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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Climate Impact of Primary Plastic Production

Plastics show the strongest production growth of all bulk materials over the last decade. The industry’s current growth trajectory is exponential and plastic production is expected to double or triple by 2050. The rapidly increasing production of plastics and the continued reliance on fossil fuels for production, have contributed to numerous environmental problems and health harms. As a result, plastic pollution has become an increasing threat to natural ecosystems, human health and climate. However, there is a lack of granularity on the contribution of the primary plastics specifically to greenhouse gas (GHG) emissions and their impact on the remaining global carbon budget needed to stay below a 1.5°C or 2°C global average temperature rise. In this report, we explore the contribution of primary plastic production to climate change disaggregated by polymer and technology. To this end, we have developed comprehensive bottom-up modeling of GHG emissions from global primary plastic production, with a special focus on polymer value chains. We have analyzed the results under various growth scenarios in the context of carbon budgets compatible with a 1.5°C global trajectory. Modeling includes the material flows of all production stages, processes and technologies used in primary plastic production value chains, including from the extraction of fossil fuels required for production to shaping the final product. We specifically focus on nine major types of fossil fuel-based plastic polymers that are produced and consumed in large quantities: three types of polyethylene (PE) – low-density (LDPE), linear low-density (LLDPE), and high-density (HDPE) – as well as polypropylene (PP); polyethylene terephthalate (PET); polyvinyl chloride (PVC); polystyrene (PS) and other key styrene-based plastics such as styrene acrylonitrile (SAN) and acrylonitrile butadiene styrene (ABS), and polyurethane (PU). Together these account for about 80% of plastics production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ion cyclotron emission in Maxwellian plasmas

Destabilization of ion cyclotron waves—waves with frequencies close to ion cyclotron harmonics—in inhomogeneous plasmas with Maxwell velocity distribution is considered. A new mechanism of destabilization of these waves is found, whereas the known interaction between cyclotron waves and drift waves is shown to be hardly able to lead to instabilities in realistic tokamak plasmas. Our finding is that the resonance wave–particle interaction in the presence of temperature gradient can change the diamagnetic drift frequency in such a way that the destabilizing influence of the diamagnetic drift exceeds Landau damping. This occurs when the energy of resonance particles is sufficiently high, which is always the case due to the infinite tail of the Maxwell distribution. Particles with higher energies provide a larger ratio of drive to damping, but the number of resonance particles and, thus, instability growth rates are exponentially small when particle energy is very high. Therefore, only moderately suprathermal particles can lead to observable instabilities. A condition for instabilities driven by these particles is obtained. Destabilization of electrostatic cyclotron waves and ordinary cyclotron waves is studied.

Kolesnichenko, Ya. I. (ORCID:0000000323219681)↗
DOE OSTI2024

Classical field approximation of ultralight dark matter: Quantum break times, corrections, and decoherence

The classical field approximation is widely used to better understand the predictions of ultralight dark matter. Here, in this work, we use the truncated Wigner approximation method to test the classical field approximation of ultralight dark matter. This method approximates a quantum state as an ensemble of independently evolving realizations drawn from its Wigner function. The method is highly parallelizable and allows the direct simulation of quantum corrections and decoherence times in systems many times larger than have been previously studied in reference to ultralight dark matter. Our study involves simulation of systems in 1, 2, and 3 spatial dimensions. We simulate three systems, the condensation of a Gaussian random field in three spatial dimensions, a stable collapsed object in three spatial dimensions, and the merging of two stable objects in two spatial dimensions. We study the quantum corrections to the classical field theory in each case. We find that quantum corrections grow exponentially during nonlinear growth with the timescale being approximately equal to the system dynamical time. In stable systems the corrections grow quadratically. We also find that the primary effect of quantum corrections is to reduce the amplitude of fluctuations on the de Broglie scale in the spatial density. Finally, we find that the timescale associated with decoherence due to gravitational coupling to baryonic matter is at least as fast as the quantum corrections due to gravitational interactions. These results are consistent with the predictions of the classical field theory being accurate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Hybrid target design for imprint mitigation in direct-drive inertial confinement fusion

