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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Editors’ Choice—Rapid Deactivation Convolutes Electrochemical CO 2 Reduction Selectivity Measurements on Gold Rotating Ring Disk Electrodes

Voltammetric measurements of electrochemical CO 2 reduction reaction (CO 2 RR) selectivity on rotating ring disk electrodes (RRDE) are a rapid and sensitive method for quantifying an electrocatalyst’s selectivity, i.e. faradaic efficiency (FE). This method has been applied to polycrystalline Au electrocatalysts where a Au disk electrode catalyzes both the CO 2 RR and hydrogen evolution reaction while the concentric Au ring electrode selectively senses CO by oxidizing CO back to CO 2 . Such measurements enabled fundamental mechanistic studies but suffer from poor inter-laboratory reproducibility. This work identifies causes of variability in RRDE selectivity measurements by comparing protocols with different electrochemical methods, reagent purities, and glassware cleaning procedures. We observed FE CO decrease by 56% during 5 min chronoamperometry measurements, a phenomenon that is not readily apparent in voltammetric scans due to their dynamic nature. Electroplating of electrolyte impurities onto the disk and ring surfaces were identified as a major contributor to Au deactivation. Additionally, the oxygen reduction reaction may lead to higher disk currents in inadequately purged electrolytes, causing an apparent underestimation of FE CO at low overpotentials. Lastly, we propose operational bounds for CO 2 RR selectivity measurements on Au using the RRDE method and provide suggestions on steps for improving the accuracy of this technique.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Selection Signatures Underlying Dramatic Male Inflorescence Transformation During Modern Hybrid Maize Breeding

Inflorescence capacity plays a crucial role in reproductive fitness in plants, and in production of hybrid crops. Maize is a monoecious species bearing separate male and female flowers (tassel and ear, respectively). The switch from open-pollinated populations of maize to hybrid-based breeding schemes in the early 20th century was accompanied by a dramatic reduction in tassel size, and the trend has continued with modern breeding over the recent decades. The goal of this study was to identify selection signatures in genes that may underlie this dramatic transformation. Using a population of 942 diverse inbred maize accessions and a nested association mapping population comprising three 200-line biparental populations, we measured 15 tassel morphological characteristics by manual and image-based methods. Genome-wide association studies identified 242 single nucleotide polymorphisms significantly associated with measured traits. We compared 41 unselected lines from the Iowa Stiff Stalk Synthetic (BSSS) population to 21 highly selected lines developed by modern commercial breeding programs, and found that tassel size and weight were reduced significantly. We assayed genetic differences between the two groups using three selection statistics: cross population extended haplotype homozogysity, cross-population composite likelihood ratio, and fixation index. All three statistics show evidence of selection at genomic regions associated with tassel morphology relative to genome-wide null distributions. These results support the tremendous effect, both phenotypic and genotypic, that selection has had on maize male inflorescence morphology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models

The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Development of Short-Term Forecasting Models Using Plant Asset Data and Feature Selection

Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This paper focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 +- 0.014, 0.0026 +- 0, and 0.063 +- 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The German Site Selection Process - Implementation and Challenges - 20528

Federal Company for Radioactive Waste Disposal (Bundesgesellschaft fuer Endlagerung mbH; hereinafter referred to as BGE) is a state-owned company established in September 2016 following the 'Act on the Organisational Restructuring in the Field of Radioactive Waste Storage'. 'Repository Site Selection Act' (hereinafter referred to as StandAG) defines the site selection procedure, aiming to ensure the best possible safety for storing high-level radioactive waste in Germany for the duration of one million years. The selection procedure is a participatory, transparent, learning and self-questioning process based on scientific expertise. Possible repository sites are sought all over Germany, without excluding or predetermining any potential site at the beginning. The procedure consists of three phases. After each phase, the legislative decides on the regions for further consideration in the next phase of the site selection procedure. The current first phase (Phase I) is divided into two steps. Objective of Step 1 is to determine subareas of favorable geological conditions based on available data. Step 2 of Phase I will lead to identification of specific regions that are considered for further surface-based geoscientific and geophysical exploration. Potential host rocks are rock salt, clay rock and crystalline rock. As part of the site selection procedure, an overview of the status of the planning and implementation of R and D activities is given. Topics of particular interest are, for example, the adaptation of the maximum temperature of 100 deg. C at the container surface, the impact of long-term climate variations as well as minimally invasive exploration methods. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Turning Normal to Abnormal: Reversing CO 2 /C2–Hydrocarbon Selectivity in HKUST–1

