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At least 109 records · Page 6

A functional form for liquid scintillator pulse shapes

Digitization of detector signals enables analysis of the original waveform to extract timing, particle identification, and energy deposition information. Here we present the use of analytical functions based on sigmoids to model and fit such pulse shapes from liquid organic scintillators, though the method should also be applicable to other detector systems. Neutron and gamma interactions in NE213 detectors were digitized from the phototube anode and fit using a sigmoid-based function. The acuity of the fit in extracting timing information and performing neutron-gamma pulse-shape discrimination are presented and discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

PDB ‐101: Educational resources supporting molecular explorations through biology and medicine

Abstract The Protein Data Bank (PDB) archive is a rich source of information in the form of atomic‐level three‐dimensional (3D) structures of biomolecules experimentally determined using macromolecular crystallography, nuclear magnetic resonance (NMR) spectroscopy, and electron microscopy (3DEM). Originally established in 1971 as a resource for protein crystallographers to freely exchange data, today PDB data drive research and education across scientific disciplines. In 2011, the online portal PDB‐101 was launched to support teachers, students, and the general public in PDB archive exploration ( pdb101.rcsb.org ). Maintained by the Research Collaboratory for Structural Bioinformatics PDB, PDB‐101 aims to help train the next generation of PDB users and to promote the overall importance of structural biology and protein science to nonexperts. Regularly published features include the highly popular Molecule of the Month series, 3D model activities, molecular animation videos, and educational curricula. Materials are organized into various categories (Health and Disease, Molecules of Life, Biotech and Nanotech, and Structures and Structure Determination) and searchable by keyword. A biennial health focus frames new resource creation and provides topics for annual video challenges for high school students. Web analytics document that PDB‐101 materials relating to fundamental topics (e.g., hemoglobin, catalase) are highly accessed year‐on‐year. In addition, PDB‐101 materials created in response to topical health matters (e.g., Zika, measles, coronavirus) are well received. PDB‐101 shows how learning about the diverse shapes and functions of PDB structures promotes understanding of all aspects of biology, from the central dogma of biology to health and disease to biological energy.

Zardecki, Christine↗

Electropolymerized-molecularly imprinted polymers (E-MIPS) as sensing elements for the detection of dengue infection

Here, a straightforward in situ detection method for dengue infection was demonstrated through the molecular imprinting of a dengue nonstructural protein 1 (NS1) epitope into an electropolymerized molecularly imprinted polyterthiophene (E-MIP) film sensor. The key enabling step in the sensor fabrication is based on an epitope imprinting strategy, in which short peptide sequences derived from the original target molecules were employed as the main template for detection and analysis. The formation of the E-MIP sensor films was facilitated using cyclic voltammetry (CV) and monitored in situ by electrochemical quartz crystal microbalance (EC-QCM). Surface properties were analyzed using different techniques including atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and polarization modulation-infrared reflection-adsorption (PM-IRRAS). The standard calibration curve (R = 0.9830) was generated for the detection of the epitope, Ac-VHTWTEQYKFQ-NH 2 , with a linear range of 0.2 to 30 μg/mL and detection limit of 0.073 μg/mL. A separate calibration curve (R = 0.9786) was obtained using spiked buffered solutions of dengue NS1 protein, which resulted in a linear range of 0.2 to 10 μg/mL and a detection limit of 0.056 μg/mL. The fabricated E-MIP sensor exhibited long-term stability, high sensitivity, and good selectivity towards the targeted molecules. These results indicated that the formation of the exact and stable cavity imprints in terms of size, shape, and functionalities was successful. In our future work, we aim to use our E-MIP sensors for NS1 detection in real-life samples such as serum and blood.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bipolar Membrane Electrodialyzers as Flexible Demand Response Resources: Co-Optimization of Cost Savings and Product Formation

