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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗
DOE OSTI2026

Reducing systematic bias in machine learning applications to J/ψ signal extraction in high-energy nuclear physics

Machine learning techniques are increasingly used in high-energy nuclear physics because they can exploit multivariate correlations more efficiently than conventional cut-based analyses. A central challenge is the construction of training samples that faithfully reproduce the detector response observed in data. Signal samples are usually derived from detector simulations; therefore, mismatches between simulation and data can degrade classifier performance and introduce systematic biases. This work presents two practical correction procedures, namely cumulative distribution function (CDF) mapping and a shift-and-scale transformation, to align simulated signal features with those measured in data. Their performance is demonstrated with $J$/$\psi$ yield measurements in $\sqrt{s_{nn}}$ = 200 GeV Ru+Ru and Zr+Zr collisions recorded by STAR. A set of self-consistency tests shows that these procedures substantially suppress the systematic bias associated with data-simulation discrepancies in machine-learning-based signal extraction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics.

The standard model of cosmology has provided a good phenomenological description of a wide range of observations both at astrophysical and cosmological scales for several decades. This concordance model is constructed by a universal cosmological constant and supported by a matter sector described by the standard model of particle physics and a cold dark matter contribution, as well as very early-time inflationary physics, and underpinned by gravitation through general relativity. There have always been open questions about the soundness of the foundations of the standard model. However, recent years have shown that there may also be questions from the observational sector with the emergence of differences between certain cosmological probes. In this White Paper, we identify the key objectives that need to be addressed over the coming decade together with the core science projects that aim to meet these challenges. These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model. After reviewing the principal probes used in the measurement of cosmological parameters, as well as potential systematics, we discuss the most promising array of potential new physics that may be observable in upcoming surveys. We also discuss the growing set of novel data analysis approaches that go beyond traditional methods to test physical models. These new methods will become increasingly important in the coming years as the volume of survey data continues to increase, and as the degeneracy between predictions of different physical models grows. There are several perspectives on the divergences between the values of cosmological parameters, such as the model-independent probes in the late Universe and model-dependent measurements in the early Universe, which we cover at length. The White Paper closes with a number of recommendations for the community to focus on for the upcoming decade of observational cosmology, statistical data analysis, and fundamental physics developments.

Dienes, Keith [Univ. of Arizona, Tucson, AZ (Unite↗
DOE OSTI2020

Sr-Nd-Pb isotope systematics of Australasian tektites: Implications for the nature and composition of target materials and possible volatile loss of Pb

The Australasian tektite (AAT) strewn field is the largest strewn field on the Earth with about ~10–30% coverage, both land and ocean, but a clearly identified source impact crater is absent despite the young age of AAT of ca. 790 ka. A genetic link between the Australasian tektites and their unequivocal parental materials is therefore largely impossible to establish. Nevertheless, the nature of the parental materials and the extent of volatilization can be constrained using the splash form tektites, carrying the chemical signatures of high-temperature processes, and the layered (so-called Muong Nong-type) tektites, which are less chemically homogenized and exceptionally abundant in the AAT field. New high-precision Sr, Nd and Pb isotopic measurements were obtained for a chemically and petrographically well-characterized suite of AAT, which included the Muong Nong-type (MN-AAT) with precisely known field locations in Laos and splash forms (SF-AAT) from different parts of the strewn field. Additionally, optically dark and light zones of the MN-AAT were also separately analyzed. Homogeneous ε Nd values from -11.8 to -11.2, combined with a narrow range of two-stage Nd model ages from 1.67 to 1.72 Ga for the entire AAT suite, point to a well-mixed source, in terms of REE, of the crustal segment from which the sedimentary material for tektites was ultimately derived. The Sr isotopic data largely overlap for SF-AAT and MN-AAT ( 87 Sr/ 86 Sr = 0.71636–0.72021) and indicate Paleozoic to Mesozoic sedimentary parentage. However, late Neogene to early Quaternary re-deposition and formation of a thick silt-sized sedimentary section with vertical stratification is required to comply with 10Be data. Lead isotope systematics documents at least three different components which can perhaps be represented by different mineral phases, such as feldspar, zircon, organic matter adsorbed on young sediments etc., sorted during fluvial transport and final deposition. In addition, the SF-AAT have systematically lower Pb contents than the MN-AAT, and generally show isotopically heavier Pb isotopic ratios. This is theoretically consistent with a preferential volatilization of lighter Pb isotopes during evaporation and considerably larger Pb loss from SF-AAT when compared to MN-AAT. Nevertheless, further experimental work would be necessary to unambiguously distinguish kinetic fractionation from source mixing.