Metal–organic frameworks (MOFs) can efficiently purify hydrocarbons from CO 2 , but their rapid saturation, driven by preferential hydrocarbon adsorption, requires energy-intensive adsorption–desorption processes. To address these challenges, an innovative approach is developed, enabling control over MOF flexibility through densification and defect engineering, resulting in an intriguing inverse CO 2 /C2 hydrocarbon selectivity. Here, in this study, the densification process induces the shearing of the crystal lattice and contraction of pores in a defective CuBTC MOF. These changes have led to a remarkable transformation in selectivity, where the originally hydrocarbon-selective CuBTC MOF becomes CO 2 -selective. The selectivity values for densified CuBTC are significantly reversed when compared to its powder form, with notable improvements observed in CO 2 /C 2 H 6 (4416 vs 0.61), CO 2 /C 2 H 4 (15 vs 0.28), and CO 2 /C 2 H 2 (4 vs 0.2). The densified material shows impressive separation, regeneration, and recyclability during dynamic breakthrough experiments with complex quinary gas mixtures. Simulation studies indicate faster CO 2 passage through the tetragonal structure of densified CuBTC compared to C 2 H 2 . Experimental kinetic diffusion studies confirm accelerated CO 2 diffusion over hydrocarbons in the densified MOF, attributed to its small pore window and minimal interparticle voids. This research introduces a promising strategy for refining existing and future MOF materials, enhancing their separation performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effects of surface species and homogeneous reactions on rates and selectivity in ethane oxidation on oxide catalysts

Selective alkane oxidations on metal oxide catalysts involve complex mechanisms with multiple reactions in series and parallel, different types of reduced and oxidized surface species, and potential contributions from gas-phase reactions. We report kinetics and thermodynamics of elementary steps involved in C 2 H 6 -O 2 reactions on SiO 2 -supported small vanadium oxide domains are determined using density functional theory. These surface reactions together with gas-phase mechanisms are incorporated in kinetic simulations to determine how surface and gaseous reactions interact and contribute to rates and selectivity. The results show that gas-phase reactions within pore volumes in contact with the catalyst contribute significantly to C 2 H 6 activation rates, even at conditions where gas-phase reactions in empty volumes without catalyst are negligible. The majority of C 2 H 6 activations occur on the surface, via H abstraction by vanadium oxo species present at terminal lattice oxygens. The gas-phase activations via H-abstraction by OH radicals also exhibit significant contributions. The reduced centers formed by reactions at vanadium oxo species are re-oxidized rapidly and, therefore, are present in very small concentrations at reaction conditions. The re-oxidation steps lead to the formation of HO 2 radicals and surface peroxo species that are also rapidly consumed and are present in small concentrations. The peroxo species preferentially convert C 2 H 4 to its epoxide product and influence selectivity even at low concentrations. The gas-phase reactions decrease the concentrations of peroxo species and improve selectivity slightly. The effects of reaction conditions and catalyst site density provide further insights into how factors beyond conversions at lattice oxygens influence rates and selectivity in alkane oxidation reactions of significant industrial importance.

42 ENGINEERING↗
DOE OSTI2023

Kinetic Control via Binding Sites within the Confined Space of Metal Metalloporphyrin‐Frameworks for Enhanced Shape‐Selectivity Catalysis

Abstract One striking feature of enzyme is its controllable ability to trap substrates via synergistic or cooperative binding in the enzymatic pocket, which renders the shape‐selectivity of product by the confined spatial environment. The success of shape‐selective catalysis relies on the ability of enzyme to tune the thermodynamics and kinetics for chemical reactions. In emulation of enzyme's ability, we showcase herein a targeting strategy with the substrate being anchored on the internal pore wall of metal‐organic frameworks (MOFs), taking full advantage of the sterically kinetic control to achieve shape‐selectivity for the reactions. For this purpose, a series of binding site‐accessible metal metalloporphyrin‐frameworks (MMPFs) have been investigated to shed light on the nature of enzyme‐mimic catalysis. They exhibit a different density of binding sites that are well arranged into the nanospace with corresponding distances of opposite binding sites. Such a structural specificity results in a facile switch in selectivity from an exclusive formation of the thermodynamically stable product to the kinetic product. Thus, the proposed targeting strategy, based on the combination of porous materials and binding events, paves a new way to develop highly efficient heterogeneous catalysts for shifting selectivity.

