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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗
DOE OSTI2021

An experimentally validated evaporative phase change heat transfer model for low mass flux applications using R134a in plate heat exchangers

Plate frame heat exchangers are common in liquid-coupled vapor compression systems due to their compactness and ease of maintenance. In some of these systems, the refrigerant within the evaporator can enter the heat exchanger as a subcooled liquid. As a result, the refrigerant passes through three different phases: single-phase liquid, two-phase fluid, and a superheated vapor. Unfortunately, there have been limited prior studies that have identified the best method to predict performance under these circumstances. Furthermore, previous investigations have not evaluated refrigerant evaporation in large industrial sized plate frame heat exchangers under conditions experienced in the present study experimental test facility, especially at mass fluxes below 7 kg m –2 s –1 . In the present investigation, a model was developed to predict the performance of plate and frame heat exchangers when the fluid enters as a subcooled liquid and exits as a superheated vapor. The model used full-sized plate heat exchanger geometry that was discretized into 20 sections to accurately capture local heat transfer and pressure drop effects. The model was validated using an R134a counter flow heat exchanger used in a turbo-compression cooling system test facility that had subcooled liquid entering the evaporator at low mass fluxes. A variety of empirical correlations were evaluated to determine what combination yielded the best predictive capability over the following range of conditions: 5.8 < G < 6.8 kg m –2 s –1 , 2 < q” < 2.8 kW m –2 , and 10 °C < T sat < 15 °C. When the correlations used a fixed control volume length in the heat flux calculation, the most accurate combination resulted in a mean absolute error of 5.5%. Finally, future studies can use the approach described here to optimize heat exchanger size and performance.

42 ENGINEERING↗
DOE OSTI2021

Flow condensation heat transfer performance of natural and emerging synthetic refrigerants

There is great interest in predicting flow condensation heat transfer for lower global warming potential (GWP) fluids. This paper analyzes the efficacy of common flow condensation correlations developed for particular fluids in order to identify their suitability to predict heat transfer performance of low GWP fluids. Condensation heat transfer data were extracted from the literature, including 19 papers and 1,473 data points for natural refrigerants [i.e., ammonia (R717), CO 2 (R744), propane (R290), isobutane (R600a)] and 35 papers and 5,030 data points for synthetic refrigerants [i.e., R12, R1234yf, R1234ze(E), R1234ze(Z), R22, R32, R41, R123, R125, R134a, R142b, R152a, R161, R404A, R410A, R448A, R449A, R450A, R452B, R454C, R455A, R513A] encompassing tube diameters of 0.1–11.5 mm, mass fluxes of 55–1200 kg/m2s, and saturation temperatures of -25°C–65°C. Correlations analyzed included Akers et al. (1959), Cavallini et al. (2006, 2011), Kim and Mudawar (2013), Macdonald and Garimella (2016), Shah (1979, 2009, 2013, 2016) and Traviss et al. (1973) for smooth tubes and Chamra et al. (2005) and Kedzierski and Goncalves (1999) for enhanced tubes. Since most studies did not report wall temperature, correlations which relied on wall temperature directly or indirectly were excluded from the analysis. For synthetic refrigerants, mean average error (MAE) ranged from 6%–257%, and Cavallini et al. (2011) and Kim and Mudawar (2013) were the best predictors for emerging synthetic refrigerants. Furthermore, the Kim and Mudawar (2013) correlation was found to best predict the heat transfer performance for propane and R600a data, but most correlations did not accurately predict ammonia and CO 2 flow condensation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Overcoming Barriers to Radiopharmaceutical Therapy (RPT): An Overview From the NRG-NCI Working Group on Dosimetry of Radiopharmaceutical Therapy

Radiopharmaceutical therapy (RPT) continues to demonstrate tremendous potential in improving the therapeutic gains in radiation therapy by specifically delivering radiation to tumors that can be well assessed in terms of dosimetry and imaging. Dosimetry in external beam radiation therapy is standard practice. This is not the case, however, in RPT. This NRG (acronym formed from the first letter of the 3 original groups: National Surgical Adjuvant Breast and Bowel Project, the Radiation Therapy Oncology Group, and the Gynecologic Oncology Group)-National Cancer Institute Working Group review describes some of the challenges to improving RPT. The main priorities for advancing the field include (1) developing and adopting best practice guidelines for incorporating patient-specific dosimetry for RPT that can be used at both large clinics with substantial resources and more modest clinics that have limited resources, (2) establishing and improving strategies for introducing new radiopharmaceuticals for clinical investigation, (3) developing approaches to address the radiophobia that is associated with the administration of radioactivity for cancer therapy, and (4) solving the financial and logistical issues of expertise and training in the developing field of RPT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Effects of the method of active site characterization for determining structure-sensitivity in Ag-catalyzed ethylene epoxidation

