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At least 595 records · Page 33

Microalgae Commodities from Coal-Fired Power Plant Flue Gas CO 2 (Draft Final Report, October 1, 2015 to June 30, 2018)

The Orlando Utilities Commission (OUC) operates an approximately 900-MWe coal fired-power plant at Stanton Energy Center (SEC), which was the site for this project to develop an integrated process for microalgae utilization of flue gas CO 2 for the production of biofuels and animal feeds. Microalgae have both potentially high yields (tons biomass/acre-year) and can be used for biofuels or high value animal feeds. The high biomass yields of microalgae cultures allows efficient use of land and water resources. They can also use wastewaters, recycle fertilizers, and have lower overall greenhouse gas emissions than conventional biofuels or animal feeds. However, many technical issues and technology gaps related to large-scale algae biomass production still must be resolved before such a process can be scaled-up. In this project, techno-economic analyses (TEAs) and life cycle assessments (LCAs) were carried out, projecting the costs and impacts of large-scale algae biomass cultivation for production of biofuels and animal feeds using OUC-SEC flue gas CO 2 . In addition, 3.5-m 2 (~ 40-ft 2 ) experimental raceway ponds were used for the cultivation of microalgae at OUC-SEC and also at the University of Florida. A large-scale algae farm was designed for a 1,300-acre site (~500-ha) located near the OUC-SEC plant, consisting of 400 hectares (1,000 acres) of paddle wheel mixed raceway ponds (each 4 ha), receiving flue gas piped approximately 3 km (2 miles) from the SEC plant. In the first year of this project (Budget Period 1, BP1), the TEA and LCA studies focused on the production of biogas produced from algae biomass and its use to replace coal at the power plant. However, due to the resulting very high cost of CO 2 mitigation, the process was modified to produce compressed natural gas (‘renewable natural gas’, RNG) for transportation fuel from the biogas, in conjunction with wastewater treatment by the algae cultures. During Budget Period 2 (BP2), the TEA and LCA studies focused on the production of animal feeds by the algae farm, using fresh water and agricultural fertilizers. In this case, CO 2 mitigation costs would be entirely covered if the algal biomass could be sold at between a two to three-fold premium above soybean feed, based on a higher nutritional value for the algal biomass. In support of the above analyses, microalgae cultivation experiments were carried out for over two years during this project in small 3.5-m 2 ponds at both SEC and the University of Florida. The most important results were the demonstration at SEC of the cultivation, on flue gas CO 2 , of filamentous algae biomass, which can be harvested at much lower cost than processes required for the colloidal algae species, as currently used by almost all algal mass culture biofuels and animal feeds projects. The yield of biogas production from the algal biomass was investigated by the University of Florida, and the value of the algal biomass as animal feed was projected based on biochemical analysis of the SEC ad UF biomasses. The conclusion from TEA/LCA carried out for the biogas case in BP1 was that a 400-ha algae system producing biomethane for co-firing at OUC-SEC could generate 27,500 MWh/yr of renewable power, offsetting 28,400 Mg CO 2eq /yr, which amounted to less than 1% of the CO 2 emitted by the SEC plant. (Mg = metric ton = 1.10 short tons). The overall cost was projected at $820/Mg of CO 2eq reduction, making this process unfeasible under any possible scenario. More favorable economics were projected when the biogas was converted to higher value transportation fuel, RNG, which also would benefit from renewable fuel (RINs) and possibly other credits. However, only by combining RNG production with municipal wastewater treatment in the algal ponds would CO 2 utilization result in no net cost or even be economically beneficial (i.e., generate income to the power plant). However, in that case the amount of CO 2 utilization would be even lower than that in the biogas case, because a large fraction of the carbon required would be supplied from the wastewater and CO 2 recovered during biogas upgrading to RNG. In brief, use of power plant CO 2 emissions for algal biofuels production was not favorable, even with optimistic assumptions about biomass productivity and biogas yields. For the animal feed case, developed during BP2, algal biomass would replace soybean feeds. The same scale 400-ha algal production plant was projected to produce 26,280 Mg per year of animal feed with a utilization of 45,300 Mg flue gas CO 2 taken up by the algal biomass. However, the process would result in a projected reduction of 112,500 Mg CO 2eq emissions per year, or roughly 1.9% of OUC-SEC emissions, mainly due to the large CO 2eq emissions from conventional soybean production. A major factor in this analysis were greenhouse gas emissions from land use changes. The cost of CO 2 utilization was projected at $116/Mg if the biomass sold for the same price as soybean meal, but if sold as a premium feed (e.g., based on high omega-3 fatty acid and carotenoid content), the power plant could actually charge for the CO 2 utilized. These economic projections are sensitive to assumptions underlying the TEA and LCA models, including biomass composition and the financial models used to project CAPEX and OPEX. Further development of an algal animal feed production using coal-fired power plant flue gas CO 2 is recommended based on the TEA and LCA, as well as experimental results. The required research and development is detailed in a technology gap analysis (Section 11), which focuses on the demonstrations of the cultivation of higher value filamentous algal biomass at OUC-SEC.

