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DOE OSTI2024

QC-GN 2 oMS 2 : a Graph Neural Net for High Resolution Mass Spectra Prediction

Predicting the mass spectrum of a molecular ion is often accomplished via three generalized approaches: rules-based methods for bond breaking, deep learning, or quantum chemical (QC) modeling. Rules-based approaches are often limited by the conditions for different chemical subspaces and perform poorly under chemical regimes with few defined rules. QC modeling is theoretically robust but requires significant amounts of computational time to produce a spectrum for a given target. Among deep learning techniques, graph neural networks (GNNs) have performed better than previous work with fingerprint-based neural networks in mass spectra prediction. To explore this technique further, we investigate the effects of including quantum chemically derived information as edge features in the GNN to increase predictive accuracy. The models we investigated include categorical bond order, bond force constants derived from extended tight-binding (xTB) quantum chemistry, and acyclic bond dissociation energies. Throughout this work, we evaluated these models against a control GNN with no edge features in the input graphs. Bond dissociation enthalpies yielded the best improvement with a cosine similarity score of 0.462 relative to the baseline model (0.437). In this work we also apply dynamic graph attention which improves performance on benchmark problems and supports the inclusion of edge features. Between implementations, we investigate the nature of the molecular embedding for spectra prediction and discuss the recognition of fragment topographies in distinct chemistries for further development in tandem mass spectrometry prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Vibrational Spectra of HNIW and its Isotopologues: A Combined Experimental and Computational Study

Incorporating isotopically labelled materials in degradation experiments could help unravel the mechanism(s) of decomposition through use of the kinetic isotope effect. Characterizing synthesized isotopologues however requires an understanding of what observable signals are affected by the isotopic substitution. As vibrational spectroscopy can distinguish between isotopologues, it is an ideal characterization technique to evaluate isotopic variants. To this end, the vibrational spectra of HNIW and its deuterated ( 2 H), 13 C, 15 N (all), 15 N (nitro), and 18 O isotopologues have been computationally predicted in the gas phase using density functional theory. These results are compared to experimentally measured FTIR/ATR and Raman spectra of both unsubstituted HNIW and 15 N-labeled HNIW in which the six nitro groups were synthetically tagged with 15 N atoms ( 15 N nitro -HNIW). The experimental isotopic frequency shift for the -NO 2 asymmetric stretching frequencies agrees with that theoretically calculated (~35.7 cm-1 vs. 36.5cm-1, respectively). Furthermore, analysis of the theoretically predicted frequency shifts for all isotopologues suggest the -NO 2 bending modes are lower in frequency than previously reported. This assignment is supported by the experimentally measured isotopic shift of ~10.1 cm -1 for these features (consistent with the predicted shift of ~13.1 cm -1 ). This work expands our current understanding of the vibrational modes in HNIW as well as provides a method for future work on similar systems.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A method for generating quantitative vapor-phase infrared spectra of solids: results for phenol, camphor, menthol, syringol, dicyclopentadiene and naphthalene

Here, a method is presented to generate quantitative vapor-phase infrared spectra from substances that naturally occur as solids with moderate volatility. The solid is gravimetrically dissolved into a solvent that has few infrared spectral features, typically CS 2 and CCl 4 separately. The solution is flowed at a constant rate from a linearly pumped syringe into a metered stream of nitrogen carrier gas regulated by a mass flow controller. The analyte/solvent mix is flash vaporized by volatilizing the solution across a heated stainless-steel surface as it emanates from the syringe tip. The N 2 gas-solution mixture is flowed into a long-path White cell thermostatted at a desired temperature, the long optical path compensating for the modest analyte mixing ratio. A composite spectrum is generated from typically ten or more 760-Torr pressure-broadened spectra over the 600 to 6500 cm -1 spectral range at 0.1 cm -1 spectral resolution. The solid analytes reported here using this novel technique include dicyclopentadiene, menthol, syringol, phenol, camphor, and naphthalene.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Using machine learning to predict the correlation of spectra using SDSS magnitudes as an improvement to the Locus Algorithm