Zhang, Weijie↗
DOE OSTI2024

Anomalous Role of Carbon in Pd‐Catalyzed Selective Hydrogenation

Carbonaceous species, including subsurface carbidic carbon and surface carbon, play crucial roles in heterogeneous catalysis. Many reports suggested the importance of subsurface carbon in the selective hydrogenation of alkynes over Pd‐based catalysts. However, the role of surface carbon has been largely overlooked. Here, we demonstrate that subsurface carbon in Pd is not responsible for the selectivity in acetylene hydrogenation. In contrast, the structure of surface carbonaceous species plays a decisive role in hydrogenation selectivity. Electron microscopy and spectroscopy evidence, along with theoretical modelling, reveal that partial graphitization of surface carbonaceous species results in unique spatial confinement of surface reaction intermediates, thus altering the reaction energy landscape in favour of ethylene desorption as opposed to over‐hydrogenation. This mechanism for selectivity control is analogous to enzyme catalysis, where the active centers selectively attract reactants and release products. Similar mechanism may be present in CO/CO 2 hydrogenation and alkane dehydrogenation reactions.

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

Engineering PdAu/CeO 2 Alloy/Oxide Interfaces for Selective Methane‐to‐Methanol Conversion with Water

The direct conversion of methane-to-methanol remains a critical challenge in methane valorization. In this study, we unveil the crucial role of PdAu/CeO 2 catalysts in enabling selective methane transformation under mild conditions, using only water as the sole oxidant. Through a combination of experimental techniques, including XPS and catalytic testing, alongside density functional theory (DFT) calculations, we demonstrate that a Pd 0.3 Au 0.7 /CeO 2 catalyst, which predominantly exposes isolated Pd atoms, achieves remarkable methanol selectivity (∼80%) at 500 K with a 1:1 methane-to-water ratio. While Pd/CeO 2 efficiently activates methane, its tendency for overreaction leads to complete methanol decomposition, thereby limiting selectivity. Alloying Pd with Au on ceria mitigates this over-reactivity, preventing methanol degradation while maintaining sufficient catalytic activity. The PdAu/CeO 2 composite exhibits a synergistic effect: Pd in contact with the ceria support facilitates methane activation and water dissociation, while Au fine-tunes reactivity to promote methanol formation. DFT calculations confirm that isolated Pd sites at the PdAu/CeO 2 interface play a key role in balancing activity and selectivity. This work underscores the importance of alloy/oxide interfaces in controlling selective methane conversion with water and offers valuable insights for designing highly efficient catalysts for methanol synthesis.

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

Computational Discovery of Active and Selective Metal‐Nitrogen‐Graphene Catalysts for Electrooxidation of Water to H 2 O 2

A direct electrosynthesis of H 2 O 2 from either O 2 or H 2 O is an attractive strategy to replace the energy-intensive industrial anthraquinone process. Two-electron water oxidation reaction (2e-WOR) offers several advantages over the oxygen reduction reaction such as better mass transfer due to the absence of gas-phase reactants. However, 2e-WOR is a more challenging and less studied process with only a handful of metal oxides exhibiting reasonable activity/selectivity properties. Herein, we employ density-functional-theory calculations to screen a variety of metal-nitrogen-graphene structures for 2e-WOR. As a consequence of scaling between the adsorption energies of reaction intermediates, we determine a linear relation between selectivities for the first and second reaction steps of 2e-WOR, viz. that if selectivity toward adsorbed OH is improved, then selectivity toward H 2 O 2 at the subsequent step is decreased. We also find that selectivity and activity are linearly scaled in such a way that a higher activity (i.e., a lower overpotential) leads to a lower selectivity for the H 2 O 2 formation step. Based on the obtained results several chemistries, e.g., containing NiN x -C moieties, are predicted to rival the best-performing metal oxides such as ZnO and CaSnO 3 in terms of combination of their activity/selectivity characteristics for 2e-WOR.

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

The Role of Asparagine as a Gatekeeper Residue in the Selective Binding of Rare Earth Elements by Lanthanide‐Binding Peptides

