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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Atom-at-a-Time Radioactive Molecule Identification: Looking toward Studies of Superheavy Elements

The chemical behavior of superheavy elements (SHEs, Z > 103) remains poorly understood. Their chemical properties are expected to deviate from established trends, challenging the predictive power of the periodic table. To investigate these elements experimentally, they must first be synthesized through nuclear reactions and then quickly subjected to chemical studies before they decay. Given the low production rates of these reactions and the need for measurements on an atom-at-a-time basis, innovative techniques are needed. Here, to address these challenges, a novel gas-phase chemistry method has been developed at Lawrence Berkeley National Laboratory, utilizing the Berkeley Gas-filled Separator and FIONA. This technique enables the production, identification, and study of molecular species formed by SHEs. As a proof of concept, we present measurements on the formation and identification of 151,152 HoO + molecules, demonstrating the capability to study the production of radioactive molecules under controlled conditions and directly identify them via their mass-to-charge ratio. These measurements validate the effectiveness of this technique for low-statistics SHE studies, highlighting the potential of this approach to ignite the next generation of experimental SHE chemistry research, offering a path to re-evaluate SHE placement on the periodic table.

Chemistry↗
DOE OSTI2019

Constructing a Tandem Mass Spectral Library for Forensic Ricin Identification

Ricin, a protein found in castor seeds, is a lethal toxin that is designated as a category 2 select agent. Because castor seeds are easy to obtain and the toxin can be easily extracted, cases of attempted ricin poisoning are relatively common. A shotgun proteomics method for ricin identification has recently been developed (manuscript in preparation), in which ricin peptides are identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by proteomics database search, and peptide-spectrum matches are verified and compared to standard spectra by a human expert. To make this process more reproducible, objective, and high-throughput, we have created a ricin spectral library for peptide identification to supplement the human review step. To construct these spectral libraries, two pure ricin samples (from a proposed standard reference material) and crude castor seed extracts were digested with trypsin and analyzed using a standard shotgun LC-MS/MS protocol. Spectral libraries were created from the filtered search results from four database search tools. The library was then used in a search using SpectraST on samples from castor seeds. Analysis showed that the spectral library search resulted in more peptides identified from crude castor seed samples compared to MS-GF+ and Sequest plus Percolator. These results suggest that computational comparison of putative ricin peptide spectra to library spectra can be an effective method of confirming the presence of ricin, and that spectral library search may be suitable to augment the more manual and subjective aspects of the currently recommended human expert review.

Spectral Library, Ricin, forensic, proteomic↗
DOE OSTI2023

Infrared Signatures for Phase Identification in Hafnium Oxide Thin Films

Phase identification in HfO 2 -based thin films is a prerequisite to understanding the mechanisms stabilizing the ferroelectric phase in these materials, which hold great promise in next-generation non-volatile memory and computing technology. While grazing-incidence X-ray diffraction is commonly employed for this purpose, it has difficulty unambiguously differentiating between the ferroelectric phase and other metastable phases that may exist due to similarities in the d-spacings, their low intensities, and the overlapping of reflections. Infrared signatures provide an alternative route. However, their use in phase identification remains limited because phase control has overwhelmingly been accomplished via substituents, thereby convoluting infrared signatures between the substituent and the phase changes they induce. Herein, we report the infrared optical responses of three undoped hafnium oxide films where annealing conditions have been used to create films consisting primarily of the ferroelectric polar orthorhombic Pca2 1 , antipolar orthorhombic Pbca, and monoclinic P2 1 /c phases, as was confirmed via transmission electron microscopy (TEM), UVvisible optical properties, and electrical property measurements. Vibrational signatures acquired from synchrotron nano-Fourier transform infrared spectroscopy (nano-FTIR) are shown to be capable of differentiating between the phases in a non-destructive, rapid, and nanoscale manner. The utility of nano-FTIR is illustrated for a film exhibiting an antiferroelectric polarization response. In this sample, it is proven that this behavior results from the Pbca phase rather than the often-cited tetragonal phase. Here, by demonstrating that IRspectroscopy can unambiguously distinguish phases in this material, this work establishes a tool needed to isolate the factors dictating ferroelectric phase stability in HfO 2 -based materials.