A target design for mitigating the Rayleigh-Taylor instability is proposed for use in high energy density and direct-drive inertial confinement fusion experiments. In this scheme, a thin gold membrane is offset from the main target by several-hundred microns. A strong picket on the drive beams is incident upon this membrane to produce x rays which generate the initial shock through the target. The main drive follows shortly thereafter, passing through the ablated shell and directly driving the main target. The efficacy of this scheme is demonstrated through experiments performed at the OMEGA EP facility, showing a reduction of the Rayleigh-Taylor instability growth which scales exponentially with frequency, suppressing development by at least a factor of 5 for all wavelengths below 100 μm. Furthermore, this results in a delay in the time of target perforation by ~40%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Biochemical and genetic studies define the functions of methylthiotransferases in methanogenic and methanotrophic archaea

Methylthiotransferases (MTTases) are radical S-adenosylmethionine (SAM) enzymes that catalyze the addition of a methylthio (-SCH 3 ) group to an unreactive carbon center. These enzymes are responsible for the production of 2-methylthioadenosine (ms 2 A) derivatives found at position A37 of select tRNAs in all domains of life. Additionally, some bacteria contain the RimO MTTase that catalyzes the methylthiolation of the S12 ribosomal protein. Although the functions of MTTases in bacteria and eukaryotes have been established via detailed genetic and biochemical studies, MTTases from the archaeal domain of life are understudied and the substrate specificity determinants of MTTases remain unclear. Here, we report the in vitro enzymatic activities of an MTTase (C4B56_06395) from a thermophilic Ca. Methanophagales anaerobic methanotroph (ANME) as well as the MTTase from a hyperthermophilic methanogen – MJ0867 from Methanocaldococcus jannaschii. Both enzymes catalyze the methylthiolation of N 6 -threonylcarbamoyladenosine (t 6 A) and N 6 -hydroxynorvalylcarbamoyladenosine (hn 6 A) residues to produce 2-methylthio-N 6 -threonylcarbamoyladenosine (ms 2 t 6 A) and 2-methylthio-N 6 -hydroxynorvalylcarbamoyladenosine (ms 2 hn 6 A), respectively. To further assess the function of archaeal MTTases, we analyzed select tRNA modifications in a model methanogen – Methanosarcina acetivorans – and generated a deletion of the MTTase-encoding gene (MA1153). We found that M. acetivorans produces ms 2 hn 6 A in exponential phase of growth, but does not produce ms 2 t 6 A in detectable amounts. Upon deletion of MA1153, the ms 2 A modification was absent, thus confirming the function of MtaB-family MTTases in generating ms 2 hn 6 A modified nucleosides in select tRNAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Quantum complexity of time evolution with chaotic Hamiltonians

We study the quantum complexity of time evolution in large-N chaotic systems, with the SYK model as our main example. This complexity is expected to increase linearly for exponential time prior to saturating at its maximum value, and is related to the length of minimal geodesics on the manifold of unitary operators that act on Hilbert space. Using the Euler-Arnold formalism, we demonstrate that there is always a geodesic between the identity and the time evolution operator e -iHt whose length grows linearly with time. This geodesic is minimal until there is an obstruction to its minimality, after which it can fail to be a minimum either locally or globally. We identify a criterion — the Eigenstate Complexity Hypothesis (ECH) — which bounds the overlap between offdiagonal energy eigenstate projectors and the k-local operators of the theory, and use it to argue that the linear geodesic will at least be a local minimum for exponential time. We show numerically that the large-N SYK model (which is chaotic) satisfies ECH and thus has no local obstructions to linear growth of complexity for exponential time, as expected from holographic duality. In contrast, we also study the case with N = 2 fermions (which is integrable) and find short-time linear complexity growth followed by oscillations. Our analysis relates complexity to familiar properties of physical theories like their spectra and the structure of energy eigenstates and has implications for the hypothesized computational complexity class separations PSPACE * BQP/poly and PSPACE * BQSUBEXP/subexp, and the “fast-forwarding” of quantum Hamiltonians.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Lyapunov exponent as a signature of dissipative many-body quantum chaos

