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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Intense cavitation-assisted electric discharge as a promising tool for water treatment

This study investigates interrelations between one-electrode Cavitation-Assisted Electric Discharge (CAED), two-electrode CAED, and recently discovered Intense CAED (I-CAED). The one-electrode CAED is a self-triggered nanosecond discharge with pulse energy in the micro-Joule range, which can be generated even by a DC voltage. I-CAED consists of a non-equilibrium part within a low-pressure cavitating region and a micro-spark traversing a liquid film. We hypothesize that CAED propagates from the high-voltage electrode as an ionization wave through bubbles of saturated vapor. Subsequently, the streamer-like discharges in the bubbles may form a continuous plasma channel. Inside the cavitating region, the plasma is strongly non-equilibrium, providing an ideal environment for generating chemically unstable species such as hydrogen peroxide (H 2 O 2 ). Plasma of I-CAED spark is characterized by high electron density and near-thermal equilibrium, emitting a continuous ultraviolet spectrum. The combination of these different discharge parts makes I-CAED in water a highly effective tool for the Advanced Oxidation Process, particularly in water disinfection. Experimentally demonstrated Electric Energy per Order value for disinfection of E. coli-contaminated water is as low as 0.135 ± 0.035 kWh/m 3 /order. Estimates show that the implementation of “dry electrodes” configuration reduces the erosion rate of the electrode material by at least one order of magnitude. Spectral analysis reveals that the continuum emission generated by I-CAED in proximity to metal electrodes deviates from the spectra of discharges spatially decoupled from the electrodes. We assume that this spectral divergence is attributable to blackbody-like emission originating from metallic nanoparticles form during the electrode's erosion process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Polaron and Spin Dynamics in Organic–Inorganic Lead Halide Perovskite Nanocrystals

Long-lived carrier population and spin-based behavior in lead halide perovskite nanocrystals (NCs) are very interesting for implementing photovoltaic devices with efficiencies exceeding the Shockley–Queisser limit and quantum information processing, respectively. However, a comprehensive understanding of polaron-mediated charge carrier interactions and an accurate description of the spin-polarized states for spintronics are still lacking. Herein, the carrier and spin interactions are studied under controlled conditions in FAPbI 3 and Cs 0.01 FA 0.99 Pb(Br 0.11 I 0.89 ) 3 NCs through ultrafast transient absorption (TA) spectroscopy. At early timescales, TA spectrum shows an asymmetric derivative feature originating from the hot carrier-induced spectral redshift in FAPbI 3 NCs (55 ± 3 meV) and Cs0.01FA0.99Pb(Br0.11I0.89)3 NCs (54 ± 2 meV) at the bandedges that stabilizes to 9 ± 1 and 11 ± 2 meV, respectively, at 1 ps due to the polaron formation. The kinetic analysis indicates that the polaron populations in FAPbI3 and Cs 0.01 FA 0.99 Pb(Br 0.11 I 0.89 ) 3 NCs decay with an average lifetime of 657 ± 34 and 532 ± 28 ps, respectively. The circular polarization-resolved TA reveals that polaron formation can control spin relaxation in NCs, thus providing a powerful tool to explore the development of their prospective applications in spintronics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Tianlai dish pathfinder array: design, operation, and performance of a prototype transit radio interferometer

ABSTRACT The Tianlai Dish Pathfinder Array is a radio interferometer designed to test techniques for 21 cm intensity mapping in the post-reionization universe as a means for measuring large-scale cosmic structure. It performs drift scans of the sky at constant declination. We describe the design, calibration, noise level, and stability of this instrument based on the analysis of about 5% of 6200 h of on-sky observations through 2019 October. Beam pattern determinations using drones and the transit of bright sources are in good agreement, and compatible with electromagnetic simulations. Combining all the baselines, we make maps around bright sources and show that the array behaves as expected. A few hundred hours of observations at different declinations have been used to study the array geometry and pointing imperfections, as well as the instrument noise behaviour. We show that the system temperature is below 80 K for most feed antennas and that noise fluctuations decrease as expected with integration time, at least up to a few hundred seconds. Analysis of long integrations, from 10 nights of observations of the North Celestial Pole (NCP), yielded visibilities with amplitudes of 20–30 mK, consistent with the expected signal from the NCP radio sky with ${\lt}10\,$ mK precision for 1 MHz × 1 min binning. Hi-pass filtering the spectra to remove smooth spectrum signal yields a residual consistent with zero signal at the $0.5\,$ mK level.

