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At least 199 records · Page 11

Phenyl‐Free Polynorbornenes for Potential Anion Exchange Ionomers for Fuel Cells and Electrolyzers

Abstract Ionomers in the catalyst layer play a critical role in the performance of fuel cells and electrolyzers. Phenyl adsorption on hydrogen oxidation catalysts and electrochemical oxidation of phenyl moieties on oxygen evolution catalysts are detrimental to the alkaline devices’ performance. Here the adsorption energy of phenyl‐containing ionomers is compared to provide the rationale for implementing phenyl‐free ionomers. Density functional theory calculations indicated that the norbornane fragment has minimal adsorption energy on Pt(111) due to the absence of aromatic π electrons. A soluble quaternized polynorbornene ionomer is prepared by vinyl addition polymerization, and it exhibits high performance in both fuel cells and electrolyzers, proving the advantage of the phenyl‐free structure. This study establishes the phenyl adsorption energy‐electrode performance relationship, highlighting the importance of material interactions between the catalysts and ionomers.

25 ENERGY STORAGE↗

Surface Functionalization of Black Phosphorus with Nitrenes: Identification of P=N Bonds by Using Isotopic Labeling

Abstract Surface functionalization of two‐dimensional crystals is a key path to tuning their intrinsic physical and chemical properties. However, synthetic protocols and experimental strategies to directly probe chemical bonding in modified surfaces are scarce. Introduced herein is a mild, surface‐specific protocol for the surface functionalization of few‐layer black phosphorus nanosheets using a family of photolytically generated nitrenes (RN) from the corresponding azides. By embedding spectroscopic tags in the organic backbone, a multitude of characterization techniques are employed to investigate in detail the chemical structure of the modified nanosheets, including vibrational, X‐ray photoelectron, solid state 31 P NMR, and UV‐vis spectroscopy. To directly probe the functional groups introduced on the surface, R fragments were selected such that in conjunction with vibrational spectroscopy, 15 N‐labeling experiments, and DFT methods, diagnostic P=N vibrational modes indicative of iminophosphorane units on the nanosheet surface could be conclusively identified.

Walz Mitra, Kendahl L.↗

High Semi-Volatile Organic Aerosol Contributions Associated with Ammonium Nitrate in the Coastal Urban Environment

Organic components often contribute 50% or more of the submicron aerosol mass in coastal urban environments, but their partitioning between the gas and particle phases is controlled by a complex mixture of unidentified organic compounds that are poorly constrained by observations. This study compares daily filter organic functional groups (OFG) with online organic mass fragments from La Jolla, California, as part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), quantifying the contributions of four types of non-volatile (NV) organic emission sources to the submicron composition. Daily filters retained only 0.79–0.98 µg/m3 NV submicron organic mass concentration, even though 1.8–1.9 µg/m3 non-refractory (NR) submicron organic mass concentration was measured online. The 62–64% of measured NR submicron organic mass concentration that exceeded what remained on the filters after 23-hr sampling is interpreted as semi-volatile, consistent with the moderate correlation of the NR NV difference to NR ammonium, NR nitrate, and biomass burning-related NV and NR organic factors. The association between semi-volatile organic components and ammonium nitrate likely results from both co-emission and co-evaporation. Size-resolved filter analysis showed that NV organic mass concentration accounts for 68% of NR organic mass concentration for 0.5–1 µm dry diameter but account for 9.0% for 0.18–0.5 µm dry diameter showing the differences in volatility between particle modes. Importantly, volatility of organic components was size-dependent Information Classification: General and associated with ammonium nitrate and biomass burning, providing guidance for constraining atmospheric aerosol properties in global models.

Pelayo, Christian↗

Tidal–hydrological dynamics of water temperature across freshwater forested wetlands on the northeastern Pacific coast