01 COAL, LIGNITE, AND PEAT↗

Total Protein Content Determination of Microalgal Biomass by Elemental Nitrogen Analysis and a Dedicated Nitrogen-to-Protein Conversion Factor

Accurately determining protein content is important in the valorization of algal biomass in food, feed, and fuel markets, where these values are used for component balance calculations. Conversion of elemental nitrogen to protein is a well-accepted and widely practiced method, but depends on developing an applicable nitrogen-to-protein conversion factor. The methodology reported here covers the quantitative assessment of the total nitrogen content of algal biomass and a description of the methodology that underpins the accurate de novo calculation of a dedicated nitrogen-to-protein conversion factor.

09 BIOMASS FUELS↗

Lunar Equator Regenerative Fuel Cell System Efficiency Analysis

It is expected that future NASA mission energy storage requirements can be adequately met by regenerative fuel cells (RFCs). Aerospace RFCs are likely to package proton exchange membrane electrochemical conversion devices based on hydrogen, oxygen, and water. To optimize system designs and direct further development, the most useful system metric is round-trip efficiency (RTE). Improving RTE generally increases specific energy and reduces system mass. The following analysis models the impact of several factors on RTE for RFCs scaling from 0.1 to 50 kW. The analysis demonstrates that higher electrolyzer (EZ) operational pressure most negatively impacts both RFC RTE and specific energy. Reactant storage heating and power management losses are significant for RFCs of any scale, but solenoid valve power becomes a noticeable parasitic load for smaller RFCs. Spherical gas storage vessels benefit RTE by only 2 to 4 percentage points but increase specific energy by ~50 percent. Cryogenic reactant storage is shown to depress RTE to below 15 percent in all cases. For a given RFC scale, there is an RTE benefit to specifying larger EZs and recharging at higher rates—if the RFC can be coupled with a corresponding power source. Although fuel cell (FC) operation is less impactful on RTE than EZ factors, efficiency is maximized by sizing the FCs relatively large and keeping current density low. RFC design is a balance of many interrelated factors, but this analysis provides a starting point for difficult decisions that must be made when designing a lunar equator RFC.

regenerative fuel cell↗

Success Probability Analysis for Shuttle Based Microgravity Experiments

Presented in this report are the results of data analysis of shuttle-based microgravity flight experiments. Potential factors were identified in the previous grant period, and in this period 26 factors were selected for data analysis. In this project, the degree of success was developed and used as the performance measure. 293 of the 391 experiments in Lewis Research Center Microgravity Database were assigned degrees of success. The frequency analysis and the analysis of variance were conducted to determine the significance of the factors that effect the experiment success.