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

Photoinduced Heterocyclic Ring Opening of Furfural: Distinct Open-Chain Product Identification by Ultrafast X-ray Transient Absorption Spectroscopy

The ultraviolet-induced photochemistry of five-membered heterocyclic rings often involves ring opening as a prominent excited-state relaxation pathway. The identification of this particular photoinduced mechanism, however, presents a challenge for many experimental methods. We show that femtosecond X-ray transient absorption spectroscopy at the carbon K-edge (~284 eV) provides core-to-valence spectral fingerprints that enable the unambiguous identification of ring-opened isomers of organic heterocycles. The unique differences in the electronic structure between a carbon atom bonded to the oxygen in the ring versus a carbon atom set free of the oxygen in the ring-opened product are readily apparent in the X-ray spectra. Ultrafast ring opening via C-O bond fission occurs within ~350 fs in 266-nm photoexcited furfural, as evidenced by fingerprint core (carbon 1s) electronic transitions into a nonbonding orbital of the open-chain carbene intermediate at 283.3 eV. The lack of recovery of the 1sπ* ground-state depletion in furfural at 286.4 eV indicates that internal conversion to the ground state is a minor channel. These experimental results, augmented by recent advances in the generation of isolated attosecond pulses at the carbon K-edge, will pave the way for probing ring-opened conical intersection dynamics in the future.

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

ESI-MS Identification of the Cationic Phosphine-Ligated Gold Clusters Au1-Au22: Insight into the Gold-Ligand Ratio and Abundance of Larger Clusters

Triphenylphosphine (PPh3)-ligated gold clusters offer promising potential applications due to their relative ease of synthesis and usefulness in forming advanced cluster architectures. While previous studies reported cationic PPh3-ligated gold clusters with core sizes of Au1 - Au4, Au6 - Au11, and Au¬13 - Au14, there has not been definitive identification by mass spectrometry of larger clusters in the Au12 - Au25¬ range. Herein, we survey a polydisperse solution of cationic PPh3-ligated gold clusters using high mass-resolution (M/?M = 60,000) electrospray ionization mass spectrometry (ESI-MS). To improve the sensitivity and mass resolution of larger clusters for unambiguous identification, we increased the number of scan averages and reduced the range of mass collection windows to 200 m/z, thereby mitigating potential mass and ion abundance bias resulting from smaller “building block” gold clusters and other solution components present in higher abundance. In addition to the previously reported clusters, we identified several new species including Au5(PPh3)5+, Au12(PPh3)9HCl2+, Au15(PPh3)9Cl2+, Au16(PPh3)10Cl22+, Au17(PPh3)113+, Au18(PPh3)102+, Au19(PPh3)10Cl2+, Au20(PPh3)12H33+, Au21(PPh3)10Cl2+, and Au22(PPh3)10Cl22+, indicating that a full range of clusters between Au1 - Au22 may be observed in a single polydisperse solution. Considering all of the observed clusters, our findings provide evidence that the “magic number” icosahedral Au13 may be the transition point in cluster growth between smaller clusters, exhibiting a 1:1 gold-to-ligand ratio, and larger clusters, wherein subsequent gold atoms are added to the core without an equal number of accompanying ligands. Our method demonstrates that reducing the range of m/z collection windows and increasing the number of scan averages can improve instrument sensitivity for cationic gold clusters and enable a more complete survey of polydisperse solutions, thereby providing new insights to guide and validate the results of other characterization methods and theoretical calculations. This work was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. MH acknowledges support from the DOE Science Undergraduate Laboratory Internship (SULI) program. HH acknowledges support from the DOE Office of Workforce Development for Teachers and Scientist (WDTS) under the Visiting Faculty Program (VFP). This work was performed using EMSL, a national scientific user facility sponsored by the DOE's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multiprogram national laboratory operated for DOE by Battelle.

Hewitt, Michael↗
DOE OSTI2014

Maximizing Diversity from a Kinase Screen: Identification of Novel and Selective pan-Trk Inhibitors for Chronic Pain

We have identified several series of small molecule inhibitors of TrkA with unique binding modes. The starting leads were chosen to maximize the structural and binding mode diversity derived from a high throughput screen of our internal compound collection. These leads were optimized for potency and selectivity employing a structure based drug design approach adhering to the principles of ligand efficiency to maximize binding affinity without overly relying on lipophilic interactions. This endeavor resulted in the identification of several small molecule pan-Trk inhibitor series that exhibit high selectivity for TrkA/B/C versus a diverse panel of kinases. We have also demonstrated efficacy in both inflammatory and neuropathic pain models upon oral dosing. Herein we describe the identification process, hit-to-lead progression, and binding profiles of these selective pan-Trk kinase inhibitors.