Abstract Tidal freshwater forests were once extensive across temperate coastlines, but loss and fragmentation have made estimation of their ecosystem functions challenging. We measured water temperature for 2 years in three Sitka spruce tidal forests, a restoration site, and an adjacent emergent marsh on the Columbia River, Washington, United States. We assessed spatial variability of water temperature within sites including the effects of hydrology, differences among bay and tributary tidal forests, and differences between the tidal forests and the mainstem Columbia, the restoration site, and the emergent marsh. The tidal forests nearest to the bay had lower interior water temperatures than their channel confluences by up to 2.5°C (weekly median temperature) and 2.0°C (weekly maximum temperature), with most cooling occurring during the low‐flow months of July–September. Tributary sites had maximum temperatures up to 1.9°C cooler than bay sites and 4.2°C cooler than the mainstem. Temperatures in the two bay sites decreased by −0.16°C/100 m and −0.07°C/100 m, on average. The restoration site had the smallest within‐site temperature gradient. Differences in maximum temperatures were greatest when tidal range was low, while higher tidal ranges were associated with warmer and more variable site interiors relative to their confluences. These results suggest that water temperatures in these tidal forests can provide temperature refugia for cold water biota including salmon.

54 ENVIRONMENTAL SCIENCES↗

Use of Split‐Intein Proteins to Design a Small Molecule Biosensor in Plants

Understanding how plants perceive their environment is fundamental to advancing agricultural productivity and sustainability. Many biological small molecules, including those involved in microbial recognition, act rapidly at the plant cell surface, but the absence of tools to visualise these dynamics has limited our ability to dissect plant–microbe communication. To address this gap, we sought to create a genetically encoded biosensor that couples ligand-induced protein dimerization with the production of a fluorescent reporter. Inteins are peptide regions that excise themselves from precursor proteins and ligate the flanking chains (exteins). When each half of a split intein is fused to one of two dimerizing proteins, ligand binding brings them into proximity, inducing intein splicing and ligation of flanking extein sequences (Kang et al. 2022). Similar to previous studies, we split the yeast vacuolar ATPase subunit 1 (VMA1) intein, creating a protein biosensor that produces eGFP upon protein dimerization after ligand binding (Figure 1A) (Mootz et al. 2003). Specifically, eGFP halves (i.e., non-functional N- and C-terminal GFP fragments) were fused to the intein halves, resulting in two fusion proteins: N-terminal GFP::N-terminal intein and C-terminal intein::C-terminal GFP (Figure 1A).

Boone, Brandon A. [Oak Ridge National Laboratory (↗

Deuteron-Deuteron Elastic and Three and Four-Body Breakup Scattering Using the Faddeev-Yakubovskii Equations

The deuteron-deuteron elastic and three and four-body breakup scattering cross section have been calculated using the Faddeev-Yakubovskii (FY) chain-of-partition momentum-space equations. In this calculation the initial two-cluster potential is split into separable and non-separable components, and the effective potential is reduced to elastic two-body and three and four-body breakup open-channels and a closed-channel many-body contribution. The closed-channel contribution is determined by minimizing a variational bound. The Coulomb interaction was included by expanding the initial and final Coulomb states in a Coulomb-Sturmian basis. The three sets of chain-of-partition integral equations were solved for the elastic and three and four-body breakup scattering amplitudes. The calculations were performed for the S = 2 spin/L = 0 angular-momentum state. The elastic and double-breakup calculations were performed for energies up to E = 5.48 MeV, while the single-breakup calculations were performed for energies up to E = 4.17 MeV. In the case of elastic scattering, the calculated scattering length of 5 a dd = 7.8 ± 0.3 fm is in good agreement with a FY cluster reduction calculation. The calculated phase shift is smaller than that predicted by the resonating group model and this difference is believed to be due to the differences in the potential and calculation methods. The breakup cross sections were calculated as a function of initial deuteron momentum and fragmented-deuteron momentum. Here, the d+d → d+n+p cross sections were compared with neutron yield measurements and, while the measurements also included the L > 0 components, the general features were consistent. Estimates of the calculational uncertainties/bias are provided.