Liou, Ying-Hsin Andrew↗

The Origin of Improved Performance in Boron‐Alloyed Silicon Nanoparticle‐Based Anodes for Lithium‐Ion Batteries

Stabilizing the solid electrolyte interphase (SEI) remains a key challenge for silicon‐based lithium‐ion battery anodes. Alloying silicon with secondary elements like boron has emerged as a promising strategy to improve the cycle life of silicon anodes, yet the underlying mechanism remains unclear. To address this knowledge gap, how boron concentration influences battery performance is systematically investigated. These results show a near‐monotonic increase in cycle lifetime with higher boron content, with boron‐rich electrodes significantly outperforming pure silicon. Additionally, silicon‐boron alloy anodes exhibit nearly three times longer calendar life than pure silicon. Through detailed mechanistic analysis, alternative contributing factors are systematically ruled out, and it is proposed that improved passivation arises from a strong permanent dipole at the nanoparticle surface. This dipole, formed by undercoordinated and highly Lewis acidic boron, creates a static, ion‐dense layer that stabilizes the electrochemical interface, reducing parasitic electrolyte decomposition and enhancing long‐term stability. These findings suggest that, within the SEI framework, the electric double layer is an important consideration in surface passivation. This insight provides an underexplored parameter space for optimizing silicon anodes in next‐generation lithium‐ion batteries.

25 ENERGY STORAGE↗

Effect of Iron Phase Evolution on Copper Separation from Slag Via Coal-Based Reduction

Copper slag, a by-product of copper pyrometallurgy, inevitably contains a certain amount of copper. Oxygen-enriched smelting technologies increase the copper content in slag indirectly because of the production of higher-grade matte. The effect of iron phase evolution on the copper content in slag during the slag cleaning process in an electric furnace was investigated using the method of combining theory with experiments. Based on the analysis, the main factors that impede the separation of slag and copper/matte were determined. Subsequently, the properties of slag were analyzed after decreasing the magnetite content within the slag. The experimental results showed that decreases in magnetite content were beneficial for the separation of copper and slag because of the decrease of slag viscosity. Nevertheless, Cu-Fe alloys formed when magnetite was completely reduced to metallic iron, and the foaming slag was formed at 1250 °C. Furthermore, the distribution of copper in the reduced slags was studied in detail.

36 MATERIALS SCIENCE↗

Removable coatings: Thermal stability and decontamination of steel surfaces from 241 Am

This study presents a comparative analysis of several strippable materials for decontamination of steel surfaces from 241 Am. The strippable coatings were chosen to have a history of application, to be commercially available, easily handled and have different composition and formulation. Carbon steel and stainless steel surfaces (coupons) were utilized as the most representative industrial materials, and the experimental series were expanded to include the rusting treatment of these surfaces as it is common for decommissioned old nuclear facilities. The experiments followed the path of pre-screening of the strippable materials (easiness of application, peeling etc.), their characterization with Fourier-transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA), decontamination factors (DF) or removal efficiencies for different types of steel surfaces, and enhancement of the removal efficiencies of the select strippable coatings via amendment with EDTA. As a result, DF and removal efficiencies for stainless steel (both pristine and with rusting treatment) are higher than for pristine carbon steel, and decontamination factors and removal efficiencies are higher for pristine than for rusted carbon steel across all the coatings. It is also shown that EDTA amendment can improve DF and removal efficiency for a strippable coating (i.e., CC Strip), however other factors should also be considered. Thus, the coating CC Strip exhibited easiness in handling and high DF (up to 97% when EDTA-amended), but its drying period was the longest among the rest of the materials and its thermal decomposition indicates on a risk of intense release of heat in case of a fire event.