Bipolar membrane electro dialyzers (BPMED) are widely used for chemical production and processing, including in the emerging ocean alkalinity enhancement (OAE) industry. In this paper, we explore the potential of BPMED devices as flexible electrochemical loads within power system operations. Using a multi-objective optimization framework, we evaluate BPMED operation across 24-hour and monthly horizons to examine how dispatch strategies respond to electricity price and grid conditions. Simulation results show that altering the relative weights of the choices in the objective function strongly shape the operating patterns, with cost-focused strategies that suppress the operation during peak prices. Furthermore, we propose alternative formulations that optimize operations to achieve both cost savings and alignment with periods of lower grid-side carbon intensity (CI), as low grid-side CI is key to maximize OAE efficiency. Additionally, a detailed sensitivity analysis highlights the importance of device properties, where low area-specific resistance (ASR) of membrane and high current efficiency (CE) are observed to jointly unlock cost-effective operation. However, even modest shunt efficiency losses are observed to erode performance and decrease system value. Importantly, the analysis demonstrates that BPMED can serve as a controllable and flexible demand response resource, shifting load to support multiple grid-side objectives, including (but not limited to) renewable integration, alleviate peak demand, and provide co-benefits for system reliability. These findings underscore BPMED’s dual role as a process technology and a grid-supporting asset, pointing to promising pathways for operational optimization of multiple objectives.

Bhattacharya, Saptarshi (ORCID:0000000308902060)↗

Finite spatial-grid effects in energy-conserving particle-in-cell algorithms

Finite-grid (or aliasing) instabilities are pervasive in particle-in-cell (PIC) plasma simulation algorithms, and force the modeler to resolve the smallest (Debye) length scale in the problem regardless of dynamical relevance. These instabilities originate in the aliasing of interpolation errors between mesh quantities and particles (which live in the space–time continuum). Recently, strictly energy-conserving PIC (EC-PIC) algorithms have been developed that promise enhanced robustness against aliasing instabilities. In this study, we confirm by analysis that EC-PIC is stable against aliasing instabilities for stationary plasmas. For drifting plasmas, we demonstrate by analysis and numerical experiments that, while EC-PIC algorithms are not free from these instabilities in principle, they feature a benign stability threshold for finite-temperature plasmas that make them usable in practice for a large class of problems (featuring ambipolarity and realistic ion-electron mass ratios) without the need to consider the size of the Debye length. We also demonstrate that this threshold is absent for the popular momentum-conserving PIC algorithms, which are therefore unstable for both drifting and stationary plasmas beyond a threshold in cell size compared to Debye length. Finite-grid (or aliasing) instabilities are pervasive in particle-in-cell (PIC) plasma simulation algorithms, and force the modeler to resolve the smallest (Debye) length scale in the problem regardless of dynamical relevance. These instabilities originate in the aliasing of interpolation errors between mesh quantities and particles (which live in the space–time continuum). Recently, strictly energy-conserving PIC (EC-PIC) algorithms have been developed that promise enhanced robustness against aliasing instabilities. In this study, we confirm by analysis that EC-PIC is stable against aliasing instabilities for stationary plasmas. For drifting plasmas, we demonstrate by analysis and numerical experiments that, while EC-PIC algorithms are not free from these instabilities in principle, they feature a benign stability threshold for finite-temperature plasmas that make them usable in practice for a large class of problems (featuring ambipolarity and realistic ion-electron mass ratios) without the need to consider the size of the Debye length. Finally, we also demonstrate that this threshold is absent for the popular momentum-conserving PIC algorithms, which are therefore unstable for both drifting and stationary plasmas beyond a threshold in cell size compared to Debye length.

97 MATHEMATICS AND COMPUTING↗

Effect of Confinement on the Density and Diffusivity of Organic Molecules in Single-Digit Nanopores Relative to Bulk Fluid Behavior

Prediction of fluid properties in microporous and mesoporous confinement is non-trivial due to distinct influences from pore surface functionality and shape and fluid molecular characteristics. The vast majority of literature focuses nearly exclusively on a small number of components that are generally low molecular weight gases and vapors. Missing are studies that utilize a relatively large number of compounds that are liquid at ambient conditions to probe the impact of molecular shape and size on confined fluid properties. Such materials are of great interest in the extraction of oil and gas from shale reservoirs or for the design of selective adsorbents for chemical separation. In this work, we reveal non-intuitive relationships that emerge when comparing bulk fluid properties to those when confined in amorphous silica single-digit nanopores (approx. 5 nm SBA-15), specifically the confined density and self-diffusivity. A counterintuitive result was obtained where larger molecules had relatively faster self-diffusivities; however, this behavior was revealed to be caused by these larger compounds exhibiting a relatively low density when confined. As the prediction of confined fluid properties impacts a diversity of disciplines, the results highlight the need for additional investigations where consistent and large-scale experimental procedures are employed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogen Adsorption in Ultramicroporous Metal–Organic Frameworks Featuring Silent Open Metal Sites