The Locus Algorithm is a new technique to improve the quality of differential photometry by optimising the choices of reference stars. At the heart of this algorithm is a routine to assess how good each potential reference star is by comparing its SDSS magnitude values to those of the target star. In this way, the difference in wavelength-dependent effects of the Earth’s atmospheric scattering between target and reference can be minimised. This paper sets out a new way to estimate the quality of each reference star using machine learning. A random subset of stars from SDSS with spectra was chosen. For each one, a suitable reference star, also with a spectrum, was chosen. The correlation between the two spectra in the SDSS r band (between 550 nm and 700 nm) was taken to be the gold-standard measure of how well they match up for differential photometry. The five SDSS magnitude values for each of these stars were used as predictors. A number of supervised machine learning models were constructed on a training set of the stars and were each evaluated on a testing set. The model using Support Vector Regression had the best performance of these models. It was then tested on a final, hold-out, validation set of stars to get an unbiased measure of its performance. With an R 2 of 0.62, the SVR model presents enhanced performance for the Locus Algorithm technique.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

ZIF-8 Vibrational Spectra: Peak Assignments and Defect Signals

In this study, Zeolitic Imidazolate Framework-8 (ZIF-8) is a promising material for gas separation applications. It also serves as a prototype for numerous ZIFs, including amorphous ones, with a broader range of possible applications, including sensors, catalysis, and lithography. It consists of zinc coordinated with 2-methylimidazolate (2mIm) and has been synthesized with methods ranging from liquid-phase to solvent-free synthesis, which aim to control its crystal size and shape, film thickness and microstructure, and incorporation into nanocomposites. Depending on the synthesis method and post-synthesis treatments, ZIF-8 materials may deviate from the nominal defect-free ZIF-8 crystal structure due to defects like missing 2mIm, missing zinc, and physically adsorbed 2mIm trapped in the ZIF-8 pores, which may alter its performance and stability. Infra-red (IR) spectroscopy has been used to assess the presence of defects in ZIF-8 and related materials. However, conflicting interpretations by various authors persist in the literature. Here, we systematically investigate ZIF-8 vibrational spectra by combining experimental IR spectroscopy and first-principles molecular dynamics simulations, focusing on assigning peaks and elucidating the spectroscopic signals of putative defects present in ZIF-8 material. We attempt to resolve conflicting assignments from the literature and to provide a comprehensive understanding of the vibrational spectra of ZIF-8 and its defect-induced variations, aiming towards more precise quality control and design of ZIF-8-based materials for emerging applications.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Transient resonant Auger–Meitner spectra of photoexcited thymine

In this paper, we present the first investigation of excited state dynamics by resonant Auger–Meitner spectroscopy (also known as resonant Auger spectroscopy) using the nucleobase thymine as an example. Thymine is photoexcited in the UV and probed with X-ray photon energies at and below the oxygen K-edge. After initial photoexcitation to a ππ* excited state, thymine is known to undergo internal conversion to an nπ* excited state with a strong resonance at the oxygen K-edge, red-shifted from the ground state π* resonances of thymine. We resolve and compare the Auger–Meitner electron spectra associated both with the excited state and ground state resonances, and distinguish participator and spectator decay contributions. Furthermore, we observe simultaneously with the decay of the nπ* state signatures the appearance of additional resonant Auger–Meitner contributions at photon energies between the nπ* state and the ground state resonances. We assign these contributions to population transfer from the nπ* state to a ππ* triplet state via intersystem crossing on the picosecond timescale based on simulations of the X-ray absorption spectra in the vibrationally hot triplet state. Moreover, we identify signatures from the initially excited ππ* singlet state which we have not observed in our previous study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Structural phase transition and manifestation of eddy currents in IR reflection spectra of PbSnTe semiconductor films

Infrared reflection spectra of thin (∼60 nm) Pb{sub 1−x} Sn{sub x}Te (x = 0.25, 0.53, 0.59) films grown by molecular beam epitaxy on GaAs/CdTe hybrid substrates have been measured at frequencies from 20 to 5500 cm{sup −1} and temperatures from 5 to 300 K. The spectra have been used to determine temperature-dependent transverse phonon and plasmon frequencies in the films, which has made it possible to identify a structural phase transition at T{sub C} ≈ 50 K. The plasma frequency of the films has been shown to increase with decreasing band gap on cooling from 300 to 77 K. The increase in plasma frequency is mainly attributable to the increase in carrier concentration and a transition of the carriers from vortex states on the film surface to the valence band. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Observations of xenon spectra on the EAST x-ray crystal spectrometer for high-temperature plasma diagnostics