36 MATERIALS SCIENCE↗

A machine learning model for predicting the minimum miscibility pressure of CO 2 and crude oil system based on a support vector machine algorithm approach

CO 2 enhanced oil recovery (EOR) is a potential way for carbon capture, utilization and storage (CCUS). Though, the effect of CO 2 injection is greatly influenced by the reservoir conditions. Typically, Minimum miscible pressure (MMP) is selected as one of the key parameters for the screening and evaluation of prospective CO 2 flooding. Conventional slim tube test is both accurate and widely accepted but it is inefficient. Existing empirical formulas for MMPs are easy to be used but have been proved inaccurate and unreliable. Machine learning-based methods have great advantages in predicting MMP. However, only predication accuracy is discussed for most models without the screening of the main control factors and further validation of the model reliability. In this paper, a new prediction model based on support vector machine (SVM) was developed for pure/impure CO 2 and crude oil system. This study was based on 147 sets of MMP data from the literature with full information on reservoir temperature, oil composition and gas composition. The main control factors were screened by several statistical methods. Unlike the conventional prediction models that verified by only prediction accuracy, learning curve and single factor control variable analysis are further validated to obtain the optimum model.

02 PETROLEUM↗

Performance optimization of CO 2 heat pump water heater

A preliminary analysis was conducted to analyze the performance of a heat pump water heater (HPWH) that uses CO 2 as the refrigerant. A model to predict the performance was developed and calibrated based on the experimental data for an existing HPWH using a CO 2 refrigerant. The calibrated model was then used to run a parametric analysis in which factors such as water supply temperature, water circulation rate, tank stratification, and condenser configuration were considered. The performance of a commercial CO 2 system was compared with that of a similar system using R-134a as the refrigerant. It was found that CO 2 HPWH performance was comparable to that of an R-134a HPWH, more so for a separated gas cooler configuration. For comparable performance, the compressor size and the tube-in-tube heat exchanger (condenser/gas cooler) size were compared for CO 2 - and R-134a-based systems. Finally, the impact of the water circulation rate on the water temperature stratification in the tank, an essential requirement for higher performance for CO 2 HPWH systems was also investigated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

MicroRNA-140-5p attenuated oxidative stress in Cisplatin induced acute kidney injury by activating Nrf2/ARE pathway through a Keap1-independent mechanism

Oxidative stress was predominantly involved in the pathogenesis of acute kidney injury (AKI). Recent studies had reported the protective role of specific microRNAs (miRNAs) against oxidative stress. Hence, we investigated the levels of miR140-5p and its functional role in the pathogenesis of Cisplatin induced AKI. A mice Cisplatin induced-AKI model was established. We found that miR-140-5p expression was markedly increased in mice kidney. Bioinformatics analysis revealed nuclear factor erythroid 2-related factor (Nrf2) was a potential target of miR-140-5p, We demonstrated that miR-140-5p did not affect Kelch-like ECH-associated protein 1 (Keap1) level but directly targeted the 3′-UTR of Nrf2 mRNA and played a positive role in the regulation of Nrf2 expression which was confirmed by luciferase activity assay and western blot. What was more, consistent with miR140-5p expression, the mRNA and protein levels of Nrf2, as well as antioxidant response element (ARE)-driven genes Heme Oxygenase-1 (HO-1) and NAD(P)H:quinone oxidoreductase l (NQO1) were significantly increased in mice kidney tissues. In vitro study, Enforced expression of miR-140-5p in HK2 cells significantly attenuated oxidative stress by decreasing ROS level and increasing the expression of manganese superoxide dismutase (MnSOD). Simultaneously, miR-140-5p decreased lactate dehydrogenase (LDH) leakage and improved cell vitality in HK2 cells under Cisplatin-induced oxidative stress. However, HK2 cells transfected with a siRNA targeting Nrf2 abrogated the protective effects of miR-140-5p against oxidative stress. These results indicated that miR-140-5p might exert its anti-oxidative stress function via targeting Nrf2. Our findings showed the novel transcriptional role of miR140-5p in the expression of Nrf2 and miR-140-5p protected against Cisplatin induced oxidative stress by activating Nrf2-dependent antioxidant pathway, providing a potentially therapeutic target in acute kidney injury. - Highlights: • miR-140-5p expression was up-regulated in Cisplatin induced AKI. • miR-140-5p directly targeted the 3′-UTR of Nrf2 mRNA. • miR-140-5p activated the Nrf2/ARE signaling pathway and served as an early protective response against oxidative stress.