In this work, we utilized an ultramicroporous metal–organic framework (MOF) named [Ni 3 (pzdc) 2 (ade) 2 (H 2 O) 4 ]·2.18H 2 O (where H 3 pzdc represents pyrazole-3,5-dicarboxylic acid and ade represents adenine) for hydrogen (H 2 ) adsorption. Upon activation, [Ni 3 (pzdc) 2 (ade) 2 ] was obtained, and in situ carbon monoxide loading by transmission infrared spectroscopy revealed the generation of open Ni(II) sites. The MOF displayed a Brunauer–Emmett–Teller (BET) surface area of 160 m 2 /g and a pore size of 0.67 nm. Hydrogen adsorption measurements conducted on this MOF at 77 K showed a steep increase in uptake (up to 1.93 mmol/g at 0.04 bar) at low pressure, reaching a H 2 uptake saturation at 2.11 mmol/g at ~0.15 bar. The affinity of this MOF for H 2 was determined to be 9.7 ± 1.0 kJ/mol. In situ H 2 loading experiments supported by molecular simulations confirmed that H 2 does not bind to the open Ni(II) sites of [Ni 3 (pzdc) 2 (ade) 2 ], and the high affinity of the MOF for H 2 is attributed to the interplay of pore size, shape, and functionality.

08 HYDROGEN↗

Customized Chiral Colloids

This contribution describes a synthetic strategy for the fabrication of multicomponent colloidal “molecules” with controllable complex morphologies and compositionally distinct lobes. Using 3-(trimethoxysilyl)propyl methacry-late (TPM) as the building block, the methodology enables a scalable bulk synthesis of customized chiral colloidal particles with geometric and compositional chirality by sequential seeded growth method. Finally, the synthetic protocol presents a versatile platform for constructing colloidal molecules with multiple components having customized shapes and functionalities, with the potential to impact the design of chromatic patchy particles, colloidal swimmers and chiral optical materials, as well as informing programmable assembly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decadal-scale recovery of carbon stocks after wildfires throughout the boreal forests

Boreal forests store 30% of the world's terrestrial carbon (C). Consequently, climate change mediated alterations in the boreal forest fire regime can have a significant impact on the global C budget. Here, we synthesize the effects of forest fires on the stocks and recovery rates of C in boreal forests from 368 plots from 16 long-term (= 100 years) fire chronosequences spread throughout the boreal zone. The mean annual temperature varied from -9.5°C to +5.2°C and annual precipitation from 295 mm to 824 mm in the study sites. Total C stocks decreased on average by 60% (range from <10% to >80%) because of forest fires, primarily due to large declines in the living trees and O-layer C stocks. C emissions of fires ranged from 0.1 to 11.4 kg m-2, and in most cases, the emissions were < 4 kg m-2. Total C stocks increased with time since fire following a sigmoidal shape Gompertz function, and it took 125 years until an average asymptote of 8.1 kg C m-2 was reached. Total C stocks accumulated at a rate of 2–60 g m-2 yr-1 during the first 100 years. We found that potential evapotranspiration (PET) was significantly correlated with C stocks and their post-fire recovery, likely because it integrates temperature, radiation and the length of the growing season. If the fire return interval shortens to under 100 years in the future, this suggests that many boreal forests will be prevented from reaching their full C storage potential. However, our results suggest that climate warming-induced increases in PET may also speed up the post-fire recovery of C stocks.

carbon accumulation, carbon pools, chronosequence,↗

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

Effects of surface charge and cluster size on the electrochemical dissolution of platinum nanoparticles using COMB3 and continuum electrolyte models

We study the site-dependent dissolution of platinum nanoparticles under electrochemical conditions to assess their thermodynamic stability as a function of shape and size using empirical molecular dynamics and electronic-structure models. The third-generation charge optimized many-body potential is employed to determine the validity of uniform spherical representations of the nanoparticles in predicting dissolution potentials (the Kelvin model). To understand the early stages of catalyst dissolution, implicit solvation techniques based on the self-consistent continuum solvation method are applied. It is demonstrated that interfacial charge and polarization can shift the dissolution energies by amounts on the order of 0.74 eV depending on the surface site and nanoparticle shape, leading to the unexpected preferential removal of platinum cations from highly coordinated sites in some cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recycled dark matter