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

Identification and Characterization of Dust Source Regions Across North Africa and the Middle East Using MISR Satellite Observations

Abstract Motivated by limitations in current satellite‐based dust source identification techniques, this study examines dust emissions and concentrations over North Africa and the Middle East during 2000–2016 by analyzing stereo and optical products from the Multiangle Imaging SpectroRadiometer instrument on the National Aeronautics and Space Administration polar‐orbiting Terra satellite. Based on the occurrence of fast‐moving, near‐surface dust plumes from the Multiangle Imaging SpectroRadiometer cloud motion vector product, dust sources in the study region are identified in geographical depressions, including the Bodélé Depression, which represents the leading source. The West African El Djouf desert generates substantial dust emissions, which are typically underestimated by aerosol loading‐based dust source identifications. In response to local vegetation cover anomalies, dust emissions and concentrations increased at 15% year −1 over the Middle East and decreased at 12% year −1 over the central Sahel during 2001–2013 but partly recovered toward their climatological means afterward.

Yu, Yan↗
DOE OSTI2018

Using both qualitative and quantitative data in parameter identification for systems biology models

Abstract In systems biology, qualitative data are often generated, but rarely used to parameterize models. We demonstrate an approach in which qualitative and quantitative data can be combined for parameter identification. In this approach, qualitative data are converted into inequality constraints imposed on the outputs of the model. These inequalities are used along with quantitative data points to construct a single scalar objective function that accounts for both datasets. To illustrate the approach, we estimate parameters for a simple model describing Raf activation. We then apply the technique to a more elaborate model characterizing cell cycle regulation in yeast. We incorporate both quantitative time courses (561 data points) and qualitative phenotypes of 119 mutant yeast strains (1647 inequalities) to perform automated identification of 153 model parameters. We quantify parameter uncertainty using a profile likelihood approach. Our results indicate the value of combining qualitative and quantitative data to parameterize systems biology models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Carbene-based Difluoromethylation of Bisphenols: Application to the Instantaneous Tagging of Bisphenol A in Spiked Soil for Its Detection and Identification by Electron Ionization Gas Chromatography-Mass Spectrometry

The rapid and efficient difluoromethylation of a panel of eleven bisphenols (BPs) for their enhanced detection and identification by Electron-Ionization Gas Chromatography-Mass Spectrometry (EI-GC-MS) is presented. The derivatization employs the inexpensive, environmentally benign agent diethyl (bromodifluoromethyl) phosphonate (DBDFP) as a difluorocarbene-generating species that converts the BPs into bis-difluoromethylated ethers that can be detected and identified by GC-MS means. Key attributes of the protocol include its extreme rapidity (30 seconds) at ambient temperature, high specificity for BPs amidst other alcohol-containing analytes, and its biphasic nature that allows for its convenient adaptation to the analysis of BPs in organic as well as aqueous matrices. The protocol furnishes stable, novel BP ethers armed with a total of four fluorine atoms for their subsequent analysis by EI-GC-MS. Furthermore, each derivatized bisphenol exhibits unique retention times vastly different from their native counterparts leading to their unequivocal identification. The effectiveness and robustness of the developed methodology was applied to the tagging of the most famous member of this family of compounds, bisphenol-A (BPA), when spiked (at 1 μg.g –1 concentration) in the physically and compositionally complex Nebraska EPA standard soil. The method detection limit (MDL) for the bis-difluoromethylated BPA was determined to be 0.01 μg.mL –1 . The bis-difluoromethylated BPA was conveniently detected on the organic layers from the biphasic, derivatized mixtures, highlighting the protocol’s practicality and utility in the rapid, qualitative detection of this endocrine disruptor during environmental analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

SeqTU: A web server for identification of bacterial transcription units

A transcription unit (TU) consists of K ≥ 1 consecutive genes on the same strand of a bacterial genome that are transcribed into a single mRNA molecule under certain conditions. Their identification is an essential step in elucidation of transcriptional regulatory networks. We have recently developed a machine-learning method to accurately identify TUs from RNA-seq data, based on two features of the assembled RNA reads: the continuity and stability of RNA-seq coverage across a genomic region. While good performance was achieved by the method on Escherichia coli and Clostridium thermocellum , substantial work is needed to make the program generally applicable to all bacteria, knowing that the program requires organism specific information. A web server, named SeqTU , was developed to automatically identify TUs with given RNA-seq data of any bacterium using a machine-learning approach. The server consists of a number of utility tools, in addition to TU identification, such as data preparation, data quality check and RNA-read mapping. SeqTU provides a user-friendly interface and automated prediction of TUs from given RNA-seq data. Furthermore, the predicted TUs are displayed intuitively using HTML format along with a graphic visualization of the prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗
DOE OSTI2016