We report catalysts have been prepared on a low surface area α-Al 2 O 3 support used commercially for previous generation olefin epoxidation catalysts. Prescreening of the low surface area alumina (0.73 m 2 /g) indicated the absence of acid catalyzed isomerization of EO at an evaluation temperature of 210 °C. A 0.1 wt% Ag base material synthesized by incipient wetness impregnation of AgNO 3 was used as a base material for electroless deposition (ED) of additional Ag to increase particle sizes by controlled reduction of Ag + directly onto the preexisting Ag surface to form weight loadings between 0.3 and 5.0 wt% metal. A 12 wt% Ag/α-Al 2 O 3 using Ag 2 C 2 O 4 as the Ag precursor was also prepared to compare performance of the ED samples with a catalyst more typical of industrial formulations. Characterization by SEM, STEM, and hydrogen titration of oxygen precovered Ag characterized before and after catalytic evaluation indicated that microscopy is required to accurately represent distributions of Ag particle sizes, but H 2 titration of O-precovered Ag gives the best representation of active sites since it directly counts the number of Ag surface sites. Larger particles >100 nm are resistant to both Ag sintering and carbon foulant; TOF values were relatively insensitive to particle size with only a 2.2 × difference between the best and worst performing samples. Selectivity, which is not a function of TOF, shows the most significant structure sensitivity effect where particle sizes follow the trend 67 nm ≈ 92 nm (58% EO) < 157 nm (67% EO) < 211–542 nm (73% EO). The lower EO selectivities were also correlated with increased fouling for the smaller Ag sizes, suggesting that more strongly bound EO precursor(s) leads to combustion and CO 2 /H 2 O formation.

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

Recommendations for improving rigor and reproducibility in site specific characterization

Heterogeneous catalysis is driven by the interaction of reactant molecules and the catalyst surface. The locus of this interaction as well as the surrounding ensemble of atoms is referred to as the catalyst active site. Active site characterization attempts to distinguish active catalytic sites from inactive surface sites, to elucidate the structural and chemical nature of active sites, and to quantify active site concentration. Numerous techniques have been demonstrated to provide compositional and structural information about the active sites within a catalyst. However, each technique has its own limitations and experimental pitfalls that can lead to data misinterpretation or irreproducible results. Further, this work aims to provide an overview of the types of data that can be collected, to outline common experimental challenges and how to avoid them, and to assemble relevant references for the most used active site characterization techniques. More broadly, we aim to outline best practices for researchers to collect, interpret, and report active site characterization data in a way that provides the most benefit to the broader catalysis community. Increasing the rigor and reproducibility of active site characterization offers a strategy to better link properties with catalytic performance and to enable the community to develop consensus concerning these relationships.

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

Perovskite design principles for efficient microwave dry reforming with noble metal free catalysts

Microwave absorbing catalysts have the potential to electrify high-temperature thermal reactions such as the dry reforming of methane process (DRM: CO 2 + CH 4 → 2CO + 2 H 2 ). However, microwave catalysts present unique challenges due to their dual requirements of maintaining microwave absorption in both oxidative and reductive environments and stability across a range of temperatures in inherently non-isothermal reactors. Here, catalyst candidates from the La 0.8 Sr 0.2 CoO 3 -La 0.8 Sr 0.2 NiO 3 -La 0.8 Sr 0.2 MnO 3 perovskite systems were screened (28 total) to identify promising microwave catalysts free of noble metals for dry reforming methane. The best performing candidates met two main criteria. First, they occurred at crystal phase boundaries, giving rise to a pseudocubic perovskite structure. The combined use of Goldschmidt tolerance factor and octahedral tolerance factors appeared to be suitable for predicting pseudocubic perovskites. Second, they provided a balance of reducible metal sites with an irreducible metal oxide support. The best performing catalyst was found to exsolve Ni-Co alloy particles as active sites for the DRM reaction which offered superior resistance to coking for excellent reforming efficiency and stability.