Abstract Lanthanide‐binding tag (LBT) peptides selectively complex lanthanide cations (Ln 3+ ) in their binding pockets and are promising for lanthanide separation. However, designing LBTs that selectively target specific Ln 3+ cations remains a challenge due to limited molecular‐level understanding and control of interactions within the lanthanide‐binding pocket. In this study, we reveal that the N5 asparagine residue acts as a gatekeeper in the binding pocket, resulting in a 100‐fold selectivity for smaller Lu 3+ over larger La 3+ cations. Nuclear magnetic resonance spectroscopy and molecular dynamics simulations show that the N5 residue weakly binds to the larger La 3+ cation, permitting H 2 O molecules inside the pocket. For the smaller Lu 3+ cations, the N5 residue forms an inter‐arm hydrogen bond with the E14 glutamic acid residue, locking the Lu 3+ cation in the pocket and preventing H 2 O infiltration. Mutating the N5 asparagine to a D5 aspartic acid prevents such a hydrogen bond, eliminating the gatekeeping mechanism and precipitously reducing selectivity. The resulting binding affinity to Ln 3+ cations is non‐monotonic but generally increases with cation size. These results suggest a molecular design paradigm: the reduced affinity for larger lanthanides is due to open pocket conformations, while the selectivity of smaller Ln 3+ cations over larger ones is due to the gatekeeping hydrogen bond.

Chemistry↗
DOE OSTI2023

PtCo/MWCNTs Prepared by a Microwave‐assisted Polyol Method for Selective Cinnamaldehyde Hydrogenation

Abstract Using microwave irradiation, PtCo alloy nanoparticles were deposited within a few minutes on COOH‐functionalized MWCNT supports. The obtained catalysts were used for selective hydrogenation of cinnamaldehyde, a reaction whose products are widely used in various fields. In the selective cinnamaldehyde hydrogenation to cinnamyl alcohol, microwave‐prepared catalysts (generically, Pt x Co y ‐MW) outperformed a catalyst prepared by the conventional method (Pt 1 Co 2 ‐con). The highest selective hydrogenation to cinnamyl alcohol, 89%, was obtained using Pt 1 Co 2 ‐MW, while Pt 1 Co 2 ‐con showed a selectivity of 76%. Characterization results confirmed that the microwave prepared samples had a stronger interaction between Pt and Co than that in the Pt 1 Co 2 ‐con sample. The alloyed Co altered the electronic structure of Pt, leading to favorable adsorption of the C=O bond by the lone‐pair electrons of its oxygen atom. Moreover, the Pt 1 Co 2 ‐MW sample showed neglectable change in catalytic performance (e. g., cinnamaldehyde conversion and selective hydrogenation to cinnamyl alcohol) during recycling experiments.

Wang, Kaiying↗
DOE OSTI2021

Modeling of transport in carrier-selective contacts in silicon heterojunction solar cells

High-performance silicon heterojunction (SHJ) solar cells use carrier-selective contact structures based on hydrogentated amorphous Si (a-Si:H) to maximize collection of photogenerated carriers. The high open circuit voltages observed experimentally in SHJ cells require that the carrier-selective contacts provide selectivity and passivation. However, a microscopic understanding of the dynamics of carrier transport through the a-Si layer is currently lacking. In this paper, we explicitly simulate the transport of holes across the a-Si:H(i) layer using a novel kinetic Monte Carlo approach. The hole-selective contact structure investigated in this paper uses p-type doped a-Si:H(p) and intrinsic a-Si:H(i) on an n-type crystalline silicon wafer, where the selectivity is provided by the a-Si:H(p) and the passivation is provided by the a-Si:H(i). However, in addition to the passivation provided by the a-Si:H(i), this layer also creates a potential barrier to the collection of photogenerated holes. There have been experimental studies in the literature that have suggested that multi-phonon processes are the main transport mechanism that assists in the transport of holes across the intrinsic a-Si:H barrier. Simulations presented here show that multi-phonon injection of holes into the a-Si:H(i) layer is the rate limiting step for transport across the a-Si:H(i) layer. Our results indicate that multi-phonon transport is strongly dependent on the electric field at the a-Si:H(i)/c-Si heterointerface as well. Transport simulations presented in this paper are consistent with experimental findings that multi-phonon processes limit transport across the a-Si:H(i) layer and are responsible for photocurrent suppression at the a-Si:H(i)/c-Si heterointerface when these processes are slower than the associated incident hole flux due to photo-excitation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗
DOE OSTI2018

Stochastic Programming Approach for Resource Selection under Demand Uncertainty

Cost-efficient selection and scheduling of a subset of geographically distributed resources to meet the demands of a scientific workflow is a challenging problem. The problem is exacerbated by uncertainties in demand and availability of resources. In this paper, we present a stochastic optimization based framework for robust decision making in the selection of distributed resources over a planning horizon under demand uncertainty. We present a novel two-stage stochastic programming model for resource selection, and implement an L-shaped decomposition algorithm to solve this model. A Sample Average Approximation algorithm is integrated to enable stochastic optimization to solve problems with a large number of scenarios. Using the metric of stochastic solution, we demonstrate up to 30% cost reduction relative to solutions without explicit consideration of demand uncertainty for a 24-month problem. We also demonstrate up to 54% cost reduction relative to a previously developed solution for a 36-month problem. We further argue that the composition of resources selected is superior to solutions computed without explicit consideration of uncertainties. Given the importance of resource selection and scheduling of complex scientific workflows, especially in the context of commercial cloud computing, we believe that our novel stochastic programming framework will benefit many researchers as well as users of distributed computing resources.