A distinct feature of Hermitian quantum chaotic dynamics is the exponential increase of certain out-of-time-order correlation (OTOC) functions around the Ehrenfest time with a rate given by a Lyapunov exponent. Physically, the OTOCs describe the growth of quantum uncertainty that crucially depends on the nature of the quantum motion. Here, we employ the OTOC in order to provide a precise definition of dissipative quantum chaos. For this purpose, we compute analytically the Lyapunov exponent for the vectorized formulation of the large- q limit of a q -body Sachdev-Ye-Kitaev model coupled to a Markovian bath. These analytic results are confirmed by an explicit numerical calculation of the Lyapunov exponent for several values of q ≥ 4 based on the solutions of the Schwinger-Dyson and Bethe-Salpeter equations. We show that the Lyapunov exponent decreases monotonically as the coupling to the bath increases and eventually becomes negative at a critical value of the coupling signaling a transition to a dynamics which is no longer quantum chaotic. Therefore, a positive Lyapunov exponent is a defining feature of dissipative many-body quantum chaos. The observation of the breaking of the exponential growth for sufficiently strong coupling suggests that dissipative quantum chaos may require in certain cases a sufficiently weak coupling to the environment. Published by the American Physical Society 2024

García-García, Antonio M.↗
DOE OSTI2026

Exponential crystallization in corals

Corals form their reef-building aragonite (CaCO 3 ) skeletons via transient precursor phases yet understanding of the dynamics of these early-stage transformations remains incomplete. Using time-independent myriad mapping (MM) at 50 nm resolution, we map five mineral phases near the skeleton surface of Stylophora pistillata corals grown in varying seawater pH. All precursors, crystalline and amorphous, exhibit a consistent exponential decay from the growth front, with a shared decay length of 0.7 ± 0.1 μm, independent of time, phase, or pH. This spatial decay, paired with the constant growth rate of the skeleton, reveals a decay time of 5.1 ± 0.5 minutes. The dominant precursor is not amorphous but crystalline: calcium carbonate hemihydrate (CCHH, CaCO₃·½H₂O). These results suggest that exponential crystallization kinetics govern coral biomineralization and may be a widespread feature in biogenic, geologic, and synthetic systems—traceable long after initial mineral deposition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

On the shear-current effect: toward understanding why theories and simulations have mutually and separately conflicted

ABSTRACT The shear-current effect (SCE) of mean-field dynamo theory refers to the combination of a shear flow and a turbulent coefficient β21 with a favourable negative sign for exponential mean-field growth, rather than positive for diffusion. There have been long-standing disagreements among theoretical calculations and comparisons of theory with numerical experiments as to the sign of kinetic ($\beta ^u_{21}$) and magnetic ($\beta ^b_{21}$) contributions. To resolve these discrepancies, we combine an analytical approach with simulations, and show that unlike $\beta ^b_{21}$, the kinetic SCE $\beta ^u_{21}$ has a strong dependence on the kinetic energy spectral index and can transit from positive to negative values at $\mathcal {O}(10)$ Reynolds numbers if the spectrum is not too steep. Conversely, $\beta ^b_{21}$ is always negative regardless of the spectral index and Reynolds numbers. For very steep energy spectra, the positive $\beta ^u_{21}$ can dominate even at energy equipartition urms ≃ brms, resulting in a positive total β21 even though $\beta ^b_{21}\lt 0$. Our findings bridge the gap between the seemingly contradictory results from the second-order-correlation approximation versus the spectral-τ closure, for which opposite signs for $\beta ^u_{21}$ have been reported, with the same sign for $\beta ^b_{21}\lt 0$. The results also offer an explanation for the simulations that find $\beta ^u_{21}\gt 0$ and an inconclusive overall sign of β21 for $\mathcal {O}(10)$ Reynolds numbers. The transient behaviour of $\beta ^u_{21}$ is demonstrated using the kinematic test-field method. We compute dynamo growth rates for cases with or without rotation, and discuss opportunities for further work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Link statistics of dislocation network during strain hardening