The Xe 44+ 2.7203 Å line, which has been proposed as one of the diagnostic lines for the x-ray imaging crystal spectrometer on ITER, is observed on the EAST tokamak together with its several satellite lines. The observations are made under high electron temperature (T e ) conditions (core T e > 5 keV). Most of the observed xenon lines are identified by comparing the experiment results with the atomic simulation results. The first ion temperature measurements made by the xenon spectra on EAST are also reported in this article. These xenon spectra observations contribute to the justification for using xenon as the diagnostic impurity in x-ray crystal spectrometers in future reactor-scale high-temperature plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Green’s function methods for excited states and x-ray spectra of functional materials

Many interesting properties of functional materials, such as dynamic response and thermodynamic behavior, depend on their excited state properties. These functional properties are often related to excitations in the system, such as phonons and plasmons, which lead to inelastic losses, lifetime, and other dynamic effects. The excitations are pure many-body correlation effects that are missing from independent particle theories. They are revealed in x-ray spectra such as photoemission and absorption, where they show up as satellites beyond the quasi-particle approximation. Our main focus in this work is the use of Green's function methods to describe these effects. In particular, we discuss how the cumulant Green's function provides a unified treatment of such dynamic correlation effects in many contexts. Besides a robust theoretical framework, these methods also yield widely applicable tools for practical calculations of many functional properties of materials. Furthermore, this methodology is illustrated with a number of applications ranging from optical and x-ray spectra to thermodynamic properties, and dynamic response. Some recent extensions for more correlated systems are also briefly discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

ExoReL{sup R}: A Bayesian Inverse Retrieval Framework for Exoplanetary Reflected Light Spectra

The high-contrast imaging technique is meant to provide insight into those planets orbiting several astronomical units from their host star. Space missions such as Wide-Field InfraRed Survey Telescope, Habitable Exoplanet Imaging Mission, and Large Ultra-Violet/Optical/InfraRed Surveyor will measure reflected light spectra of cold gaseous and rocky planets. To interpret these observations, we introduce ExoReL{sup R} (Exoplanetary Reflected Light Retrieval), a novel Bayesian retrieval framework to retrieve cloud properties and atmospheric structures from exoplanetary reflected light spectra. As a unique feature, it assumes a vertically nonuniform volume mixing ratio (VMR) profile of water and ammonia, and uses it to construct cloud densities. In this way, clouds and molecular mixture ratios are consistent. We apply ExoReL{sup R} on three test cases: two exoplanets (υ And e and 47 Uma b) and Jupiter. We show that we are able to retrieve the concentration of methane in the atmosphere, and estimate the position of clouds when the signal-to-noise ratio of the spectrum is higher than 15, in line with previous works. Moreover, we described the ability of our model to give a chemical identity to clouds, and we discussed whether or not we can observe this difference in the planetary reflection spectrum. Finally, we demonstrate how it could be possible to retrieve molecular concentrations (water and ammonia in this work) below the clouds by linking the nonuniform VMR profile to the cloud presence. This will help to constrain the concentration of water and ammonia unseen in direct measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

ARES I: WASP-76 b, A Tale of Two HST Spectra

We analyze the transmission and emission spectra of the ultra-hot Jupiter WASP-76 b, observed with the G141 grism of the Hubble Space Telescope’s (HST) Wide Field Camera 3 (WFC3). We reduce and fit the raw data for each observation using the open-source software Iraclis before performing a fully Bayesian retrieval using the publicly available analysis suite TauREx 3. Previous studies of the WFC3 transmission spectra of WASP-76 b found hints of titanium oxide (TiO) and vanadium oxide (VO) or non-gray clouds. Accounting for a fainter stellar companion to WASP-76, we reanalyze this data and show that removing the effects of this background star changes the slope of the spectrum, resulting in these visible absorbers no longer being detected, eliminating the need for a non-gray cloud model to adequately fit the data but maintaining the strong water feature previously seen. However, our analysis of the emission spectrum suggests the presence of TiO and an atmospheric thermal inversion, along with a significant amount of water. Given the brightness of the host star and the size of the atmospheric features, WASP-76 b is an excellent target for further characterization with HST, or with future facilities, to better understand the nature of its atmosphere, to confirm the presence of TiO and to search for other optical absorbers.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