scientific workflows, task scheduling, optimizatio↗
DOE OSTI2013

Dense Accumulation of Lipiodol Emulsion in Hepatocellular Carcinoma Nodule during Selective Balloon-occluded Transarterial Chemoembolization: Measurement of Balloon-occluded Arterial Stump Pressure

Purpose. To reveal the mechanism of dense accumulation of lipiodol emulsion (LE) in hepatocellular carcinoma (HCC) during selective balloon-occluded transarterial chemoembolization (B-TACE). Methods. Balloon-occluded arterial stump pressure (BOASP) at the embolization portion was measured during selective B-TACE for 43 nodules in 42 patients. Fluoroscopy and digital subtraction angiography were prospectively observed during selective B-TACE to note whether dense LE accumulation in HCC occurred. The LE concentration ratio of HCC to embolized liver parenchyma (LECHL ratio) was also calculated for each treatment on the basis of the computed tomographic scan obtained immediately after selective B-TACE. The relationships between degree of LE accumulation and the BOASP, as well as the LECHL ratio, were analyzed. Results. Arterial flow beyond the catheter tip was maintained even after balloon inflation. In 39 of 43 treatments, LE inflow into the nontumorous liver parenchyma ceased immediately after LE droplets were filled in arteries of the nontumorous liver parenchyma while LE inflow into the HCC nodule continued (group 1). More dense LE accumulation in HCC nodule was obtained in these 39 treatments. In four treatments, LE inflow both into the nontumorous liver parenchyma and into the HCC nodule continued, and no dense LE accumulation in HCC nodule was observed (group 2). In these four treatments, thick anastomotic vessels with collateral artery were noted. The BOASP in group 1 was (mean {+-} SD) 33.8 {+-} 12.8 mmHg (range 13-64 mmHg) and that in group 2 was 92.3 {+-} 7.4 mmHg (range 83-100 mmHg). There was a statistically significant difference in BOASP between groups (p = 0.00004, Welch's t test). The LECHL ratio in group 1 was 18.3 {+-} 13.9 (range 2.9-54.2) and that in group 2 was 2.6 {+-} 1.1 (range 1.7-4.2). There was a statistically significant difference in the LECHL ratio between the groups (p = 0.000034, Welch's t test). Conclusion. Selective B-TACE induced dense LE accumulation in HCC nodules in 39 (91 %) of 43 treatments in which BOASP was 64 mmHg or less.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Highly Selective Detection of Cr{sup 3+} Ion with Colorimetric & Fluorescent Response Via Chemodosimetric Approach in Aqueous Medium

So far, very few numbers of chemosensors for Cr{sup 3+} ion have been reported. However, the main drawback of reported receptors are the lack of selectivity and other trivalent cations such as Fe{sup 3+}, Al{sup 3+} and anions like F{sup −} and {sup −}OAc frequently interfere with such assays. This paper present the synthesis, characterization & sensor studies of Schiff base containing naphthalene moiety which selectively detect Cr{sup 3+} ion by chemodosimetric approach. Using FT-IR, {sup 1}H NMR, {sup 13}C NMR and ESI mass spectroscopic techniques the probe was characterized. This receptor exhibit more selectivity and sensitivity towards Cr{sup 3+} than other divalent and trivalent cations like Mn{sup 2+}, Zn{sup 2+}, Co{sup 2+}, Ni{sup 2+}, Cd{sup 2+}, Cu{sup 2+}, Hg{sup 2+}, Fe{sup 3+}, and Al{sup 3+} ions. After the addition of chromium ion the receptor get change from yellow to colorless in aqueous medium. But no color change was observed on the addition of other metal ions. Using UV-Vis and PL studies, it was confirmed that the selective hydrolysis of imine group of receptor by Cr{sup 3+} ions takes place with high fluorescence enhancement that is corresponding to 1-naphthylamine. Receptor acts as selective chemodosimeter for Cr{sup 3+} ions with 2:1 stoichiometry and micro molar detection limit. This chemodosimetric approach was applied successfully for bio-imaging of HeLa cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