60 APPLIED LIFE SCIENCES↗

Mapping the Complete Reaction Energy Landscape of a Metal–Organic Framework Phase Transformation

Crystalline materials undergo valuable phase transformations, and the energetic processes that underlie these transformations can be fully characterized through a combination of thermodynamic and kinetic studies. Here, we report the first complete reaction energy landscape of metal–organic framework (MOF) interpenetration, specifically in the phase transformation of NU-1200 to its doubly interpenetrated counterpart, STA-26. We characterized the thermodynamics of this phase transformation by pairing experiments with density functional theory (DFT) calculations. This analysis revealed that factors such as the increase in crystal density likely drive Zr- and Hf-NU-1200 to STA-26 interpenetration, while other chemical interactions such as steric repulsions prevent Th-NU-1200 from interpenetrating. Using time-resolved in situ X-ray diffraction, we monitored phase transformation reaction profiles and extracted quantitative kinetic information using the Avrami-Erofe’ev model. As a result, we obtained activation energies for the Zr- and Hf-NU-1200 transformations to Zr- and Hf-STA-26, respectively, revealing slower phase change kinetics for MOFs with stronger bonds. Finally, we paired the kinetic data with experimental observations to classify the mechanistic model of this phase transformation as partial dissolution. Here, we anticipate that this thermodynamic, kinetic, and mechanistic understanding will broadly inform further studies on the energetics of crystallization.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Learning from Imperfections: Predicting Structure and Thermodynamics from Atomic Imaging of Fluctuations

In materials characterization, traditionally a single experimental sample is used to derive information about a single point in the composition space, while the imperfections, impurities, and stochastic details of material structure are deemed irrelevant or complicating factors in the analysis. Here we demonstrate that atomic-scale studies of a single nominal composition can provide information about microstructures and thermodynamic response over a finite area of chemical space. Using the principles of statistical inference, we develop a framework for incorporating structural fluctuations into statistical mechanical models and use it to solve the inverse problem of deriving effective interatomic interactions responsible for elemental segregation in a La 5/8 Ca 3/8 MnO 3 thin film. Here, the results are further analyzed by a variational autoencoder to detect anomalous behavior in the composition phase diagram. This study provides a framework for creating generative models from a combination of multiple experimental data and provides direct insight into the driving forces for cation segregation in manganites.

36 MATERIALS SCIENCE↗

Sustained Nonphotochemical Quenching Shapes the Seasonal Pattern of Solar-Induced Fluorescence at a High-Elevation Evergreen Forest

Traditional methods of carbon monitoring in mountainous regions are challenged by complex terrain. Recently, solar-induced fluorescence (SIF) has been found to be an indicator of gross primary production (GPP), and the increased availability of remotely sensed SIF provides an opportunity to estimate GPP across the Western United States. Although the empirical linkage between SIF and GPP is strong, the current mechanistic understanding of this linkage is incomplete and depends upon changes in leaf biochemical processes in which absorbed sunlight leads to photochemistry, heat (via nonphotochemical quenching [NPQ]), fluorescence, or tissue damage. An improved mechanistic understanding is necessary to leverage SIF observations to improve representation of ecosystem processes within land surface models. Here we included an improved fluorescence model within the Community Land Model, Version 4.5 (CLM 4.5), to simulate seasonal changes in SIF at a subalpine forest in Colorado. We found that when the model accounted for sustained NPQ, this provided a larger seasonal change in fluorescence yield leading to simulated SIF that more closely resembled the observed seasonal pattern (Global Ozone Monitoring Experiment-2 [GOME-2] satellite platform and a tower-mounted spectrometer system). We found that an acclimation model based on mean air temperature was a useful predictor for sustained NPQ. Although light intensity was not an important factor for this analysis, it should be considered before applying the sustained NPQ and SIF to other cold climate evergreen biomes. More leaf-level fluorescence measurements are necessary to better understand the seasonal relationship between sustained and reversible components of NPQ and to what extent that influences SIF.