Dislocations are line defects in crystals that multiply and self-organize into a complex network during strain hardening. The length of dislocation links, connecting neighboring nodes within this network, contains crucial information about the evolving dislocation microstructure. By analyzing data from Discrete Dislocation Dynamics (DDD) simulations in face-centered cubic (fcc) Cu, we characterize the statistical distribution of link lengths of dislocation networks during strain hardening on individual slip systems. Here, our analysis reveals that link lengths on active slip systems follow a double-exponential distribution, while those on inactive slip systems conform to a single-exponential distribution. The distinctive long tail observed in the double-exponential distribution is attributed to the stress-induced bowing out of long links on active slip systems, a feature that disappears upon removal of the applied stress. We further demonstrate that both observed link length distributions can be explained by extending a one-dimensional Poisson process to include different growth functions. Specifically, the double-exponential distribution emerges when the growth rate for links exceeding a critical length becomes super-linear, which aligns with the physical phenomenon of long links bowing out under stress. This work advances our understanding of dislocation microstructure evolution during strain hardening and elucidates the underlying physical mechanisms governing its formation.

Crystal plasticity↗
DOE OSTI2020

Chaos, percolation and the coronavirus spread: a two-step model

We discuss a two-step model for the rise and decay of a new coronavirus (Severe Acute Respiratory Syndrome-CoV-2) first reported in December 2019, COVID-19. The first stage is well described by the same equation for turbulent flows, population growth and chaotic maps: a small number of infected, d 0 , grows exponentially to a saturation value, d ∞ . The typical growth time (aggressive spreading of the virus) is given by τ = 1/λ where λ is the Lyapunov exponent. After a time t crit determined by social distancing and/or other measures, the spread decreases exponentially analogous to nuclear decays and non-chaotic maps. Some countries, like China, S. Korea and Italy, are in this second stage while others including the USA are near the end of the growth stage. The model predicted 15,000 (±2250) casualties for the Lombardy region (Italy) at the end of the spreading around May 10, 2020. Without the quarantine, the casualties would have been more than 50,000, one hundred days after the start of the pandemic. Here, the data from the 50 US states are of very poor quality because of an extremely late and confused response to the pandemic, resulting unfortunately in a large number of casualties, more than 70,000 on May 6, 2020, and more than 170,000 on August 21, 2020. S. Korea, notwithstanding the high population density (511/km 2 ) and the closeness to China, responded best to the pandemic with 255 deceased as of May 6, 2020, and 301 on August 21, 2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Divergent carbon use efficiency-growth rate tradeoff in popular biological growth models

Carbon use efficiency (CUE) is an important trait emerging from processes regulating biological growth. CUE can be computed either based on the growth of structural biomass or total biomass divided by substrate uptake rate. Nonequilibrium thermodynamics and observations suggest that, for an exponentially growing population of cells, structural biomass CUE should first increase, then peak, and finally decrease with specific growth rate; meanwhile, total biomass CUE increases asymptotically with specific growth rate. We compared predictions from six popular models that are often used for plant and microbial growth in existing ecosystem models. We found that, for an exponentially growing population of biological cells, (1) the source-driven Pirt and Compromise models predict that structural biomass CUE increase asymptotically with growth rate; (2) the apparent sink-driven modified Droop model predicts that structural biomass CUE decreases with growth rate; and (3) the sink-driven variable internal storage model and two dynamic energy budget models predict that structural biomass CUE first increases, then peaks, and finally decreases with growth rate. Moreover, the modified Droop model predicts that total biomass CUE is constant with growth rate, while all other five models predict that total biomass CUE increases with growth rate asymptotically. For non-exponential biological growth, we show that there is no static relationship between total biomass CUE or structural biomass CUE with respect to either growth rate or temperature. Therefore, we contend that biological growth models should explicitly represent interactions between substrate acquisition, substate transformation, and maintenance respiration to better capture observed CUE dynamics, and the sink-driven model should be preferred for general ecosystem biogeochemistry modeling.