42 ENGINEERING↗
DOE OSTI2021

Efficiency and mechanisms of Sb(III/V) removal by Fe-modified biochars using X-ray absorption spectroscopy

Fe-modified biochars (FeBC) are effective antimony (Sb) removal materials; however, the removal mechanisms require further investigation. In this study, aqueous Sb(III) and Sb(V) removal by FeBC (300, 600, and 900 °C) was evaluated, with the adsorption mechanisms investigated using X-ray absorption spectroscopy (XAS). Screening results (based on removal efficiencies) using different types of FeBC indicated the 900 °C FeCl3- modified biochar (FeCl3BC900) achieved the best Sb(III/V) removal performance. The kinetics of the Sb(III/V) removal process were best fitted by a pseudo-second-order model. Additionally, the isothermal results were described by Langmuir and Redlich-Peterson models. Aqueous analysis and X-ray absorption near-edge structure data fitting indicated Sb(III) was oxidized to Sb(V) in the Sb(III)-spiked system, and the oxidation extent increased with increasing pyrolysis temperature. The oxidation process rapidly occurred in both the solution and biochar. No Sb(V) was reduced to Sb(III) in the Sb(V)-spiked system. The XAS results of the isothermal experiment indicated the oxidation capacity of FeCl3BC900 was limited for high initial Sb(III) concentrations. The SbFe1 and Sb-Fe2 bonding distances were 3.05–3.10 and 3.47–3.54 Å, respectively, indicating inner-sphere complexes were formed during the Sb(III/V) removal processes. The Sb(III/V) removal mechanisms included electrostatic adsorption, inner-sphere complexes, and coprecipitation. Oxidation was also involved in Sb(III) removal.

Antimony↗
DOE OSTI2022

Third international challenge to model the medium- to long-range transport of radioxenon to four Comprehensive Nuclear-Test-Ban Treaty monitoring stations

In 2015 and 2016, atmospheric transport modeling challenges were conducted in the context of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) verification, however, with a more limited scope with respect to emission inventories, simulation period and number of relevant samples (i.e., those above the Minimum Detectable Concentration (MDC)) involved. Therefore, a more comprehensive atmospheric transport modeling challenge was organized in 2019. Stack release data of Xe-133 were provided by the Institut National des Radioéléments/IRE (Belgium) and the Canadian Nuclear Laboratories/CNL (Canada) and accounted for in the simulations over a three (mandatory) or six (optional) months period. Best estimate emissions of additional facilities (radiopharmaceutical production and nuclear research facilities, commercial reactors or relevant research reactors) of the Northern Hemisphere were included as well. Model results were compared with observed atmospheric activity concentrations at four International Monitoring System (IMS) stations located in Europe and North America with overall considerable influence of IRE and/or CNL emissions for evaluation of the participants’ runs. Participants were prompted to work with controlled and harmonized model set-ups to make runs more comparable, but also to increase diversity. It was found that using the stack emissions of IRE and CNL with daily resolution does not lead to better results than disaggregating annual emissions of these two facilities taken from the literature if an overall score for all stations covering all valid observed samples is considered. A moderate benefit of roughly 10% is visible in statistical scores for samples influenced by IRE and/or CNL to at least 50% and there can be considerable benefit for individual samples. Effects of transport errors, not properly characterized remaining emitters and long IMS sampling times (12–24 h) undoubtedly are in contrast to and reduce the benefit of high-quality IRE and CNL stack data. Complementary best estimates for remaining emitters push the scores up by 18% compared to just considering IRE and CNL emissions alone. Despite the efforts undertaken the full multi-model ensemble built is highly redundant. An ensemble based on a few arbitrary runs is sufficient to model the Xe-133 background at the stations investigated. The effective ensemble size is below five. An optimized ensemble at each station has on average slightly higher skill compared to the full ensemble. However, the improvement (maximum of 20% and minimum of 3% in RMSE) in skill is likely being too small for being exploited for an independent period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Accounting for uncertainty in complex alluvial aquifer modeling by Bayesian multi-model approach