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

Overview of oxygen opacity experiments at the National Ignition Facility and investigation of potential systematic errors

Experiments to measure oxygen opacity at stellar interior conditions have been performed at the National Ignition Facility in a Discovery Science campaign. These experiments utilize the Opacity-on-NIF platform with a sample comprised of O, Mg, and Si. The spectral data from the Opacity Spectrometer cover the 1000–2000 eV photon energy range showing bound-free continuum absorption from O and line absorption from Mg and Si. DANTE and the Gated X-ray Detector are employed to measure the sample plasma’s temperature and density, respectively. Initial data show lower transmission than expected by theoretical models, raising questions of whether potential background or data uniformity concerns could produce systematic errors in the inferred transmission. Here, we investigate three concerns thought to be important for the oxygen opacity data, including instrumental scattered background, sample self-emission non-uniformity, and backlight continuum non-uniformity. Additionally, we show the effect of a recently developed method to account for 2nd order crystal reflection. The total effect of these concerns on one experiment is found to be small compared to the observed difference between the inferred transmission and a model calculation at the inferred temperature and density. Thus, we conclude that these potential sources of systematic error cannot account for the observed difference, increasing the likelihood of a real effect due to the high temperature and density conditions. However, because this is only a single experiment, we cannot make a firm conclusion. More experiments measuring the opacity and necessary calibrations are needed to assess the reproducibility and uncertainty of this result.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A systematic exploration of the hydrolysis products of the uranium trioxide polymorphs and their optical vibrational spectra

Study of the uranium trioxide (UO 3 )-water system is complex with inconclusive results and limited details in the literature. The UO 3 system is home to at least seven structural polymorphs and an amorphous phase. The proposed hydrolysis products of UO 3 are just as numerous, yet investigations of these alteration products are sporadic and generally antiquated, thus requiring systematic investigations. Recent developments in the understanding of UO 3 phase space, aided by improvements in analytical and computational techniques, necessitate more modern investigations into the uranyl hydroxide family and their naturally occurring mineral counterparts. We present findings from a systematic investigation of the products formed via hydrothermal reactions of common UO 3 polymorphs and discuss how the equatorial coordination of the uranyl/uranyl-like ions within the UO 3 precursors leads to differences in the optical vibrational spectra of the resulting hydrolysis products. The hypo-stochiometric nature of α-UO 2 (OH) 2 allows for the formation of multiple unique uranyl sites and a distortion of the unit cell to a lower symmetry. This study provides, for the first time, an analysis of β-UO 2 (OH) 2 using modern techniques and instrumentation (Raman/infrared spectroscopy and powder x-ray diffraction) and lays a foundation for future time-dependent investigations into the structural dependence of the hydrolysis kinetics of the UO 3 phases. In conclusion, given the prevalence of UO 3 at both ends of the nuclear fuel cycle, an understanding of its behavior with water has applications ranging from nuclear forensics to waste management and environmental transport.

Uranium trioxide↗
DOE OSTI2020

Systematic error analysis in the absolute hydrogen gas jet polarimeter at RHIC

The Polarized Atomic Hydrogen Gas Jet Target polarimeter (HJET) is operated at the Relativistic Heavy Ion Collider (RHIC) since 2004 to measure the absolute polarization of each colliding proton beam. Polarimeter detectors and data acquisition were upgraded in 2015 to increase the solid angle, energy range, and to improve the energy and time resolution. These upgrades along with an improved beam intensity and polarization allowed us to greatly reduce the statistical and systematic errors for the proton polarization measurements in RHIC Runs 15 (E beam = 100 GeV) and 17 (255 GeV). For a typical 8 hour RHIC store, the measured proton beam average polarization was about P beam ~ 55 ± 2.0 stat ± 0.3 syst %. The elastic pp analyzing power, AN(t)~0.04, was determined with a precision of about |δA N (t)|~0.0002 in the momentum transfer squared range 0.001<-t<0.020 GeV 2 . In this paper we present a detailed systematic error analysis of the polarization measurements at HJET. Perspectives of using the HJET based absolute polarimeters in the future Electron Ion Collider (EIC) will be also discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Exploring the Potential of Rainwater Harvesting for Cooling Towers: A Systematic Review and Regional Feasibility Assessment