42 ENGINEERING↗

Implementation and testing of physics-based pulverization model in BISON

This report summarizes lower length scale computational research conducted to improve the pulverization criterion for high-burnup UO 2 fuel in the BISON fuel performance code. This research was sponsored by the NEAMS program during FY22. Efforts to improve the model primarily focus on calculating the current pressure of bubbles in the high-burnup structure (HBS) region, as well as the critical bubble pressure at which pulverization occurs in the HBS. The phase-field model for predicting initial bubble pressure in the HBS was improved by implementing a more realistic model for defect production, and by coupling the phase-field model for inter-granular bubble evolution with the spatially-resolved cluster dynamics code Xolotl to simulate intra-granular fission gas evolution. An evolution equation for current bubble pressure was added to BISON, an improvement over the previous model that assumed that bubble pressure was static following HBS formation. To improve calculations of critical bubble pressure for pulverization, 3-D phase-field fracture simulations were performed, and a function for critical bubble pressure was fit—based on the simulation results—to replace the previous function, which had been determined using 2-D simulations. The impacts of these modifications to the existing pulverization assessment cases will be reported in the forthcoming engineering scale milestone on high-burnup UO 2 pulverization. A poromechanics-based approach was used to include the effect of bubble over pressurization on the stress state of the pellet at the engineering scale, and the initial strategy for integration of the pulverization criterion with pellet-scale mechanical degradation using a smeared cracking model was developed. This report also describes the initial research that was conducted to inform a forthcoming transient fission gas release (tFGR) model in BISON. Focusing on the fission gas release caused by pulverization of the outer pellet rim, a model for the amount of fission gas release was developed as a function of fuel porosity, bubble size, and fragment size. Implementation of this model in BISON and its impact of engineering-scale predictions will also be described in the aforementioned engineering-scale milestone on high-burnup UO 2 pulverization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The erosion of biodiversity and biomass in the Atlantic Forest biodiversity hotspot

Tropical forests are being deforested worldwide, and the remaining fragments are suffering from biomass and biodiversity erosion. Quantifying this erosion is challenging because ground data on tropical biodiversity and biomass are often sparse. Here, we use an unprecedented dataset of 1819 field surveys covering the entire Atlantic Forest biodiversity hotspot. We show that 83-85% of the surveys presented losses in forest biomass and tree species richness, functional traits, and conservation value. On average, forest fragments have 25-32% less biomass, 23-31% fewer species, and 33, 36, and 42% fewer individuals of late-successional, large-seeded, and endemic species, respectively. Biodiversity and biomass erosion are lower inside strictly protected conservation units, particularly in large ones. We estimate that biomass erosion across the Atlantic Forest remnants is equivalent to the loss of 55-70 thousand km 2 of forests or US$2.3-2.6 billion in carbon credits. These figures have direct implications on mechanisms of climate change mitigation.

54 ENVIRONMENTAL SCIENCES↗

Leading order track functions in a hot and dense QGP

We study the modifications to the fragmentation pattern of partons into charged particles in the presence of a hot and dense quark gluon plasma. To this end, we analyze the perturbative renormalization group equations of the track functions, which describe the energy fraction carried by charged hadrons. Focusing on pure Yang-Mills theory, we compute the lowest-order moments of the medium-modified track functions, which are found to be sensitive to the reduced phase space for emissions in the medium and to energy loss. We use the extracted moments to calculate the energy energy correlator (EEC) on tracks in the collinear limit. The EEC on medium-evolved tracks does not differ qualitatively from the EEC on vacuum tracks despite being sensitive to the color decoherence transition and suppressing the distribution due to quenching, as seen in other jet observables. Published by the American Physical Society 2024

Barata, João (ORCID:0000000342864555)↗

Proton Conducting Sulfonated Poly(Ionic Liquid) Block Copolymers

Herein, we report the synthesis of proton-conducting sulfonated poly(ionic liquid) block copolymers (S-PILBCPs) containing one block with sulfonic acid (sulfonated styrene, SS) and the other with an IL moiety (vinylbenzylmethylimidazolium bis(trifluoromethylsulfonyl)imide, VBMIm-TFSI) using reversible addition–fragmentation chain-transfer (RAFT) polymerization and post-polymerization modifications (i.e., functionalization, anion exchange reactions, and sulfonation). The S-PILBCPs uniquely conjoin the SS block with mobile protons (H + ) and the PIL block with mobile anions (TFSI – ), where multiple highly desired properties, including high proton conductivity (from the SS block), and high IL-philicity and oxygen solubility (from the PIL block) can exist compartmentally within a microphase separated morphology (evidenced by differential scanning calorimetry (DSC) and small-angle X-ray scattering (SAXS)). High ion conductivity of 79.7 mS/cm at a PIL block composition of 21.6 mol % was observed at 80 °C and 90% relative humidity (RH) (comparable to the benchmark Nafion ionomer). This work successfully demonstrates the design of S-PILBCPs as a new material platform and showcases its promise as an ionomer for proton exchange membrane fuel cells (PEMFCs) as they simultaneously and compartmentally combine proton conductivity and oxygen solubility. Furthermore, these benefits have recently been leveraged to achieve substantial improvement in oxygen reduction reaction (ORR) activity and subsequently fuel cell performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Truncating 2D Framework Materials Down to a Single Pore: Synthetic Approaches and Opportunities