Here, we outline a new production mechanism for dark matter that we dub “recycling”: dark sector particles are kinematically trapped in the false vacuum during a dark phase transition; the false pockets collapse into primordial black holes (PBHs), which ultimately evaporate before Big Bang Nucleosynthesis (BBN) to reproduce the dark sector particles. The requirement that all PBHs evaporate prior to BBN necessitates high scale phase transitions and hence high scale masses for the dark sector particles in the true vacuum. Our mechanism is therefore particularly suited for the production of ultra heavy dark matter (UHDM) with masses above ~10 12 GeV. The correct relic density of UHDM is obtained because of the exponential suppression of the false pocket number density. Recycled UHDM has several novel features: the dark sector today consists of multiple decoupled species that were once in thermal equilibrium and the PBH formation stage has extended mass functions whose shape can be controlled by IR operators coupling the dark and visible sectors.

79 ASTRONOMY AND ASTROPHYSICS↗

Quenching, bursting, and galaxy shapes: colour transformation as a function of morphology

ABSTRACT Different mechanisms for quenching star formation in galaxies are commonly invoked in the literature, but the relative impact of each one at different cosmic epochs is still unknown. In particular, the relation between these processes and morphological transformation remains poorly understood. In this work, we measure the effectiveness of changes in star formation rates by analysing a new parameter, the Star Formation Acceleration (SFA), as a function of galaxy morphology. This methodology is capable of identifying both bursting and quenching episodes that occurred in the preceding 300 Myr. We use morphological classification catalogues based on Deep Learning techniques. Our final sample has ∼14 200 spirals and ∼2500 ellipticals. We find that elliptical galaxies in the transition region have median shorter quenching time-scales (τ < 1 Gyr) than spirals (τ ≥ 1 Gyr). This result conforms to the scenario in which major mergers and other violent processes play a fundamental role in galaxy evolution for most ellipticals, not only quenching star formation more rapidly but also playing a role in morphological transformation. We also find that ∼two-thirds of galaxies bursting in the green valley in our sample are massive spirals ($M_\star \ge 10^{11.0}\, \mathrm{M}_\odot$) with signs of disturbance. This is in accordance with the scenario where low-mass galaxies are losing their gas in an interaction with a massive galaxy: while the former is quenching, the last is being refueled and going through a burst, showing signs of recent interaction.

79 ASTRONOMY AND ASTROPHYSICS↗

Stellar population analysis of MaNGA early-type galaxies: IMF dependence and systematic effects

We study systematics associated with estimating simple stellar population (SSP) parameters – age, metallicity [M/H], α-enhancement [α/Fe], and initial mass function (IMF) shape – and associated M * /L gradients, of elliptical slow rotators (E-SRs), fast rotators (E-FRs), and S0s from stacked spectra of galaxies in the MaNGA survey. These systematics arise from (i) how one normalizes the spectra when stacking; (ii) having to subtract emission before estimating absorption line strengths; (iii) the decision to fit the whole spectrum or just a few absorption lines; (iv) SSP model differences (e.g. isochrones, enrichment, IMF). The MILES+Padova SSP models, fit to the H β , 〈Fe〉, TiO 2SDSS , and [MgFe] Lick indices in the stacks, indicate that out to the half-light radius R e : (a) ages are younger and [α/Fe] values are lower in the central regions but the opposite is true of [M/H]; (b) the IMF is more bottom-heavy in the center, but is close to Kroupa beyond about R e /2; (c) this makes M * /L about 2 × larger in the central regions than beyond R e /2. While the models of Conroy et al. return similar [M/H] and [α/Fe] profiles, the age and (hence) M * /L profiles can differ significantly even for solar abundances and a Kroupa IMF; different responses to non-solar abundances and IMF parametrization further compound these differences. There are clear (model independent) differences between E-SRs, E-FRs, and S0s: younger ages and less enhanced [α/Fe] values suggest that E-FRs and S0s are not SSPs, but relaxing this assumption is unlikely to change their inferred M * /L gradients significantly.