Tang, Jinyun [Lawrence Berkeley National Laborator↗
DOE OSTI2022

Viscoelastic necking dynamics between attractive microgels

Hypothesis: Microgels can deform and interpenetrate and display colloid/polymer duality. The effective interaction of microgels in the collapsed state is governed by the interplay of polymer–solvent interfacial tension and bulk elasticity. A connecting neck is shown to mediate microgel interaction, but its temporal evolution has not been addressed. Here we hypothesize that the necking dynamics of attractive microgels exhibits liquid-like or solid-like behavior over different time and length scales. Experiments: We simulate the merging and pinching of attractive microgels with different crosslinking densities in explicit solvent using dissipative particle dynamics. The temporal coalescence dynamics of microgels is investigated and compared with simple liquid and polymeric droplets. We model the neck growth on long time scales using Maxwell model of polymer relaxation and compare the theoretical prediction with simulation data. The mechanical strength of the neck is characterized systematically via simulated pinch-off of microgels by steered molecular dynamics. Findings: We evidence a crossover in the coalescence dynamics reflecting the viscoelastic signature of microgels. In contrast to the common knowledge that viscoelastic materials respond elastically on short time scales, the early expansion of the microgel neck exhibits a linear behavior, similar to the viscous coalescence of liquid droplets. However, the late regime with arrested dynamics resembles sintering of solid particles. Through an analytical model relating microgel dynamics to neck growth, we show that the long-term behavior is governed by stress relaxation of the polymers in the neck region and predict an exponential decay in the rate of growth, which agrees favorably with the simulation. Different from coalescence, the thread thinning in microgel breakup primarily highlights its polymeric characteristics.

42 ENGINEERING↗
DOE OSTI2021

Design Space Exploration of Emerging Memory Technologies for Machine Learning Applications

Memory design space exploration methods study memory systems’ performances and limitations before implementation. The computer memory design space has grown exponentially because of the enormous growth of memory types, memory controllers, and application software. Computer simulators are commonly used for memory design space exploration. However, complex memory simulations take an enormous amount of time. Hence, in this paper, we proposed a machine learning-based design space exploration method for dynamic random-access memory and non-volatile memory systems. We applied our method to the CosmoGAN and LeNet applications to predict the following six memory response parameters: (i) bandwidth, (ii) power, (iii) average latency, (iv) average total latency, (v) memory reads, and (vi) memory writes. Our experimental results show that machine learning models can predict memory response parameter values faster than simulations. We used support vector machine, random forest, and gradient boosting machine learning models. We observed that the support vector machine provides better performance for bandwidth, average latency, and average total latency. The random forest model works better for memory reads and writes. The gradient boosting model provides superior prediction performance for power. We provide a detailed discussion on learning curve characteristics, error analysis, and memory type recommendation.

Hasan, S M Shamimul↗
DOE OSTI2025

Impact of nutritional history, prey quality, and quantity on grazing and photophysiological responses in the mixoplanktonic dinoflagellate Karenia brevis

The mixotrophic toxic dinoflagellate Karenia brevis forms red tides almost annually along Florida's Gulf coast. We hypothesize that the nutritional status and abundance of its prey, the picocyanobacterium Synechococcus , will affect its feeding rates and growth responses, with implications for bloom dynamics. This study investigated how prey nutritional quality and quantity (absolute and relative) impact grazing rates by K. brevis initially exponentially growing and in nitrogen (N)-limited conditions, and how grazing, in turn, affects the photophysiological responses of predator and prey. Prey quality was manipulated by providing Synechococcus grown under different ratios of N : phosphorus (P). Synechococcus quality did not significantly affect ingestion rates (measured as prey death rate) but grazing rates increased with increasing prey : grazer ratios (R 2 = 0.7). Compared to control, the growth of exponentially growing grazers doubled when Synechococcus was provided, whereas there was no growth enhancement when Synechococcus of varying qualities was provided to N-limited, chemostat-seeded grazers. Despite this doubled growth, 15 N labeling of the prey and nanoscale secondary ion mass spectrometry (nanoSIMS) detected low Synechococcus -N transfer into grazer biomass after 3 d (< 1% on a cell basis). This suggests the potential of grazers benefiting from alternative N sources (e.g., microbiome-N) or other constituents (e.g., vitamins or metals) not measured in this study. Prey photosynthetic efficiency declined under grazing conditions, demonstrating that grazers can directly affect prey abundance through grazing and indirectly affect prey photophysiology, potentially via allelopathy, supporting previous findings of an inverse relationship between grazers and prey along the Florida Gulf Coast.