Alluvial aquifers by nature are complex caused by varied depositional environments. Developing a reliable groundwater model to represent an alluvial aquifer is non-trivial. Also, relying on a single best calibrated model may not be sufficient because of an inadequate choice of model parameter values. To better understand groundwater dynamics and improve model prediction reliability, this study presents a Bayesian multi-model uncertainty quantification (BMMUQ) framework to account for model parameter uncertainty in complex alluvial groundwater modeling. The methodology was applied to the agriculturally intensive Mississippi River alluvial aquifer (MRAA), Northeast Louisiana. An aquifer architecture was first constructed using 7,259 well logs in the MRAA area which covers three fluvial deposits (alluvium, braided-stream terrace, and braided-stream terrace-loess). A 12-layer MODFLOW model was then developed to address the alluvial aquifer complexity and well calibrated through a genetic algorithm. This study quantified model parameter uncertainty in hydraulic conductivity and specific storage of sand facies. Bayesian model averaging (BMA) with the Expectation Maximization (EM) algorithm was adopted to derive posterior model weights and head variances of 50 alternative conceptual groundwater flow models, and thereby obtains BMA ensemble model predictions instead of only relying on the best calibrated conceptual model. Overall, results show that an estimated around 950 million m3 of groundwater storage loss occurs in 2015 with respect to the beginning of 2004, due to high groundwater demand for irrigation in the MRAA area. Explicitly quantifying model uncertainty can produce more reliable groundwater level predictions from BMA ensemble model. The presented groundwater modeling framework improves our understanding of the MRAA and provides a valuable tool to assist agricultural water management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region

In recent years, the Artificial Intelligence and Data Mining (AI&DM) models have become popular tools in assisting various aspects of reservoir operation. However, the practical uses are still rarely reported. Comparison experiment of many AI&DM models over a large number of reservoir cases is particularly valuable to help reservoir operators first examine the usefulness and transferability of different AI&DM models, and then identify the most stable and reliable AI&DM model in assist of various decision-making processes. In this study, a total of 12 AI&DM models with different parameterizations and simulation scenarios are comprehensively tested out and compared in simulating the controlled reservoir outflows of 33 reservoir cases over the Upper Colorado Region, United States. Results show that the Random Forecast and the Long-Short-Term-Memory model could consistently derive the best statistical performance than other models under the baseline simulation scenario. The employed AI&DM models could obtain satisfactory statistical interquartile ranges (25–75%) between [0.6–0.9], [0.3–0.8], and [0.2–0.8], for CORR, NSE, and KGE measurements, respectively, and [1.5–6.5], [–15 to 20], and [0.5–8.5] for the normalized RMSE, PBIAS and RSR measurements, respectively. Results also show Multi-Layer Perceptron model and Extreme Gradient Boosting Tree Algorithm produced more stable and superior performance than other models under more complex input scenarios. We also found that the performance of different AI&DM models are closely relevant to the reservoir elevations, sizes, and functionalities. Discussions were made about the sensitivity of AI&DM models’ parameterizations and the key advantages of AI&DM models over the rule-based reservoir models. We further identify that the main advantage of AI&DM models is the flexibility in designing input structures, whereas the rule-based simulation model is rather limited. Future studies were suggested regarding the best way reservoir operators and researchers could use, select, and apply different AI&DM models in simulating reservoir releases under different natural and modeling environments. Finally, this comparison study also serves as a reference and a piece of groundwork for further promoting the practical uses of AI&DM models in assisting reservoir operation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Intercomparison of flood inundation models across land use types and hydrological flood stages

Flood Inundation Mapping (FIM) model selection is a key operational decision because accurate, rapid mapping underpins early warning and resource allocation. FIM performance is context-dependent and can vary with hydrograph phase, land-use/land-cover (LULC), and the evaluation benchmark. Intercomparison studies typically assess a single near-peak snapshot against one reference dataset. Here, we provide a context-stratified intercomparison across (i) multiple hydrograph phases, (ii) LULC classes, and (iii) benchmark types, for five FIM approaches spanning a wide range of physical complexity and operational cost (TRITON, LISFLOOD-FP, HEC-RAS 2D, ARC-Curve2Flood, and OWP HAND-FIM). We use the Hurricane Matthew flood (2016) in the Neuse River Basin, North Carolina, USA, as a case study. Using high-resolution remote sensing-derived flood inundation maps, hand-labeled points, and building footprints, we assess model skill across two rising and two falling hydrograph limbs and across major LULC types. Results show that model rankings shift systematically across contexts: LISFLOOD-FP ranks highest in three of four flood phases, while TRITON leads during one rising limb phase; LISFLOOD-FP performs best in vegetated areas, whereas HEC-RAS improves relative performance in agricultural and urban areas; and benchmark choice influences conclusions, with LISFLOOD-FP performing best for flooded-building detection in the late falling limb, while TRITON ranks highest against hand-labeled points. We also report representative wall-clock runtimes for each workflow to provide use-case context for operational feasibility. Together, these results offer transferable guidance for model selection and for designing large-scale, benchmark-aware FIM intercomparison studies.