Water scarcity has driven interest in rainwater harvesting, especially for U.S. industries like power and manufacturing, which dedicate a large percentage of their water needs to cooling towers. This paper provides a comprehensive systematic review of studies on the use of rainwater in cooling tower applications, along with an assessment of the regional feasibility of integrating RWH in U.S. manufacturing cooling towers. The systematic review examines the technical, economic, environmental, and policy feasibility of utilizing harvested rainwater, and the regional feasibility analysis evaluates the practical implementation of RWH in manufacturing cooling towers, considering factors such as regional RWH potential, water costs, state policies, and the industrial water use of manufacturing facilities per state. This study supports the hypothesis that RWH for cooling towers is technically feasible, economically viable, and environmentally beneficial. Harvested rainwater is naturally less conductive and soft, and rainwater reuse minimizes the ecological footprint. Supportive state policies, regional RWH potential, and rising water costs across the U.S. are important variables that may impact RWH adoption. The review highlights rooftop RWH as the most studied method and notes that implementing RWH requires infrastructure changes and filtration techniques. While initial investment costs may be high, operational and maintenance costs are low, making RWHS economically feasible over time. Regions with higher water costs and supportive policies are more likely to benefit from RWH adoption. The study provides a foundation for understanding the potential for using RWH in industrial cooling towers.

Cooling towers↗
DOE OSTI2020

A systematic strategy for estimating hERG block potency and its implications in a new cardiac safety paradigm

Introduction: hERG block potency is widely used to calculate a drug's safety margin against its torsadogenic potential. Previous studies are confounded by use of different patch clamp electrophysiology protocols and a lack of statistical quantification of experimental variability. Since the new cardiac safety paradigm being discussed by the International Council for Harmonisation promotes a tighter integration of nonclinical and clinical data for torsadogenic risk assessment, a more systematic approach to estimate the hERG block potency and safety margin is needed. Methods: A cross-industry study was performed to collect hERG data on 28 drugs with known torsadogenic risk using a standardized experimental protocol. A Bayesian hierarchical modeling (BHM) approach was used to assess the hERG block potency of these drugs by quantifying both the inter-site and intra-site variability. A modeling and simulation study was also done to evaluate protocol-dependent changes in hERG potency estimates. Results: A systematic approach to estimate hERG block potency is established. The impact of choosing a safety margin threshold on torsadogenic risk evaluation is explored based on the posterior distributions of hERG potency estimated by this method. The modeling and simulation results suggest any potency estimate is specific to the protocol used. Discussion: This methodology can estimate hERG block potency specific to a given voltage protocol. The relationship between safety margin thresholds and torsadogenic risk predictivity suggests the threshold should be tailored to each specific context of use, and safety margin evaluation may need to be integrated with other information to form a more comprehensive risk assessment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Systematic Evaluation of Counterpoise Correction in Density Functional Theory

A widespread belief persists that the Boys–Bernardi function counterpoise (CP) procedure “overcorrects” supramolecular interaction energies for the effects of basis-set superposition error. To the extent that this is true for correlated wave function methods, it is usually an artifact of low-quality basis sets. The question has not been considered systematically in the context of density functional theory, however, where basis-set convergence is generally less problematic. We present a systematic assessment of the CP procedure for a representative set of functionals and basis sets, considering both benchmark data sets of small dimers and larger supramolecular complexes. The latter include layered composite polymers with ~150 atoms and ligand–protein models with ~300 atoms. Provided that CP correction is used, we find that intermolecular interaction energies of nearly complete-basis quality can be obtained using only double-ζ basis sets. Furthermore, this is less expensive as compared to triple-ζ basis sets without CP correction. CP-corrected interaction energies are less sensitive to the presence of diffuse basis functions as compared to uncorrected energies, which is important because diffuse functions are expensive and often numerically problematic for large systems. Our results upend the conventional wisdom that CP “overcorrects” for basis-set incompleteness. In small basis sets, CP correction is mandatory in order to demonstrate that the results do not rest on error cancellation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Ultra-Low Amounts of Transition Metals in Carbon-Based Catalysts Improve Their Alkaline OER Performance: A Systematic Study