Testing contamination source identification methods for water distribution networks

In the event of contamination in a water distribution network (WDN), source identification (SI) methods that analyze sensor data can be used to identify the source location(s). Knowledge of the source location and characteristics are important to inform contamination control and cleanup operations. Various SI strategies that have been developed by researchers differ in their underlying assumptions and solution techniques. The following manuscript presents a systematic procedure for testing and evaluating SI methods. The performance of these SI methods is affected by various factors including the size of WDN model, measurement error, modeling error, time and number of contaminant injections, and time and number of measurements. This paper includes test cases that vary these factors and evaluates three SI methods on the basis of accuracy and specificity. The tests are used to review and compare these different SI methods, highlighting their strengths in handling various identification scenarios. These SI methods and a testing framework that includes the test cases and analysis tools presented in this paper have been integrated into EPA’s Water Security Toolkit (WST), a suite of software tools to help researchers and others in the water industry evaluate and plan various response strategies in case of a contamination incident. Lastly, a set of recommendations are made for users to consider when working with different categories of SI methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

The identification and nature of bound exciton I-line PL systems in ZnO

The chemical identification of donor bound excitons in ZnO has been studied using radioactive ions. Implantations of {sup 117}Ag - which decays to radioactive Cd and In - have enabled the identification of the I{sub 2} optical feature as being the ionized donor counterpart of I{sub 9}, one of the most prominent optical features in the photoluminescence spectrum of ZnO. Both of these lines are consistent with In occupying a Zn site.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Performance study of LMS based adaptive algorithms for unknown system identification

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

A review for identification of initiating events in event tree development process on nuclear power plants

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logic model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Radioisotope identification method for poorly resolved gamma-ray spectrum of nuclear security concern

Gamma-ray signal can be used as a fingerprint for radioisotope identification. In the context of radioactive and nuclear materials security at the border control point, the detection task can present a significant challenge due to various constraints such as the limited measurement time, the shielding conditions, and the noise interference. This study proposes a novel method to identify the signal of one or several radioisotopes from a poorly resolved gamma-ray spectrum. In this method, the noise component in the raw spectrum is reduced by the wavelet decomposition approach, and the removal of the continuum background is performed using the baseline determination algorithm. Finally, the identification of radioisotope is completed using the matrix linear regression method. The proposed method has been verified by experiments using the poorly resolved gamma-ray signals from various scenarios including single source, mixing of natural uranium with five of the most common industrial radioactive sources (57Co, 60Co, 133Ba, 137Cs, and 241Am). The preliminary results show that the proposed algorithm is comparable with the commercial method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

IDENTIFICATION OF GALAXY CLUSTER SUBSTRUCTURES WITH THE CAUSTIC METHOD

We investigate the power of the caustic technique for identifying substructures of galaxy clusters from optical redshift data alone. The caustic technique is designed to estimate the mass profile of galaxy clusters to radii well beyond the virial radius, where dynamical equilibrium does not hold. Two by-products of this technique are the identification of the cluster members and the identification of the cluster substructures. We test the caustic technique as a substructure detector on two samples of 150 mock redshift surveys of clusters; the clusters are extracted from a large cosmological N-body simulation of a ΛCDM model and have masses of M{sub 200}∼10{sup 14}h{sup −1}M{sub ⊙} and M{sub 200}∼10{sup 15}h{sup −1}M{sub ⊙} in the two samples. We limit our analysis to substructures identified in the simulation with masses larger than 10{sup 13}h{sup −1}M{sub ⊙}. With mock redshift surveys with 200 galaxies within 3R{sub 200}, (1) the caustic technique recovers ∼30%–50% of the real substructures, and (2) ∼15%–20% of the substructures identified by the caustic technique correspond to real substructures of the central cluster, the remaining fraction being low-mass substructures, groups or substructures of clusters in the surrounding region, or chance alignments of unrelated galaxies. These encouraging results show that the caustic technique is a promising approach for investigating the complex dynamics of galaxy clusters.

79 ASTRONOMY AND ASTROPHYSICS↗