Nikrou, Parvaneh [University of Alabama]↗
DOE OSTI2025

Characterization of the fatigue threshold behavior of UHMWPE

Ultra-high-molecular-weight-polyethylene (UHMWPE) has been the material of choice for bearings in total joint replacements (TJRs) for decades as a result of its excellent wear resistance, chemical inertness, energetic toughness, low friction, and biocompatibility. Utilization of this polymer in orthopedic devices requires oxidation, wear, and fatigue resistance. Balancing these important properties by tailoring processing techniques and modulating microstructural features has been an ongoing endeavor in the field. Research into the clinical applications of UHMWPE has primarily focused on the challenges of wear and oxidation while studies into the realm of fatigue have been more limited. Literature gaps exist in fully understanding the fatigue crack initiation near notches or propagation of small existing flaws in UHMWPE used in TJRs. In particular, the characterization of the fatigue thresholds and near-threshold fatigue behavior of orthopedic grade UHMWPE has yet to be thoroughly explored. In this work, we characterized the fatigue crack arrest threshold of clinically-relevant UHMWPE formulations. Correlations between the fatigue thresholds and bulk mechanical properties as well as microstructural properties were examined across these medical resins. The important role played by crosslinking in influencing the fatigue performance of UHMWPE is highlighted in this study. In addition, it is established that J-integral fracture toughness is the best predictor of fatigue thresholds and could possibly be used as a stand-in metric for fatigue performance if thresholds cannot be directly ascertained. Finally, this study corroborates that the true constitutive parameters best describe the mechanical behavior of UHMWPE.

Cross-linking↗
DOE OSTI2024

Glass-bonded ceramic waste forms for immobilization of radioiodine from caustic scrubber wastes

Glass-bonded sodalite composite waste forms have been developed for the immobilization of liquid radioactive wastes resulting from off-gas treatment during aqueous reprocessing of used nuclear fuel, with a particular focus on 129I. The proposed composite waste form is comprised of aluminosilicate ceramic phases containing volatile radionuclides bonded with a glassy matrix. In this work, a suite of ten candidate low-temperature glass binders (ZnO-Bi2O3-based glasses and a Na2O-B2O3-SiO2 glass) were examined. Six glasses were mixed with caustic scrubber waste simulant previously converted into a sodalite-rich material (to provide glass fractions of 10 and 20 wt.%), uniaxially pressed into pellets, and sintered at 350 °C or 550 °C for 8 h in air. Iodine retention after heat treatment was assessed by neutron activation analysis, showing retention of 67-100 % of expected iodine. The aqueous durabilities of the resulting materials were then determined, following the ASTM C1308 standard test, showing iodine releases of 1 to 23 g m-2 after 4 d. The cumulative iodine release for the best performing system (a zinc-bismuth-borate glass binder) was <1 g m-2, and its iodine retention from processing was 67 %. The iodine releases compared favorably with other waste forms. In parallel, this best-performing composition was also consolidated via hot isostatic pressing (HIP) in a stainless-steel canister at 550 °C for 2 h under 100 MPa pressure. The HIPed sample was produced at the ~20 g scale and showed improved densification and minimal reaction with the canister.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Comprehensive review of photophysical parameters (ε, Φ f , τ s ) of tetraphenylporphyrin (H 2 TPP) and zinc tetraphenylporphyrin (ZnTPP) – Critical benchmark molecules in photochemistry and photosynthesis

Tetraphenylporphyrin (H 2 TPP) and zinc tetraphenylporphyrin (ZnTPP) are widely used benchmark molecules in diverse photochemical studies given facile synthetic access, rich visible-region spectra, and broad structural analogy to chlorophylls. Yet the literature values for each key photophysical parameter – the molar absorption coefficient (ε), fluorescence quantum yield (Φ f ), and also singlet excited-state lifetime (τ S ) – vary over an astonishing range. Here, a comprehensive literature review (~1940–September 2020) encompassing 871 publications is reported for these essential parameters. Each parameter is determined by measurement with distinct instrumentation and suffers idiosyncratic sources of error. The best values for H 2 TPP are ε = 460,000 cm -1 ·M -1 , Φ f = 0.090, and τ S = 12.8 ns in Ar- purged toluene (Φf = 0.070, τS = 9.9 ns in toluene in air); the best values for ZnTPP are ε = 560,000 cm -1 ·M -1 , Φf = 0.030, and τ S = 2.1 ns in Ar-purged toluene (Φ f = 0.029, τ S = 2.0 ns in toluene in air). The choice of values for such parameters has far-reaching consequences in photochemistry ranging from fluorescence (or Förster) resonance energy transfer (FRET) processes to assessments of molecular brightness.