Ahn, So Hyun [Univ. of Maryland, Cambridge, MD (Un↗
DOE OSTI2021

Foliar respiration is related to photosynthetic, growth and carbohydrate response to experimental drought and elevated temperature

Short-term plant respiration (R) increases exponentially with rising temperature, but drought could reduce respiration by reducing growth and metabolism. Acclimation may alter these responses. We examined if species with different drought responses would differ in foliar R response to +4.8°C temperature and -45% precipitation in a field experiment with mature piñon and juniper trees, and if any differences between species were related to differences in photosynthesis rates, shoot growth and non-structural carbohydrates (NSCs). Short-term foliar R had a Q 10 of 1.6 for piñon and 2.6 for juniper. Piñon foliar R did not respond to the +4.8°C temperatures, but R increased 1.4x for juniper. Across treatments, piñon foliage had higher growth, lower NSC content, 29% lower photosynthesis rates, and 44% lower R than juniper. Removing 45% precipitation had little impact on R for either species. Species differences in the response of R under elevated temperature were related to substrate availability and stomatal response to leaf water potential. Despite not acclimating to the higher temperature and having higher R than piñon, greater substrate availability in juniper suggests it could supply respiratory demand for much longer than piñon. Species responses will be critical in ecosystem response to a warmer climate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Advanced Diagnostics of Broad Spectrum Multipactor

Multipactor is a resonance event between electron emission and RF fields causing exponential secondary electron re-emission growth when the secondary electron yield of the primary electron impact energy exceeds unity. Multipactor is a serious problem in vacuum electron devices (VEDs) such as particle accelerators, radars, electronic warfare systems, directed energy devices, and even Hall effect thrusters. It also poses an even greater threat to space communication systems where high power, multi-channel links are required. The UC Davis and SLAC team will conduct basic research to advance the fundamental understanding of multipactor physics by developing and carrying out full spectrum, radio frequency (RF) laboratory tests aimed at understanding both single and two-surface multipactor phenomena and at evaluating novel multipactor mitigation approaches for accelerator, space-based RF systems, as well as high power microwave (HPM) applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Fluorinated ionic liquids as gas chromatographic stationary phases for the separation of volatile per- and polyfluoroalkyl substances

Background Here, the production of fluorinated organic compounds in the manufacturing, semiconductor, and pharmaceutical industries has increased exponentially over the past decade. This rapid growth has created an urgent need for efficient chromatographic platforms capable of selectively separating these compounds from complex mixtures, not only to support industrial quality control and waste management practices, but also to enable reliable environmental monitoring of volatile fluorinated contaminants. Conventional GC stationary phases lack the fluorophilic interactions needed for highly fluorinated analytes. Consequently, there is a clear demand for specialized stationary phases designed to improve chromatographic retention and selectivity for these compounds. Results Three stationary phases composed of fluorinated ionic liquids (ILs) with varied extent of fluorination were prepared to study fluorophilic interactions with fluorinated/non-fluorinated probe molecules by gas chromatography (GC). IL stationary phases featuring linear and branched perfluoroalkyl moieties, as well as a branched alkyl moiety, were systematically investigated. Chromatographic performance was examined using fluorinated compounds and their hydrocarbon analogs, including CF 3 -substituted aromatics, aliphatic alcohols, fluorotelomer alcohols (FTOHs), and perfluoroalkenes. Measurements on 5 m and 20 m columns revealed that the IL possessing branched alkyl provided stronger dispersive and hydrogen bonding interactions toward non-fluorinated aromatic and long-chain alcohols, whereas the fluorinated ILs enhanced retention of highly fluorinated FTOHs and perfluorodecene. Comprehensive two-dimensional GC (GC × GC), using a nonpolar primary column coupled with secondary columns featuring cross-bonded poly(trifluoropropylmethyl siloxane) (Rtx-200 ms), the branched fluorinated IL, or the branched non-fluorinated IL, highlighted complementary selectivity with the branched fluorinated IL providing the strongest interactions with fluorinated analytes. Significance These results demonstrate that fluorinated IL stationary phases are promising alternatives to conventional polysiloxane stationary phases for improving the separation of per- and polyfluoroalkyl substances and related fluorinated compounds. By correlating IL structure with fluorophilic interactions, this work establishes design principles for GC stationary phases that enable enhanced selectivity for highly fluorinated analytes while maintaining complementary interactions with non-fluorinated compounds.

Comprehensive two-dimensional GC↗