(cosmology:) large-scale structure of the Universe↗
DOE OSTI2025

A Measurement of the Largest-scale CMB E -mode Polarization with CLASS

We present measurements of large-scale cosmic microwave background E-mode polarization from the Cosmology Large Angular Scale Surveyor 90 GHz data. Using 115 det-yr of observations collected through 2024 with a variable-delay polarization modulator, we achieved a polarization sensitivity of 82 μK arcimin, comparable to Planck at similar frequencies (100 and 143 GHz ). The analysis demonstrates effective mitigation of systematic errors and addresses challenges to large-angular-scale power recovery posed by time-domain filtering in maximum-likelihood map-making. A novel implementation of the pixel-space transfer matrix is introduced, which enables efficient filtering simulations and bias correction in the power spectrum using the quadratic cross-spectrum estimator. Overall, we achieved an unbiased time-domain filtering correction to recover the largest angular scale polarization, with the only power deficit, arising from map-making nonlinearity, being characterized as <3%. Through cross-correlation with Planck, we detected the cosmic reionization at 99.4% significance and measured the reionization optical depth τ = $0.053^{+0.018}_{-0.019}$, marking the first ground-based attempt at such a measurement. At intermediate angular scales (ℓ > 30), our results, both independently and in cross-correlation with Planck, remain fully consistent with Planck’s measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

XA21-mediated resistance to Xanthomonas oryzae pv. oryzae is dose dependent

The rice receptor kinase XA21 confers broad-spectrum resistance to Xanthomonas oryzae pv. oryzae ( Xoo ), the causal agent of rice bacterial blight disease. To investigate the relationship between the expression level of XA21 and resulting resistance, we generated independent HA-XA21 transgenic rice lines accumulating the XA21 immune receptor fused with an HA epitope tag. Whole-genome sequence analysis identified the T-DNA insertion sites in sixteen independent T0 events. Further, through quantification of the HA-XA21 protein and assessment of the resistance to Xoo strain PXO99 in six independent transgenic lines, we observed that XA21-mediated resistance is dose dependent. In contrast, based on the four agronomic traits quantified in these experiments, yield is unlikely to be affected by the expression level of HA-XA21 . These findings extend our knowledge of XA21-mediated defense and contribute to the growing number of well-defined genomic landing pads in the rice genome that can be targeted for gene insertion without compromising yield.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Aging power spectrum of membrane protein transport and other subordinated random walks

Single-particle tracking offers detailed information about the motion of molecules in complex environments such as those encountered in live cells, but the interpretation of experimental data is challenging. One of the most powerful tools in the characterization of random processes is the power spectral density. However, because anomalous diffusion processes in complex systems are usually not stationary, the traditional Wiener-Khinchin theorem for the analysis of power spectral densities is invalid. Here, we employ a recently developed tool named aging Wiener-Khinchin theorem to derive the power spectral density of fractional Brownian motion coexisting with a scale-free continuous time random walk, the two most typical anomalous diffusion processes. Using this analysis, we characterize the motion of voltage-gated sodium channels on the surface of hippocampal neurons. Our results show aging where the power spectral density can either increase or decrease with observation time depending on the specific parameters of both underlying processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predicting Drug Effects from High-dimensional Asymmetric Drug Data Sets using Graph Neural Networks: A Comprehensive Analysis of Multi-target Drug Effect Prediction