High-resolution Spectra of Earth-like Planets Orbiting Red Giant Host Stars

In the near future we will have ground- and space-based telescopes that are designed to observe and characterize Earth-like planets. While attention is focused on exoplanets orbiting main-sequence stars, more than 150 exoplanets have already been detected orbiting red giants, opening the intriguing question of what rocky worlds orbiting in the habitable zone (HZ) of red giants would be like and how to characterize them. We present a high-resolution spectral database of reflection and emission spectra for nominal Earth-like planets orbiting in the red giant HZ from the visible to infrared (0.4–20 μm) for planets orbiting at the Earth-equivalent distance. We also show the change of such planetary spectra through the evolution of their red giant hosts. While the luminosity of the host increases the contrast ratio between star and planet, the increased orbital distance of the HZ for red giant hosts relaxes the light suppression requirements close to the star, which could make such planets interesting targets to characterize and search for signs of life, if new coronagraph designs with higher suppression at larger orbital separations could be developed. We assess the feasibility of characterizing atmospheric features including biosignatures for such planets with the proposed mission concept Large UV/Optical/IR Surveyor (LUVOIR).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

X-Ray Spectra and Multiwavelength Machine Learning Classification for Likely Counterparts to Fermi 3FGL Unassociated Sources

We conduct X-ray spectral fits on 184 likely counterparts to Fermi-LAT 3FGL unassociated sources. Characterization and classification of these sources allows for more complete population studies of the high-energy sky. Most of these X-ray spectra are well fit by an absorbed power-law model, as expected for a population dominated by blazars and pulsars. A small subset of seven X-ray sources have spectra unlike the power law expected from a blazar or pulsar and may be linked to coincident stars or background emission. We develop a multiwavelength machine learning classifier to categorize unassociated sources into pulsars and blazars using gamma-ray and X-ray observations. Training a random forest (RF) procedure with known pulsars and blazars, we achieve a cross-validated classification accuracy of 98.6%. Applying the RF routine to the unassociated sources returned 126 likely blazar candidates (defined as P {sub bzr} ≥ 90%) and five likely pulsar candidates (P {sub bzr} ≤ 10%). Our new X-ray spectral analysis does not drastically alter the RF classifications of these sources compared to previous works, but it builds a more robust classification scheme and highlights the importance of X-ray spectral fitting. Our procedure can be further expanded with UV, visual, or radio spectral parameters or by measuring flux variability.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

AIMD‐Based Protocols for Modeling Exciplex Fluorescence Spectra and Inter‐System Crossing in Photocatalytic Chromophores

ABSTRACT This study introduces a computational protocol for modeling the emission spectra of exciplexes using excited‐state ab initio molecular dynamics (AIMD) simulations. The protocol is applied to a model exciplex formed by oligo‐p‐phenylenes (OPPs) and triethylamine (TEA), which is of interest in the context of photocatalytic reduction of . AIMD facilitates efficient sampling of the conformational space of OPP3 and OPP4 exciplexes with TEA, offering a dynamic alternative to previously employed static methods. The AIMD‐based protocol successfully reproduces experimental emission spectra for OPP‐TEA exciplexes, agreeing with previous computational and experimental findings. The results show that AIMD simulations provide an efficient means of sampling the conformational space of these exciplexes, requiring less user input and, in some instances, fewer computational resources than multiple excited‐state optimizations initiated from user‐specified initial structures. The study also evaluates the yield of intersystem crossing (ISC) using AIMD and Landau‐Zener probability. The results suggest that ISC is a minor decay channel for OPP3 and OPP4. This work provides new insights into the structural flexibility and emission characteristics of OPP‐TEA photoredox catalyst systems, potentially contributing to improved design strategies for organic chromophores in reduction applications.