54 ENVIRONMENTAL SCIENCES↗

Peak Rain Rate Sensitivity to Observed Cloud Condensation Nuclei and Turbulence in Continental Warm Shallow Clouds During CACTI

Abstract Warm clouds strongly affect Earth's energy budget but remain imperfectly represented in climate models, partly due to the complexity and covariability of relevant processes influencing warm rain. This work presents a detailed analysis of different factors affecting rain rate peak intensity (RR) in continental warm clouds. Clouds were identified with vertically pointing radar and lidar observations and categorized via a temperature‐based cloud type classification algorithm from which warm clouds were isolated. Observations and retrievals of liquid water path (LWP), cloud condensation nuclei concentration (N CCN ), cloud depth, and cloud duration of more than 3,000 separate warm clouds sampled during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign are analyzed in this work. Multiple linear regression (MLR) and random forest (RF) models are applied to assess the relative impact of these variables on RR. Overall, RR tends to increase as cloud depth, LWP, and cloud duration increase, or N CCN decreases. Cloud depth affects RR the most while N CCN impacts it the least. When considering over 170 warm clouds observed at least 1 hr in which in‐cloud turbulence is retrieved, the effect of N CCN on RR remains most likely suppressive, but it is not significant at a 75% level for MLR and is highly uncertain for RF. The impact of in‐cloud turbulence depends on the moment and location it is sampled. Cloud base turbulence around the time of RR suppresses RR, while cloud top turbulence effects are inconclusive. Possible difficulties in isolating robust CCN and turbulence effects on RR are discussed.

54 ENVIRONMENTAL SCIENCES↗

Pathways for practical high-energy long-cycling lithium metal batteries

Lithium (Li)-ion batteries play a critical role in modern day technologies, but their specific energy (Wh kg-1) and energy density (Wh L-1) are approaching the maximum practically achievable values based on existing manufacturing processes with the conventional cathode and anode materials. Developing the next generation rechargeable batteries with a specific energy higher than 300 Wh kg-1, up to 500 Wh kg-1, is a significant challenge. This paper discusses the pathways to build the next generation 500 Wh kg-1 rechargeable Li battery based on Li metal anode and a high nickel-content lithium nickel-manganese-cobalt oxide (high-Ni NMC) cathode. The fundamental requirements and practical technical approaches will be explored to hopefully address this grand challenge. In particular, we discuss the detailed cell level requirements and parameters to achieve high energy density, as well as the significant scientific challenges and potential solutions, including but not limited to enable the direct utilization of Li metal anode with high efficiency and long-term cycling stability, dendrite-free Li metal deposition, high utilization of the cathode materials with high mass loading and reasonable electrode thickness along with minimum parasitic weight in the cathode side. The cell level understanding and validation of the materials properties for high performance and control of interfacial reactions across the whole cell will be explored. New concepts in emerging multifunctional materials and electrolytes/additives and their implications will also be discussed.

lithium metal anode, lithium nickel manganese coba↗

Effect of chiral 2-ethylhexyl side chains on chiroptical properties of the narrow bandgap conjugated polymers PCPDTBT and PCDTPT