Graph neural networks (GNNs) have emerged as one of the most effective Machine learning (ML) techniques for drug effect prediction from drug molecular graphs. Despite having immense potential, GNN models lack performance when using data sets that contain high dimensional asymmetrically co-occurrent drug effects as targets with complex correlations between them. Training individual learning models for each drug effect and incorporating every prediction result for a wide spectrum of drug effects is beyond practicality. Such an implication provides a testbed to address this challenge as multi-target prediction problems, aiming to predict all drug effects at a time. We develop standard and hybrid graph neural networks (GNNs)to perform two separate tasks that are multi-regression for continuous values and multi-label classification for categorical values contained in our data sets. Since this step makes the target data even more sparse and introduces asymmetric label co-occurrence, the learning of multi-label classification models becomes difficult and heavily impacts the GNN's performance. To address these challenges, we propose a new data oversampling technique to improve multi-label classification performances on all the given imbalanced molecular graph data sets. Using the technique, we improve the data imbalance ratio of the drug effects better than before while protecting the data set's integrity. Finally, we evaluate multi-label classification performance using the best-performant hybrid GNN model on all the oversampled data sets obtained from the proposed oversampling technique. These results outperform those of other ML models including GNN models when they are trained on the original data sets or oversampled data sets using MLSMOTE (a well-known oversampling technique) in all evaluation metrics precision, recall, and F1 score by a significant margin.

Bose, Avishek [ORNL]↗
DOE OSTI2021

Electron-ion coincidence measurements of molecular dynamics with intense X-ray pulses

Molecules can sequentially absorb multiple photons when irradiated by an intense X-ray pulse from a free-electron laser. If the time delay between two photoabsorption events can be determined, this enables pump-probe experiments with a single X-ray pulse, where the absorption of the first photon induces electronic and nuclear dynamics that are probed by the absorption of the second photon. Here we show a realization of such a single-pulse X-ray pump-probe scheme on N 2 molecules, using the X-ray induced dissociation process as an internal clock that is read out via coincident detection of photoelectrons and fragment ions. By coincidence analysis of the kinetic energies of the ionic fragments and photoelectrons, the transition from a bound molecular dication to two isolated atomic ions is observed through the energy shift of the inner-shell electrons. Via ab-initio simulations, we are able to map characteristic features in the kinetic energy release and photoelectron spectrum to specific delay times between photoabsorptions. In contrast to previous studies where nuclear motions were typically revealed by measuring ion kinetics, our work shows that inner-shell photoelectron energies can also be sensitive probes of nuclear dynamics, which adds one more dimension to the study of light-matter interactions with X-ray pulses.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Gravitational wave background from mergers of large primordial black holes

The Peters formula, which tells how the coalescence time of a binary system emitting gravitational radiation is determined by the initial size and shape of the elliptic orbit, is often used in estimating the merger rate of primordial black holes and the gravitational wave background from the mergers. Valid as it is in some interesting scenarios, such as the analysis of the LIGO-Virgo events, the Peters formula fails to describe the coalescence time if the orbital period of the binary exceeds the value given by the formula. This could underestimate the event rate of mergers that occur before the cosmic time t ~ 10 13 s. As a result, the energy density spectrum of the gravitational wave background could develop a peak, which is from mergers occurring at either t ~ 10 13 s (for black holes with mass M ≳ 10 8 M ⊙ ) or t ~ 10 26 (M/M ⊙ ) -5/3 s (for 10 5 M ⊙ ≲ M ≲ 10 8 M ⊙ ). This can be used to constrain the fraction of dark matter in primordial black holes (denoted by f) if potential probes (such as SKA and U-DECIGO) do not discover such a background, with the result f ≲ 10 -6 –10 -4 for the mass range 10– 10 9 M ⊙ . Finally, we then consider the effect of mass accretion onto primordial black holes at redshift z ~ 10, and find that the merger rate could drop significantly at low redshifts. The spectrum of the gravitational wave background thus gets suppressed at the high-frequency end. This feature might be captured by future detectors such as ET and CE for initial mass M = Script $\mathcal{O}$(10–100) M ⊙ with f ≳ 10 -4 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dynamics of long-lived (axionic) domain walls and its cosmological implications