Here, in this Accounts article, we summarize our recent work on truncating conjugated two-dimensional framework materials down to a single pore, or a single macrocycle. Conjugated 2D architectures have emerged as one of the most synthetically adaptable motifs for coupling semiconductivity and porosity in metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). However, despite their prevalence, 2D architectures have several limitations. In particular, the strong interlayer π–π stacking can limit both processability and the accessibility of internal active sites. We have found that simple macrocycles preserve key aspects of 2D framework structure and function, including porosity and out-of-plane electrical conductivity, while providing improved processability, surface tunability, and mass transport properties. In this article, we first describe our synthetic approach and general design considerations. Specifically, we show how ditopic analogues of the tritopic ligands commonly found in the synthesis of 2D MOFs and COFs can be used to achieve a diverse library of conjugated macrocycles that resemble fragments of semiconducting frameworks in both form and function. The length of the peripheral side chains, the size of the aromatic core, and the solubility of intermediates are all key variables in favoring selective macrocycle formation over undesired linear polymers and oligomers. Next, we highlight the unique advantages that macrocycles provide, including improved processability, atomically precise surface tunability, and greater active site accessibility. In particular, the identity of the peripheral side chains dramatically impacts both solubility and colloidal stability as well as crystal size and morphology. We further show how the solution processability and nanoscale dimensions of macrocycles can simplify electronic device fabrication and improve electrochemical performance. Finally, we end with a forward-looking discussion on how macrocycles offer a unique bridge between conjugated molecules and extended frameworks, enabling new application areas and fundamental science.

charge transport↗

Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry

Mass spectrometry is a ubiquitous technique capable of complex chemical analysis. The fragmentation patterns that appear in mass spectrometry are an excellent target for artificial intelligence methods to automate and expedite the analysis of data to identify targets such as functional groups. To develop this approach, we trained models on electron ionization (a reproducible hard fragmentation technique) mass spectra so that not only the final model accuracies but also the reasoning behind model assignments could be evaluated. The convolutional neural network (CNN) models were trained on 2D images of the spectra using transfer learning of Inception V3, and the logistic regression models were trained using array-based data and Scikit Learn implementation in Python. Our training dataset consisted of 21,166 mass spectra from the United States’ National Institute of Standards and Technology (NIST) Webbook. The data was used to train models to identify functional groups, both specific (e.g., amines, esters) and generalized classifications (aromatics, oxygen-containing functional groups, and nitrogen-containing functional groups). We found that the highest final accuracies on identifying new data were observed using logistic regression rather than transfer learning on CNN models. It was also determined that the mass range most beneficial for functional group analysis is 0–100 m/z. We also found success in correctly identifying functional groups of example molecules selected from both the NIST database and experimental data. Beyond functional group analysis, we also have developed a methodology to identify impactful fragments for the accurate detection of the models’ targets. The results demonstrate a potential pathway for analyzing and screening substantial amounts of mass spectral data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Fragmentation of Organic Small Molecules in Atom Probe Tomography

In atom probe tomography of molecular organic materials, field ionization of either entire molecules or molecular fragments can occur, but the mechanism governing this behavior was not previously understood. This work explains when a doubly ionized small molecule organic material is expected to undergo fragmentation. Here, we find that multiple detection events arising from post-ionization fragmentation of a parent molecular dication into two daughter ions is well explained by the free energy and geometries of the molecules computed using density functional theory. Of the systems studied, exergonic free energies for formation of the daughter ions, smaller activation energies for dissociation, and increases in bond length are all found to be quantitative predictors for ion fragmentation. This work expands the applicability of atom probe tomography to organic materials by increasing the fundamental understanding of processes occurring during this analysis technique.