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

Layer-structured triple-conducting electrocatalyst for water-splitting in protonic ceramic electrolysis cells: Conductivities vs. activity

Electron, proton and oxygen-triple-conducting materials are becoming the dominant steam electrode candidate to break the rate limit on the water-splitting reaction that throttles the performance of protonic ceramic electrolysis cells (PCECs). In this study, based on Pr 2 NiO 4+δ Ruddlesden-Popper phase, we manipulate these conductivities by Pr-site Ba substitution to probe the correlation of each conductivity with the kinetics of the elementary reaction steps. It is found that the proton conductivity is vital to sustain an extended active surface area for faster adsorption of reactants and desorption of products. The effect of oxygen conductivity is surprisingly found insignificant in the water-splitting reaction. On the contrary, surface oxygen removal is discovered as the most rate-limiting process. The electronic conductivity is not a direct limiting factor. However, an electron transfer process between the current collector and the electrode junction could introduce extra resistance that is perceptible at a high operating temperature range. The best water-splitting activity is obtained on a proton conductivity/oxygen surface desorption capability well-balanced sample after Ba substitution. As a result, a water-splitting reaction resistance of 0.022 Ωcm 2 , a current density of 1.96 A/cm 2 at 700 °C is achieved on Pr 1.7 Ba 0.3 NiO 4+δ , one of the best performances for PCECs.

25 ENERGY STORAGE↗
DOE OSTI2025

Low Peripheral Blood Counts and Elevated Proinflammatory Cytokines Signal a Poor CD19 Chimeric Antigen Receptor T-cell Response in Acute Lymphoblastic Leukemia

CD19 chimeric antigen receptor T-cell (CAR-T) therapy has significantly improved outcomes for patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL). However, approximately 20% of patients fail to achieve a complete remission (CR), and some develop severe, life-threatening toxicities. Understanding the biological mechanisms underlying both dysfunctional responses and severe toxicity is essential for optimizing patient management and improving therapeutic efficacy. This study aimed to (1) characterize cytokine profiles associated with dysfunctional responses and severe toxicity following CAR-T infusion, (2) examine the timing and trajectory of cytokine changes in relation to treatment outcomes, and evaluate potential strategies for mitigating toxicity and treatment failure. We conducted a comprehensive analysis of serum cytokine profiles in 86 adult and pediatric patients undergoing autologous CD19 CAR-T therapy for B-ALL. Patients were categorized into three groups: (1) Dysfunctional response—Patients who failed to achieve a minimal residual disease-negative CR (MRD-CR) by Day 63 or who experienced recurrence of CD19+ disease in the setting ongoing CAR-T cell detection before Day 63. (2) Functional response with severe cytokine release syndrome (CRS) and/or neurotoxicity (NTX)—Patients with best response of MRD-CR by Day 63 who experienced grade 3 or higher CRS or NTX. (3) Functional response without severe CRS or NTX—Patients with best response of MRD-CR by Day 63 who did not experience grade =3 CRS or NTX. Cytokine levels were measured during the first-week postinfusion and correlated with treatment efficacy, toxicity outcomes, complete blood counts, and CAR-T expansion dynamics. This analysis aimed to better understand how cytokine profiles relate to patient outcomes and immune responses in CAR-T therapy. Patients with dysfunctional response exhibited decreased neutrophils, platelets, and levels of granulocytic cytokines (suggestive of low bone marrow reserve) alongside elevated pro-inflammatory cytokines by Day 1. Functional response with severe toxicity patients showed a progressive rise in proinflammatory cytokines, reaching similar levels to dysfunctional response patients by Day 7. We observed that high cytokines at both the Day 1 and Day 7 time points were associated with poor survival. These findings remained significant when adjusting for high disease burden, a known predictor of severe inflammatory toxicity and lack of response. Early post-CAR-T infusion inflammation is associated with both dysfunctional response and severe toxicity—even after adjusting for disease burden. This suggests that inflammation, in addition to disease burden, plays a role in determining patient outcome. Therefore, strategies aimed at reducing the pro-inflammatory state prior to or early after CAR-T cell infusion may improve outcomes for R/R B-ALL patients.

Serum cytokines↗