Here, we perform an updated analysis on a long-lived domain wall (DW) network, which may apply to a broad class of axion models. By simulating an axion-like scalar field on a 3D lattice and fitting an analytical model for the DW evolution, we identify the leading energy loss mechanisms of the DWs and compute the spectrum of axions emitted from the network. The contribution from the DWs to axion-like dark matter (DM) density is derived, with viable parameter space given. The application to both QCD axions and general axion-like particles (ALPs) is considered. Due to the new approaches taken, while our results bear consistency with earlier literature, notable discrepancies are also revealed, such as the specifics about DW decay rate which impacts the prediction for DM abundance, which may have a profound impact on axion phenomenology at large.

Cosmic strings↗
DOE OSTI2021

Adaptive machine learning for time-varying systems: low dimensional latent space tuning

Machine learning (ML) tools such as encoder-decoder convolutional neural networks (CNN) can represent incredibly complex nonlinear functions which map between combinations of images and scalars. For example, CNNs can be used to map combinations of accelerator parameters and images which are 2D projections of the 6D phase space distributions of charged particle beams as they are transported between various particle accelerator locations. Despite their strengths, applying ML to time-varying systems, or systems with shifting distributions, is an open problem, especially for large systems for which collecting new data for re-training is impractical or interrupts operations. Particle accelerators are one example of large time-varying systems for which collecting detailed training data requires lengthy dedicated beam measurements which may no longer be available during regular operations. We present a novel method of adaptive ML for time-varying systems. Our approach is to map very high (N ≈ 100k) dimensional inputs (a combination of scalar parameters and images) into the low dimensional (N ≈ 2) latent space at the output of the encoder section of an encoder-decoder CNN. We then actively tune the low dimensional latent space-based representation of complex system dynamics by the addition of an adaptively tuned feedback vector directly before the decoder sections builds back up to our image-based high-dimensional phase space density representations. This method allows us to learn correlations within and to quickly tune the characteristics of incredibly large parameter space systems and to track their evolution in real time based on feedback without massive new data sets for re-training. We demonstrate that our method can accurately predict and track the phase space of charged particle beams at various locations in a particle accelerator by adaptively adjusting in real-time while the unknown input beam distribution of the accelerator is changing in shape, charge, and offset and while the RF system of the accelerator itself is also changing in an unpredictable way. For FACET-II we demonstrate that such an approach has the potential to use transverse deflecting cavity and energy spread spectrum beam measurements to accurately predict 2D projections of the 6D phase space of the electron beam at the plasma wakefield acceleration interaction point where such diagnostics are unavailable.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the BAO and growth rate of structure of the luminous red galaxy sample from the anisotropic power spectrum between redshifts 0.6 and 1.0

ABSTRACT We analyse the clustering of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 luminous red galaxy sample (DR16 eBOSS LRG) in combination with the high redshift tail of the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey Data Release 12 (DR12 BOSS CMASS). We measure the redshift space distortions (RSD) and also extract the longitudinal and transverse baryonic acoustic oscillation (BAO) scale from the anisotropic power spectrum signal inferred from 377 458 galaxies between redshifts 0.6 and 1.0, with the effective redshift of zeff = 0.698 and effective comoving volume of $2.72\, {\rm Gpc}^3$. After applying reconstruction, we measure the BAO scale and infer DH(zeff)/rdrag = 19.30 ± 0.56 and DM(zeff)/rdrag = 17.86 ± 0.37. When we perform an RSD analysis on the pre-reconstructed catalogue on the monopole, quadrupole, and hexadecapole we find, DH(zeff)/rdrag = 20.18 ± 0.78, DM(zeff)/rdrag = 17.49 ± 0.52 and fσ8(zeff) = 0.454 ± 0.046. We combine both sets of results along with the measurements in configuration space and report the following consensus values: DH(zeff)/rdrag = 19.77 ± 0.47, DM(zeff)/rdrag = 17.65 ± 0.30 and fσ8(zeff) = 0.473 ± 0.044, which are in full agreement with the standard ΛCDM and GR predictions. These results represent the most precise measurements within the redshift range 0.6 ≤ z ≤ 1.0 and are the culmination of more than 8 yr of SDSS observations.

