1 during the progression of superiorquality brush hair traits.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Protein 4.1R affects photodynamic therapy for B16 melanoma by regulating the transport of 5-aminolevulinic acid

Highlights: • Protein 4.1R knockout promoted the proliferation, migration, and invasion of B16 cells. • Protein 4.1R knockout induced a decrease expression of 5-ALA transporters GAT-1 and GAT-2. • Protein 4.1R knockout reduced the effect of PDT and downregulated the anti-tumor immune response induced by PDT. Melanoma is the most aggressive malignant tumor of skin cancer as it can grow rapidly and metastasize. Photodynamic therapy (PDT) is a promising cancer ablation method for skin tumors, although it lacks efficiency owing to factors such as tumor characteristics, delivery of photosensitizers, immune response in vivo etc. Extensive investigation of molecules that can potentially modulate treatment efficacy is required. Protein 4.1R is a cytoskeletal protein molecule. Previous studies have shown that protein 4.1R knockdown reduces PDT sensitivity in mouse embryonic fibroblast cells. However, the functional role of protein 4.1R in melanoma is unclear. In this study, we aimed to elucidate the effect of protein 4.1R on PDT for melanoma in mice and the mechanism of anti-tumor immunity. Our results indicated that CRISPR/Cas9-mediated protein 4.1R knockout promotes the proliferation, migration, and invasion of B16 cells. We further investigated the potential mechanism of protein 4.1R on tumor cell PDT sensitivity. Our results showed that protein 4.1R knockout reduced the expression of membrane transporters γ-aminobutyric acid transporter (GAT)-1 and (GAT)-2 in B16 cells, which affected 5-ALA transmembrane transport and reduced the efficiency of PDT on B16 cells. Protein 4.1R knockout downregulated the anti-tumor immune response triggered by PDT in vivo. In conclusion, our data suggest that protein 4.1R is an important regulator in PDT for tumors and may promote the progress and efficacy of melanoma treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Therapeutic targeting of membrane-associated proteins in central nervous system tumors

The activity of the most complex system, the central nervous system (CNS) is profoundly regulated by a huge number of membrane-associated proteins (MAP). A minor change stimulates immense chemical changes and the elicited response is organized by MAP, which acts as a receptor of that chemical or channel enabling the flow of ions. Slight changes in the activity or expression of these MAPs lead to severe consequences such as cognitive disorders, memory loss, or cancer. CNS tumors are heterogeneous in nature and hard-to-treat due to random mutations in MAPs; like as overexpression of EGFRvIII/TGFβR/VEGFR, change in adhesion molecules α5β3 integrin/SEMA3A, imbalance in ion channel proteins, etc. Extensive research is under process for developing new therapeutic approaches using these proteins such as targeted cytotoxic radiotherapy, drug-delivery, and prodrug activation, blocking of receptors like GluA1, developing viral vector against cell surface receptor. The combinatorial approach of these strategies along with the conventional one might be more potential. Henceforth, our review focuses on in-depth analysis regarding MAPs aiming for a better understanding for developing an efficient therapeutic approach for targeting CNS tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Human α-defensin 5 suppressed colon cancer growth by targeting PI3K pathway

Defensins are highly conserved antimicrobial peptides, which ubiquitously expressed in different species. In addition to the functions in host defense, their aberrant expression have also been documented in cancerous tissue including breast cancer, lung caner and renal carcinoma etc. Whereas, roles of Defensin Alpha 5 (DEFA5) in colon cancer has not been explored. Bioinformatic analysis was used to study the expression of DEFA5 and its correlation with clinical outcomes; Western blot, qPCR, Co-immunoprecipitation, xenograft models were used to the study the molecular mechanism. Decreased expression of DEFA5 at protein level was observed in colon tissues. Colon cancer cell lines proliferation and colony formation capacity were significantly suppressed by DEFA5 overexpression. Moreover, in vivo tumor growth in nude mice was also suppressed by DEFA5 overexpression, suggesting a tumor suppressor role of DEFA5 in colon cancer. Mechanistically, DEFA5 directly binds to the subunits of PI3K complex, thus attenuates the downstream signaling transduction, leads to delayed cell growth and metastasis. Collectively, we concluded that DEFA5 showed an inhibitory effect in colon cancer cell growth and may serve as a potential tumor suppressor in colon cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Construction of extracellular matrix-based 3D hydrogel and its effects on cardiomyocytes