The pursuit of green hydrogen production highlights a persistent gap in electrocatalyst research: while academic efforts prioritize cost-efficiency via activity enhancement, industrial viability demands greater emphasis on electrochemical stability. Carbon-based electrocatalysts, particularly those incorporating transition metals, have shown promise in alkaline oxygen evolution (OER) due to their high activity, cost-efficiency, and resource-efficiency. However, these catalysts suffer from insufficient stability under oxidizing conditions compared to pure transition metal catalysts due to erosion of the carbon support resulting from carbon corrosion, among other degradation mechanisms. In this systematic study, the influence of ultra-low amounts (<1 wt %) of iron, cobalt, nickel, and their most common combinations on the stability of a hydrothermally derived, N-doped carbon support and the overall catalyst performance during alkaline OER is systematically explored. By identifying critical stability descriptors and correlating them with synthesis conditions and catalyst properties, primary and secondary corrosion pathways are unraveled. Subsequently, through careful adjustment of carbonization temperature and composition of incorporated transition metals, overall catalyst corrosion can be suppressed immensely. Especially, the inclusion of Ni and Fe is paramount for the formation of stable catalyst materials under laboratory conditions (10 mA/cm 2 in 0.1 M KOH), which is surprisingly unconstrained by the degree of graphitization of the carbon support. Mixing this electrochemically stable material with a graphitic carbon powder results in an excellent stability of over 400 h at 100 mA/cm 2 in 1 M KOH, implying great potential for the future improvement of carbon-based electrodes under oxidizing conditions toward industrial application.

N-doped carbon↗
DOE OSTI2025

Systematic Mapping of Bacterial CRISPRa Systems for Synergistic Gene Activation Reveals Antagonistic Effects

CRISPR gene activation (CRISPRa) tools have shown great promise for bacterial strain engineering but often require customization for each intended application. Our goal is to create generalizable CRISPRa tools that can overcome previous limitations of gene activation in bacteria. In eukaryotic cells, multiple activators can be combined for synergistic gene activation. To identify potential effectors for synergistic activation in bacteria, we systematically characterized bacterial activator proteins with a set of engineered synthetic promoters. We found that optimal target sites for different activators could vary by up to 200 bases in the region upstream of the transcription start site (TSS). These optimal target sites qualitatively matched previous reports for each activator, but the precise targeting rules varied between different promoters. By characterizing targeting rules in the same promoter context, we were able to test activator combinations with each effector positioned at its optimal target site. We did not find any activator combinations that produced synergistic activation, and we found that many combinations were antagonistic. Furthermore, this systematic investigation highlights fundamental mechanistic differences between bacterial and eukaryotic transcriptional activation systems and suggests that alternative strategies will be necessary for strong bacterial gene activation at arbitrary endogenous targets.

CRISPR activation↗
DOE OSTI2021

Using Large Ensembles to Identify Regions of Systematic Biases in Moderate-to-Heavy Daily Precipitation

Because of internal variability in both the real-world and global climate models, it is unclear whether disagreement between models and observations reflects true systematic differences, or different phasing of internal variability in the short observational period. Here, we address this issue through an examination of moderate-to-heavy precipitation in large ensembles of global climate models. We find that model inconsistency with a global observational product is lowest for extratropical precipitation in northern hemisphere winter. The inconsistency is systematically greater for the southern hemisphere winter, but the difference between hemispheres could be due to observational quality. Moderate-to-heavy extratropical winter precipitation is less inconsistent than moderate-to-heavy tropical precipitation in most models. Within the tropics, moderate-to-heavy precipitation is particularly inconsistent with the reference in regions including the Caribbean (especially during JJA), the northern and southern flanks of the Pacific and Atlantic ITCZ, and the Indian Ocean.

58 GEOSCIENCES↗
DOE OSTI2026

Systematic Benchmarking of Climate Models: Methodologies, Applications, and New Directions

As climate models become increasingly complex, there is a growing need to comprehensively and systematically assess model performance with respect to observations. Given the increasing number and diversity of climate model simulations in use, the community has moved beyond simple model intercomparison and toward developing methods capable of benchmarking a large number of simulations against a suite of climate metrics. Here, we present a detailed review of evaluation and benchmarking methods and approaches developed in the last decade, focusing primarily on scientific implications for Coupled Model Intercomparison Project (CMIP) simulations and CMIP6 results that contributed to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Based on this review, we explain the resulting contemporary philosophy of model benchmarking, and provide clear distinctions and definitions of the terms model verification, process validation, evaluation, and benchmarking. While significant progress has been made in model development based on systematic evaluation and benchmarking efforts, some climate system biases still remain. The development of open‐source community software packages has played a fundamental role in identifying areas of significant model improvement and bias reduction. We review the key features of several software packages that have been commonly used over the past decade to evaluate and benchmark global and regional climate models. Additionally, we discuss best practices for the selection of evaluation and benchmarking metrics and for interpreting the obtained results, the importance of selecting suitable sources of reference data and accurate uncertainty quantification.