Gil-Marín, Héctor↗
DOE OSTI2021

Searching for axionlike particles from core-collapse supernovae with Fermi LAT’s low-energy technique

Light axionlike particles (ALPs) are expected to be abundantly produced in core-collapse supernovae (CCSNe), resulting in a ~ 10 -second long burst of ALPs. These particles subsequently undergo conversion into gamma rays in external magnetic fields to produce a long gamma-ray burst (GRB) with a characteristic spectrum peaking in the 30–100-MeV energy range. At the same time, CCSNe are invoked as progenitors of ordinary long GRBs, rendering it relevant to conduct a comprehensive search for ALP spectral signatures using the observations of long GRBs with the Fermi Large Area Telescope (LAT). We perform a data-driven sensitivity analysis to determine CCSN distances for which a detection of an ALP signal is possible with the LAT’s low-energy technique which, in contrast to the standard LAT analysis, allows for a a larger effective area for energies down to 30 MeV. Assuming an ALP mass m a ≲ 10 - 10 eV and ALP-photon coupling g a γ = 5.3 × 10 - 12 GeV - 1 , values considered and deduced in ALP searches from SN1987A, we find that the distance limit ranges from ~ 0.5 to ~ 10 Mpc , depending on the sky location and the CCSN progenitor mass. Furthermore, we select a candidate sample of 24 GRBs and carry out a model comparison analysis in which we consider different GRB spectral models with and without an ALP signal component. We find that the inclusion of an ALP contribution does not result in any statistically significant improvement of the fits to the data. Finally, we discuss the statistical method used in our analysis and the underlying physical assumptions, the feasibility of setting upper limits on the ALP-photon coupling, and give an outlook on future telescopes in the context of ALP searches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Measurements of the 239 Pu(n,f)/ 235 U(n,f) and 238 U(n,f)/ 235 U(n,f) Cross-Section Ratios Using Quasi-Monoenergetic Neutron Beams

Neutron-induced fission cross-section ratio measurements were carried out at Triangle Universities Nuclear Laboratory (TUNL) over multiple experiment campaigns from 2021-2023. The total beam time for these measurements across all the experimental campaigns was approximately three weeks. This work was intended to serve as an independent validation of the fissionTPC cross-section ratio measurements. In contrast to the white spectrum neutron source and time-projection chamber utilized in the fissionTPC, these measurements utilized pulsed, quasi-monoenergetic neutron beams and fission ionization chambers. Therefore, this work has different sources of systematic error and can be used as a complementary measurement. In this report we describe our fission cross-section ratio measurements, analysis, results and provide a detailed uncertainty budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Simple Bioparticle Filtration Device Based on an Ultralow-Fouling Zwitterionic Polyurethane Membrane for Rapid Large-Volume Separation of Plasma and Viruses from Whole Blood

Plasma separation from whole blood is oftent required as an essential first step when performing blood tests with a viral assay. However, developing a point-of-care plasma extraction device with a large output and high virus recovery remains a significant obstacle to the success of on-site viral load tests. Here, we report a portable, easy-to-use, cost-efficient, membrane-filtration-based plasma separation device that enables rapid large-volume plasma extraction from whole blood, designed for point-of-care virus assays. The plasma separation is realized by a low-fouling zwitterionic polyurethane-modified cellulose acetate (PCBU-CA) membrane. The zwitterionic coating on the cellulose acetate membrane can decrease surface protein adsorption by 60% and increase plasma permeation by 46% compared with a pristine membrane. The PCBU-CA membrane, with its ultralow-fouling properties, enables rapid plasma separation. The device can yield a total of 1.33 mL plasma from 10 mL whole blood in 10 min. The extracted plasma is cell-free and exhibits a low hemoglobin level. In addition, our device demonstrated a 57.8% T7 phage recovery in the separated plasma. The results of real-time polymerase chain reaction analysis confirmed that the nucleic acid amplification curve of the plasma extracted by our device is comparable to that obtained by centrifugation. With its high plasma yield and good phage recovery, our plasma separation device provides an excellent replacement for traditional plasma separation protocols for point-of-care virus assays and a broad spectrum of clinical tests.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Assessment of Impurities in Neptunium Metal Using Double-Focusing SF-ICP-MS