Highlights: • SOD and Triton X-100 could efficiently decellularize cells to get cardiac ECM. • Main proteins of cECM were fibronectin, collagen, elastin, fibrillin, laminin, etc. • 75% cECM-containing 3D hydrogel promoted cell proliferation and anti-apoptosis. • cECM3DH facilitated the differentiation of ESCs into CMs. • APcECM3DH was more conducive to NCM and ESC-derived CM maturation. Some discoveries resulted from 2-dimensional (2D) cultured cardiac cells have been disqualified in animal testing and later clinical trials. Extracellular matrix (ECM) plays a vital role in cardiac homeostasis, cardiac ECM (cECM)-based 3D cell cultures can mimics the physiological and pathological conditions in vivo closely, it is hopeful of addressing this challenge. Construction of cECM-based 3-dimensional (3D) hydrogel (cECM3DH) and its effects on cell behaviors were studied here. The results indicated that cellular compartments could be efficiently removed from heart tissue via sodium dodecyl sulfonate (SDS)- and Triton X-100-mediated decellularization, remaining the natural fibrous network structure and major proteins. 3D hydrogel consisted of 1 × 10{sup 7} cells/mL cells and 75% cECM could promote the proliferation and anti-apoptosis ability of human embryonic kidney (HEK)-293T cells. 0.25% trypsin or 0.20% collagenase was suitable to retrieve these cells from 3D hydrogel for further researches. Compared with 2D culture system, cECM3DH could significantly increase the proportion of GATA 4{sup +} cardiomyocytes (CMs) derived from heart tissue of neonatal mouse or induced differentiation of embryonic stem cells (ESCs) (P < 0.05) The expression levels of mature genes including cTnT, JCN, CaV1.2, MYL2, CASQ2, NCX1, and Cx43 of these CMs in adult pig cECM-based 3D hydrogel (APcECM3DH) were significantly higher than that in 2D culture system and in newborn piglet cECM-based 3D hydrogel (NPcECM3DH), respectively (P < 0.05). Therefore, cECM3DH supports the generation of primary CMs and ESC-derived CMs, APcECM3DH was more conducive to promoting CM maturation, which contributes to building 3D model for pathogenesis exploration, drug screening, and regenerative medicine of heart diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Protein Data Bank (PDB): Fifty-three years young and having a transformative impact on science and society

This review article describes the co-evolution of structural biology as a discipline and the Protein Data Bank (PDB), established in 1971 as the first open-access data resource in biology by like-minded structural scientists. As the PDB archive grew in size and scope to encompass macromolecular crystallography, NMR spectroscopy, and cryo-electron microscopy, new technologies were developed to ingest, validate, curate, store, and distribute the information. Community engagement ensured that the needs of structural biologists (data depositors) and data consumers were met. Today, the archive houses more than 230,000 experimentally determined structures of proteins, nucleic acids, and macromolecular machines and their complexes with one another and small-molecule ligands. Aggregate costs of PDB data preservation are ~1% of the cost of structure determination. The enormous impact of PDB data on basic and applied research and education across the natural and medical sciences is presented and highlighted with illustrative examples. Enablement of de novo protein structure prediction (AlphaFold2, RoseTTAfold, OpenFold, etc.) is the most widely appreciated benefit of having a corpus of rigorously validated, expertly curated 3D biostructure data.

bioinformatics↗
DOE OSTI2020

Atomic-Scale Structural Mapping of Active Sites in Monolayer PGM-Free Catalysts by Low-Voltage 4D-STEM

Two-dimensional (2D) materials have attracted a large amount of attention in both basic and applied fields, and scanning transmission electron microscopy (STEM) is often uniquely well-suited for characterizing the atomic-scale structure of these materials [1-4]. As a result, STEM is poised to significantly impact progress on platinum group metal (PGM)-free catalysts, which are currently under intense development to enable low-cost, commercially viable hydrogen fuel cells [5]. While recent advancements have resulted in fuel cell performance comparable to Pt catalysts by some measures [6], cell durability remains a significant challenge, limiting practical applications [7]. Catalytically active sites in PGM-free materials are proposed to be FeN4 complexes embedded in a graphene lattice (Fig. 1b) within layered or other larger materials, but this is still under debate largely due to the range of potential actives sites predicted by computational methods and lack of methods for directly validating these models [5]. Fundamental insights into the atomic structure and resulting degradation pathways of proposed active sites are therefore needed to fully understand and control cell performance and durability [6].2D materials typically make ideal samples for STEM, but those within PGM-free catalysts present additional challenges since these materials are often defect-rich, with a high density of edges, dopant atoms, etc., which significantly increase susceptibility to beam damage at standard operating voltages. This makes analysis of potential FeN4 active sites particularly challenging, since a large proportion of Fe exists at edge sites where beam-induced atomic displacements can prohibit high-resolution structural characterization [6]. Conventional dark-field imaging compounds this problem by producing less signal for a given dose and being less sensitive to light elements than dose-efficient phase contrast imaging techniques such as those enabled by four-dimensional (4D)-STEM [8-10] (Fig. 1a). Consequently, active site structural analysis is often left to methods such as low-resolution imaging combined with quantum chemical calculations [6], which hinders accurate determination of reaction and degradation mechanisms.Here, we demonstrate direct atomic-scale structural mapping of FeN4 sites by performing low-voltage 4D-STEM on a model PGM-free catalyst system with many exposed monolayer regions. To accomplish this, we pair a 30 keV aberration-corrected probe with a fast pixelated detector that has optimal performance at low beam voltages [11]. This enables us to simultaneously image light and heavy elements with high signal-to-noise by center-of-mass analysis (Fig. 1c) while minimizing beam-induced atomic displacements at sensitive sites. The monolayer nature of these materials additionally allows for experimental validation by direct comparison with multislice simulations [12] of model structures (Fig. 1d-e). This work demonstrates how low-voltage 4D-STEM will provide new insights into the atomic-scale structure and degradation mechanisms of active sites in PGM-free catalysts, facilitating the development of low-cost hydrogen fuel cells and other energy conversion technologies in the future [13].

Zachman, Michael↗