Giudetti, Goran [Department of Chemistry Universit↗

DOE OSTI2021

Understanding flavin electronic structure and spectra

Abstract Flavins have emerged as central to electron bifurcation, signaling, and countless enzymatic reactions. In bifurcation, two electrons acquired as a pair are separated in coupled transfers wherein the energy of both is concentrated on one of the two. This enables organisms to drive demanding reactions based on abundant low‐grade chemical fuel. To enable incorporation of this and other flavin capabilities into designed materials and devices, it is essential to understand fundamental principles of flavin electronic structure that make flavins so reactive and tunable by interactions with protein. Emerging computational tools can now replicate spectra of flavins and are gaining capacity to explain reactivity at atomistic resolution, based on electronic structures. Such fundamental understanding can moreover be transferrable to other chemical systems. A variety of computational innovations have been critical in reproducing experimental properties of flavins including their electronic spectra, vibrational signatures, and nuclear magnetic resonance (NMR) chemical shifts. A computational toolbox for understanding flavin reactivity moreover must be able to treat all five oxidation and protonation states, in addition to excited states that participate in flavoprotein's light‐driven reactions. Therefore, we compare emerging hybrid strategies and their successes in replicating effects of hydrogen bonding, the surrounding dielectric, and local electrostatics. These contribute to the protein's ability to modulate flavin reactivity, so we conclude with a survey of methods for incorporating the effects of the protein residues explicitly, as well as local dynamics. Computation is poised to elucidate the factors that affect a bound flavin's ability to mediate stunningly diverse reactions, and make life possible. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Electronic Structure Theory > Combined QM/MM Methods Theoretical and Physical Chemistry > Spectroscopy

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

First measurement of large area jet transverse momentum spectra in heavy-ion collisions

Jet production in lead-lead (PbPb) and proton-proton (pp) collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV is studied with the CMS detector at the LHC, using PbPb and pp data samples corresponding to integrated luminosities of 404 μb$^{−1}$ and 27.4 pb$^{−1}$, respectively. Jets with different areas are reconstructed using the anti-k$_{T}$ algorithm by varying the distance parameter R. The measurements are performed using jets with transverse momenta (p$_{T}$) greater than 200 GeV and in a pseudorapidity range of |η| < 2. To reveal the medium modification of the jet spectra in PbPb collisions, the properly normalized ratio of spectra from PbPb and pp data is used to extract jet nuclear modification factors as functions of the PbPb collision centrality, p$_{T}$ and, for the first time, as a function of R up to 1.0. For the most central collisions, a strong suppression is observed for high-p$_{T}$ jets reconstructed with all distance parameters, implying that a significant amount of jet energy is scattered to large angles. The dependence of jet suppression on R is expected to be sensitive to both the jet energy loss mechanism and the medium response, and so the data are compared to several modern event generators and analytic calculations. The models considered do not fully reproduce the data.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Search for periodic signals in the dielectron and diphoton invariant mass spectra using 139 fb -1 of $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for physics beyond the Standard Model inducing periodic signals in the dielectron and diphoton invariant mass spectra is presented using 139 fb -1 of $\sqrt{s}$ = 13 TeV pp collision data collected by the ATLAS experiment at the LHC. Novel search techniques based on continuous wavelet transforms are used to infer the frequency of periodic signals from the invariant mass spectra and neural network classifiers are used to enhance the sensitivity to periodic resonances. In the absence of a signal, exclusion limits are placed at the 95% confidence level in the two-dimensional parameter space of the clock work gravity model. Model-independent searches for deviations from the background-only hypothesis are also performed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Perspectives on Tailoring Neutron Energy Spectra in Material Test Reactors

Material test reactors (MTRs) are used to irradiate nuclear fuels and materials to develop data for how they endure neutron bombardment in or near reactor cores. Most historic MTRs, and all that remain operational in the US today, are water-cooled types and produce a thermalized neutron flux. New irradiation facilities are needed which can produce neutron energy spectra relevant to fast and fusion reactor environments. Construction of these facilities will take several years of steadfast funding to complete, which poses a formidable schedule challenge for current fast and fusion reactor developers. Irradiation designs which modify the neutron energy spectra delivered to test specimens in thermal spectrum MTRs, an approach referred to as “spectral tailoring”, can be used to approximate several relevant phenomena in the materials needed to enable fast and fusion reactor technologies. This approach is imperfect, but still valuable in the present situation. Here, the two highest flux MTRs operational in the United States, the Advanced Test Reactor (ATR) and High Flux Isotope Reactor (HFIR), have rich histories, ongoing developments, and new potentials for spectral tailoring that will be reviewed and discussed in this paper.

36 MATERIALS SCIENCE↗