In the transmutation process, minor actinides such as neptunium, americium and curium obtained from spent nuclear fuel are incorporated into new fuel that can be placed into a fast reactor, where these elements fission into products with shorter half-lives which reduces the health and safety hazards. In order to better understand the all the involved processes, fundamental physical properties of actinides should be investigated, and for that reason, high-purity materials need to be produced. One of the main challenges in characterizing these materials is the lack of pure metal available for study, and lack of analytical methods to determine the purity. Trans-uranic elements are challenging to study because of the need to be handled in specialized facilities, safeguards concerns and they are not easily purchased and/or produced. High-purity Np metal is being produced at the Materials and Fuels Complex (MFC) of Idaho National Laboratory (INL), in a process of direct oxide reduction developed by Squires and Lessing, with a target purity of 99.999%. The goal of this research is to develop methods to determine the impurities in the Np metal, with detection limits low enough to achieve this purity level. In this work, we have used several ICP-MS and ICP OES techniques, but the focus was the method development using a recently acquired Double-Focusing Sector Field Inductively Coupled Plasma Mass Spectrometer (SF-ICP-MS). To produce the Np metal, approximately 20 g of the neptunium oxide powder was calcined at 800 oC for 6 h in a magnesium oxide crucible, which is placed inside a stainless steel crucible, that goes into the Hot Uniaxial Press (HUP) furnace insert. After the calcining step, the Np oxide was mixed with approximately 9 g of calcium metal and 100 g of ultra-dry calcium chloride. The HUP furnace was heated in a ramp rate of 50 oC min -1 up to 1000 oC. When the reaction mixture reached 850 oC, a tantalum stirrer was activated at 100 rpm. After the tantalum stirrer was removed and the mixture cooled overnight, the MgO crucible was opened with a hammer and chisel to retrieve the Np metal button at the bottom of the reaction mixture. Prior to the dissolution process, the surface contaminants of the sample were removed. The Np button was washed in 10 mL of ultra-pure water for 1 min, with a faint reaction observed on the surface, indicating the presence of Ca metal. The water-washed sample was placed in a tube with 2 M HCl for only 3 s, as a vigorous reaction in the button surface was observed. The leachates were saved for further analysis. The sample was then rinsed with ultra-pure water and air-dried prior to dissolution. The cleaned sample was placed in a PTFE beaker and 25 mL of 6 M HCl and 150 µL of 24 M HF were added. After 10 minutes of reaction, the beaker was placed on a hot plate for 1 h and 30 min, followed by the addition of 1 mL of 16 M HNO3 and allowed to react for a further 1 h and 20 min. The sample was removed from heat and 10 mL of HNO3 16 M was added to react with the HCl. The beaker was covered and left for overnight reaction, producing a solution with approximately 20 mL of final volume. A Quadrupole Inductively Coupled Plasma Mass Spectrometer (Q-ICP-MS, Perkin Elmer ELAN DRC II Q-ICP-MS) was used to obtain qualitative mass spectra for the dissolution blank, each of the leachates and the dissolved sample. In the water leachate spectrum mainly Ca and Mg were observed, while the acid wash had a similar peak pattern to the one observed for the Np metal sample, indicating that the process not only removed surface contamination, but also reacted with the sample itself. In the Np material spectrum, Ta and actinides were identified as candidates for major contaminants, as the most intense peaks corresponded to the mass-to-charge ratios of these elements. Minor contaminants included Al, Au, Ca, Cr, Fe, I, Na, Nb, Pb, Sn, Ti, Tl, V, Y. The presence of impurities in the material could have originated from several sources, such as the materials used for the casting process, the use of impure NpO2 or contamination of reagents and materials used for the analysis. Some of the isotopes listed as potential contaminants are susceptible to spectral interferences, so Double-Focusing SF-ICP-MS (Nu Instruments Attom ES HR-ICP-MS) was used for the quantitative analysis. For each isotope determined, several items were evaluated: raw signal of a blank solution, sensitivity and determination coefficient of calibration curves, possibility of interferences and comparison of results obtained for at least two resolving powers (RP): 300 and 4000. The evaluation of the signal in a blank solution can indicate if a spectral interference from the plasma gas and/or the solvent was successfully resolved (commonly observed for 52Cr+/40Ar12C+, for example). It is important to highlight that a signal reduction is expected when a higher RP is used, as the ion beam transmission is decreased by the use of narrower slits