Two narrow bandgap conjugated polymers containing chiral 2-ethylhexyl side chains were synthesized: poly[(4,4-bis(2-ethylhexyl)cyclopenta-[2,1-b:3,4-b']dithiophene)-2,6-diyl-alt-(2,1,3-benzothiadiazole)-4,7-diyl] (PCPDTBT*) and poly[(4,4-bis(2-ethylhexyl)cyclopenta[2,1-b:3,4-b0]dithiophene)-2,6-diyl-alt-[1,2,5]-thiadiazolo[3,4-c]pyridine] (PCDTPT*). The presence of a chiral substituent provides a handle to study the geometry of interchain aggregates and/or the secondary structure of these conjugated polymers in solution and in thin films via circular dichroism (CD) spectroscopy, provided that the asymmetry in the side-chain is translated to the optically active conjugated backbone. CD signals are observed for PCPDTBT* and PCDTPT* in poor solvent systems, which indicate the presence of chiral ordering in the aggregates. PCPDTBT* shows greater chiral order than PCDTPT* based on their relative anisotropy factors. Additionally, GIWAXS analysis reveals that PCPDTBT* films are more ordered than what is observed for the same polymer containing racemic 2-ethylhexyl chains. Upon solution deposition, the chiral ordering is found to translate to the solid-state microstructure for PCPDTBT* but not PCDTPT*. The presence of a pyridyl nitrogen on the thiadiazolo[3,4-c]pyridine ring of PCDTPT* favors a planar conformation for the backbone such that it has a higher rotational barrier compared to PCPDTBT*. This larger rotational barrier appears to limit the ability of PCDTPT* to adopt a helical structure or relevant chain distortions for achieving chiral aggregates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The AUREX cell: a versatile operando electrochemical cell for studying catalytic materials using X-ray diffraction, total scattering and X-ray absorption spectroscopy under working conditions

Understanding the structure–property relationship in electrocatalysts under working conditions is crucial for the rational design of novel and improved catalytic materials. This paper presents the Aarhus University reactor for electrochemical studies using X-rays (AUREX) operando electrocatalytic flow cell, designed as an easy-to-use versatile setup with a minimal background contribution and a uniform flow field to limit concentration polarization and handle gas formation. The cell has been employed to measure operando total scattering, diffraction and absorption spectroscopy as well as simultaneous combinations thereof on a commercial silver electrocatalyst for proof of concept. This combination of operando techniques allows for monitoring of the short-, medium- and long-range structure under working conditions, including an applied potential, liquid electrolyte and local reaction environment. The structural transformations of the Ag electrocatalyst are monitored with non-negative matrix factorization, linear combination analysis, the Pearson correlation coefficient matrix, and refinements in both real and reciprocal space. Upon application of an oxidative potential in an Ar-saturated aqueous 0.1 M KHCO 3 /K 2 CO 3 electrolyte, the face-centered cubic (f.c.c.) Ag gradually transforms first to a trigonal Ag 2 CO 3 phase, followed by the formation of a monoclinic Ag 2 CO 3 phase. A reducing potential immediately reverts the structure to the Ag (f.c.c.) phase. Following the electrochemical-reaction-induced phase transitions is of fundamental interest and necessary for understanding and improving the stability of electrocatalysts, and the operando cell proves a versatile setup for probing this. In addition, it is demonstrated that, when studying electrochemical reactions, a high energy or short exposure time is needed to circumvent beam-induced effects.

Frank, Sara (ORCID:0000000163218363)↗

Partially coherent ptychography by gradient decomposition of the probe

Coherent ptychographic imaging experiments often discard the majority of the flux from a light source to define the coherence of the illumination. Even when the coherent flux is sufficient, the stability required during an exposure is another important limiting factor. Partial coherence analysis can considerably reduce these limitations. A partially coherent illumination can often be written as the superposition of a single coherent illumination convolved with a separable translational kernel. This article proposes the gradient decomposition of the probe (GDP), a model that exploits translational kernel separability, coupling the variances of the kernel with the transverse coherence. An efficient first-order splitting algorithm ( GDP-ADMM ) for solving the proposed nonlinear optimization problem is described. Numerical experiments demonstrate the effectiveness of the proposed method with Gaussian and binary kernel functions in fly-scan measurements. Remarkably, GDP-ADMM using nanoprobes produces satisfactory results even when the ratio between the kernel width and the beam size is more than one, or when the distance between successive acquisitions is twice as large as the beam width.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