36 MATERIALS SCIENCE↗

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗

Theory of nuclear fission

Atomic nuclei are quantum many-body systems of protons and neutrons held together by strong nuclear forces. Under the proper conditions, nuclei can break into two (sometimes three) fragments which will subsequently decay by emitting particles. This phenomenon is called nuclear fission. Since different fission events may produce different fragmentations, the end-products of all fissions that occurred in a small chemical sample of matter comprise hundreds of different isotopes, including α particles, together with a large number of emitted neutrons, photons, electrons and antineutrinos. The extraordinary complexity of this process, which happens at length scales of the order of a femtometer, mostly takes less than a femtosecond but is not entirely over until all the lingering β decays have completed – which can take years – is a fascinating window into the physics of atomic nuclei. While fission may be more naturally known in the context of its technological applications, it also plays a crucial role in the synthesis of heavy elements in astrophysical environments. In both cases, simulations are needed for the many systems or energies inaccessible to experiments in the laboratory. In this context, the level of accuracy and precision required poses formidable challenges to nuclear theory. Overall, the goal of this article is to provide a comprehensive overview of the theoretical methods employed in the description of nuclear fission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Atomistic simulations for investigation of substrate effects on lipid in-source fragmentation in secondary ion mass spectrometry

In beam-based ionization methods, the substrate plays an important role on the desorption mechanism of molecules from surfaces. Both the specific orientation that a molecule adopts at a surface and the strength of the molecule-surface interaction can greatly influence desorption processes, which in turn will affect the ion yield and the degree of in-source fragmentation of a molecule. In the beam-based method of secondary ion mass spectrometry (SIMS), in-source fragmentation can be significant and molecule specific due to the hard ionization method of using a primary ion beam for molecule desorption. To investigate the role of the substrate on orientation and in-source fragmentation, we have used atomistic simulations—molecular dynamics in combination with density functional theory calculations—to explore the desorption of a sphingolipid (palmitoylsphingomyelin) from a model surface (gold). We then compare SIMS data from this model system to our modeling findings. Using this approach, we found that the combined adsorption and binding energy of certain bonds associated with the headgroup fragments (C3H8N+, C5H12N+, C5H14NO+, and C5H15PNO4+) was a good predictor for fragment intensities (as indicated by relative ion yields). This is the first example where atomistic simulations have been applied in beam-based ionization of lipids, and it presents a new approach to study biointerfacial lipid ordering effects on SIMS imaging.

59 BASIC BIOLOGICAL SCIENCES↗

Delocalization error poisons the density-functional many-body expansion

The many-body expansion is a fragment-based approach to large-scale quantum chemistry that partitions a single monolithic calculation into manageable subsystems. This technique is increasingly being used as a basis for fitting classical force fields to electronic structure data, especially for water and aqueous ions, and for machine learning. Here, we show that the many-body expansion based on semilocal density functional theory affords wild oscillations and runaway error accumulation for ion–water interactions, typified by F − (H 2 O) N with N ≳ 15. We attribute these oscillations to self-interaction error in the density-functional approximation. The effect is minor or negligible in small water clusters, explaining why it has not been noticed previously, but grows to catastrophic proportion in clusters that are only moderately larger. This behavior can be counteracted with hybrid functionals but only if the fraction of exact exchange is ≳50%, whereas modern meta-generalized gradient approximations including ωB97X-V, SCAN, and SCAN0 are insufficient to eliminate divergent behavior. Other mitigation strategies including counterpoise correction, density correction (i.e., exchange–correlation functionals evaluated atop Hartree–Fock densities), and dielectric continuum boundary conditions do little to curtail the problematic oscillations. In contrast, energy-based screening to cull unimportant subsystems can successfully forestall divergent behavior. These results suggest that extreme caution is warranted when the many-body expansion is combined with density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Relativistic effects in Green's function Monte Carlo calculations of neutrino-nucleus scattering

Here, microscopic calculations of neutrino-nucleus scattering cross sections are critical for the success of the neutrino-oscillation program. In addition to retaining nuclear correlations in the initial and final state of the reaction, they are based on consistent nuclear interactions and transition current operators, thereby enabling robust uncertainty quantification. In this work, we address a significant limitation of these microscopic methods, which arises from their nonrelativistic nature. By performing the calculations in a reference frame that minimizes nucleon momenta and utilizing the so-called two-fragment model, we extend the applicability of Green's function Monte Carlo calculations of neutrino-nucleus scattering to higher momenta than currently possible. To validate this approach, we compare our theoretical predictions against inclusive data measured by the MiniBooNE, T2K, and MINER ν A experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