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

Deep-Learning-Derived Evaluation Metrics Enable Effective Benchmarking of Computational Tools for Phosphopeptide Identification

Tandem mass spectrometry (MS/MS)-based phosphoproteomics is a powerful technology for global phosphorylation analysis. However, applying four computational pipelines to a typical mass spectrometry (MS)-based phosphoproteomic dataset from a human cancer study, we observed a large discrepancy among the reported phosphopeptide identification and phosphosite localization results, underscoring a critical need for benchmarking. While efforts have been made to compare performance of computational pipelines using data from synthetic phosphopeptides, evaluations involving real application data have been largely limited to comparing the numbers of phosphopeptide identifications due to the lack of appropriate evaluation metrics. We investigated three deep learning-derived features as potential evaluation metrics: phosphosite probability, Delta RT and spectral similarity. Predicted phosphosite probability is computed by MusiteDeep, which provides high accuracy as previously reported; Delta RT is defined as the absolute retention time (RT) difference between RTs observed and predicted by AutoRT; and spectral similarity is defined as the Pearson’s correlation coefficient between spectra observed and predicted by pDeep2. Using a synthetic peptide dataset, we found that both Delta RT and spectral similarity provided excellent discrimination between correct and incorrect peptide-spectrum matches (PSMs) both when incorrect PSMs involved wrong peptide sequences and even when incorrect PSMs were caused by only incorrect phosphosite localization. Based on these results, we used all the three deep learning-derived features as evaluation metrics to compare different computational pipelines on diverse set of phosphoproteomic datasets and showed their utility in benchmarking performance of the pipelines. The benchmark metrics demonstrated in this study will enable users to select computational pipelines and parameters for routine analysis of phosphoproteomics data and will offer guidance for developers to improve computational methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

DESI DR1 Lyα 1D power spectrum: the optimal estimator measurement

The one-dimensional power spectrum P 1D of Lyα forest offers rich insights into cosmological and astrophysical parameters, including constraints on the sum of neutrino masses, warm dark matter models, and the thermal state of the intergalactic medium. We present the measurement of P 1D using the optimal quadratic maximum likelihood estimator applied to over 300,000 Lyα quasars from Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) survey. This sample represents the largest to date for P 1D measurements and is larger than the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) by a factor of 1.7. We conduct a meticulous investigation of instrumental and analysis systematics and quantify their impact on P 1D . This includes the development of a cross-exposure estimator that eliminates the need to model the pipeline noise and has strong potential for future P 1D measurements. We also present new insights into metal contamination through the 1D correlation function. Using a fitting function we measure the evolution of the Lyα forest bias with high precision: b F (z) = (-0.218 ± 0.002) × ((1 + z)/4) 2.96±0.06 . In a companion validation paper, we substantially extend our previous suite of CCD image simulations to quantify the pipeline's exquisite performance accurately. In another companion paper, we present DR1 P 1D measurements using the Fast Fourier Transform (FFT) approach to power spectrum estimation. These two measurements produce a forest bias parameter that differs by 2.2 sigma. However, our model is simplistic, so this disagreement will be investigated in future work.

Lyman alpha forest↗