79 ASTRONOMY AND ASTROPHYSICS↗

PDB‐101: Molecular Explorations through Biology and Medicine

PDB‐101 is an online portal for teachers, students, and the general public to promote exploration of the structural biology of proteins and nucleic acids ( pdb101.rcsb.org ). Learning about the diverse shapes and functions of these biological macromolecules helps to understand all aspects of biomedicine and agriculture, from protein synthesis to health and disease to biological energy. Why PDB‐101? Researchers around the world are studying these molecules at the atomic level. These 3D structures are freely available at the Protein Data Bank (PDB), the central storehouse of biomolecular structures. This website builds introductory materials to help beginners get started in the basics of biomolecular structure and function (“101”, as in an entry level course) as well as resources for extended learning. Since 2011, PDB‐101 has been developed by the RCSB PDB , a global resource for the advancement of research and education in biology and medicine. Along with our Worldwide PDB collaborators, RCSB PDB curates, annotates, and makes publicly available the PDB data deposited by scientists around the globe. The RCSB PDB then provides a window to these data through a rich online resource with powerful searching, reporting, and visualization tools for researchers. This information is then streamlined for students and teachers at PDB‐101. Features include the ongoing Molecule of the Month series, educational materials such as paper models, posters, molecular animations, educational curricula and more. The section “Guide to Understanding PDB Data” is a primer for detailed PDB‐specific information: PDB Data, Visualizing Structures, Reading Coordinate Files, scientific methods for structure determination, and more. PDB‐101 also runs annual Video Challenges for high school students. Participants create short videos that tell molecular stories that connect structural biology and medicine. Previous topics have included HIV/AIDS, diabetes, and antimicrobial resistance. The 2022 challenge will focus on Molecular Mechanisms of Cancer. PDB‐101 activities are evaluated using user surveys, feedback from in‐person activities, and website analytics. In 2020, PDB‐101 hosted >850,000 users and >2.6 million page views.

Zardecki, Christine↗

Measurement of event shapes in minimum-bias events from proton-proton collisions at $\sqrt{s}$ = 13

A measurement of event-shape variables is presented, using a data sample produced in a special run with approximately one inelastic proton-proton collision per bunch crossing. The data were collected with the CMS detector at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 64 μ⁢b −1 . A number of observables related to the overall distribution of charged particles in the collisions are corrected for detector effects and compared with simulations. Inclusive event-shape distributions, as well as differential distributions of event shapes as functions of charged-particle multiplicity, are studied. None of the models investigated are able to satisfactorily describe the data. Moreover, there are significant features common amongst all generator setups studied, particularly showing data being more isotropic than any of the simulations. Multidimensional unfolded distributions are provided, along with their correlations.

Chekhovsky, V. [Yerevan Physics Institute]↗

Habitat Affinity of Riverine Dissolved Organic Matter Linked to Molecular Traits

Fluxes of organic matter across Earth habitats shape ecosystem function and carbon storage. Yet, it is challenging to predict howthe molecules are preferentially accumulated in specific habitats, that is, the habitat affinities, due to their diverse character-istics. Here, we develop an indicator of compositional-level habitat affinity for dissolved organic matter (DOM) by quantifyingthe aggregated affinities of individual molecules that are over- or under-represented relative to a reference habitat. Applyingthis indicator to 93 paired riverine water-sediment sites, we find that 65.1% of molecules show non-significant habitat affinitiesfor water or sediment and are thermodynamically favorable and susceptible to microbial degradation. Consistently, the habitataffinities of DOM assemblages decrease with lower molecular weights and recalcitrance for waters, and with higher thermody-namic favorability for sediments. These affinities are both reduced by elevated temperatures and anthropogenic pressures, suchas nitrogen loading and land-use change. Our projection of habitat affinities of global riverine DOM shows that regions withintense anthropogenic disturbances or warm climates, such as East Asia, Western Europe, and the Amazon, tend to exhibit loweraffinities. These findings suggest enhanced molecular homogenization between water and sediment habitats is associated withenvironmental changes and underscore the importance of habitat affinities for predicting the potential trajectories of organiccarbon across ecosystems

Cui, Yifan↗