Environmental sciences↗
DOE OSTI2025

Systematic softening in universal machine learning interatomic potentials

Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have led to universal MLIPs (uMLIPs) that are pre-trained on diverse datasets, providing opportunities for universal force fields and foundational machine learning models. However, their performance in extrapolating to out-of-distribution complex atomic environments remains unclear. In this study, we highlight a consistent potential energy surface (PES) softening effect in three uMLIPs: M3GNet, CHGNet, and MACE-MP-0, which is characterized by energy and force underprediction in atomic-modeling benchmarks including surfaces, defects, solid-solution energetics, ion migration barriers, phonon vibration modes, and general high-energy states. The PES softening behavior originates primarily from the systematically underpredicted PES curvature, which derives from the biased sampling of near-equilibrium atomic arrangements in uMLIP pre-training datasets. Our findings suggest that a considerable fraction of uMLIP errors are highly systematic, and can therefore be efficiently corrected. We argue for the importance of a comprehensive materials dataset with improved PES sampling for next-generation foundational MLIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

TDCOSMO. I. An exploration of systematic uncertainties in the inference of $H_0$ from time-delay cosmography

Time-delay cosmography of lensed quasars has achieved 2.4% precision on the measurement of the Hubble constant, H0. As part of an ongoing effort to uncover and control systematic uncertainties, we investigate three potential sources: 1- stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model. To meet this goal in a quantitative way, we reproduced the H0LiCOW/SHARP/STRIDES (hereafter TDCOSMO) procedures on a set of real and simulated data, and we find the following. First, stellar kinematics cannot be a dominant source of error or bias since we find that a systematic change of 10% of measured velocity dispersion leads to only a 0.7% shift on H0 from the seven lenses analyzed by TDCOSMO. Second, we find no bias to arise from incorrect estimation of the line-of-sight effects. Third, we show that elliptical composite (stars + dark matter halo), power-law, and cored power-law mass profiles have the flexibility to yield a broad range in H0 values. However, the TDCOSMO procedures that model the data with both composite and power-law mass profiles are informative. If the models agree, as we observe in real systems owing to the “bulge-halo” conspiracy, H0 is recovered precisely and accurately by both models. If the two models disagree, as in the case of some pathological models illustrated here, the TDCOSMO procedure either discriminates between them through the goodness of fit, or it accounts for the discrepancy in the final error bars provided by the analysis. This conclusion is consistent with a reanalysis of six of the TDCOSMO (real) lenses: the composite model yields H0 = 74.0−1.8+1.7 km s−1 Mpc−1, while the power-law model yields 74.2−1.6+1.6 km s−1 Mpc−1. In conclusion, we find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Toward a systematic improvement of the fixed-node approximation in diffusion Monte Carlo for solids—A case study in diamond

While Diffusion Monte Carlo (DMC) is in principle an exact stochastic method for ab initio electronic structure calculations, in practice, the fermionic sign problem necessitates the use of the fixed-node approximation and trial wavefunctions with approximate nodes (or zeros). This approximation introduces a variational error in the energy that potentially can be tested and systematically improved. Here, we present a computational method that produces trial wavefunctions with systematically improvable nodes for DMC calculations of periodic solids. These trial wavefunctions are efficiently generated with the configuration interaction using a perturbative selection made iteratively (CIPSI) method. A simple protocol in which both exact and approximate results for finite supercells are used to extrapolate to the thermodynamic limit is introduced. This approach is illustrated in the case of the carbon diamond using Slater–Jastrow trial wavefunctions including up to one million Slater determinants. Fixed-node DMC energies obtained with such large expansions are much improved, and the fixed-node error is found to decrease monotonically and smoothly as a function of the number of determinants in the trial wavefunction, a property opening the way to a better control of this error. The cohesive energy extrapolated to the thermodynamic limit is in close agreement with the estimated experimental value. Interestingly, this is also the case at the single-determinant level, thus, indicating a very good error cancellation in carbon diamond between the bulk and atomic total fixed-node energies when using single-determinant nodes.

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

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