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At least 343 records · Page 19

Repository scale classification and decomposition of tandem mass spectral data

Various studies have shown associations between molecular features and phenotypes of biological samples. These studies, however, focus on a single phenotype per study and are not applicable to repository scale metabolomics data. Here we report MetSummarizer, a method for predicting (i) the biological phenotypes of environmental and host-oriented samples, and (ii) the raw ingredient composition of complex mixtures. We show that the aggregation of various metabolomic datasets can improve the accuracy of predictions. Since these datasets have been collected using different standards at various laboratories, in order to get unbiased results it is crucial to detect and discard standard-specific features during the classification step. We further report high accuracy in prediction of the raw ingredient composition of complex foods from the Global Foodomics Project.

59 BASIC BIOLOGICAL SCIENCES↗

Inappropriate antibiotic access practices at the community level in Eastern Ethiopia

Access to antibiotic medications is critical to achieving the Sustainable Development Goal for good health and well-being. However, non-prescribed and informal sources are implicated as the most common causes of inappropriate antibiotic access practices, resulting in untargeted therapy, which leads to antibiotic resistance. Hence, knowing antibiotic access practices at the community level is essential to target misuse sources. In this study, 2256 household representatives were surveyed between July and September 2023 to examine their antibiotic access practices. Of 1245 household members who received antibiotics, 45.6% did so inappropriately. Non-prescribed antibiotic access was more common among urban residents and individuals not enrolled in health insurance schemes. This means of antibiotic access was also more common among individuals concerned about distance, drug availability, and healthcare convenience at public facilities. In addition, women and rural individuals were more likely to get antibiotics from unauthorized sources. Unrestricted antibiotic dispensing practices in urban areas enabled their non-prescribed access, while unlicensed providers prevailed with this access practice in rural areas. In this regard, personal behaviors and healthcare-related gaps such as the lack of health insurance, inconvenience, and drug unavailability have led community members to seek antibiotics from unofficial and non-prescribed sources. Targeting the identified behavioral and institutional factors can enhance antibiotic access through prescriptions, hence reducing antibiotic resistance.

60 APPLIED LIFE SCIENCES↗

Anomalous softening of 3D printed elastomeric foam irradiated under compressive strain

Elastomeric foam is an essential component in many industrial and technological settings, primarily as thermal insulators and as positional/mechanical support cushions. In particular, silicone foam is utilized in harsh environments due to exceptional thermal and chemical stability. Under service conditions within certain applications such material gets exposed to a high dosage of gamma radiation, which can permanently alter the material’s structural and mechanical response properties. Most studies on gamma-exposure under inert or oxidative atmosphere indicate hardening of silicone foam, which is attributed to radiation-induced enhancement in chemical cross-linking. Here we report two contrasting effects depending on whether (non-oxidative) radiation exposure is carried out with the foam under zero or finite compressive strain. While in the former case we observe radiation-hardening consistent with previous studies, in the latter case (50% porous foam under 30% uniaxial compression) we see a monotonic decrease in Young’s modulus with increasing dosage, although solvent swelling experiments on the constituent rubber indicate a net increase in cross-link density independent of the state of strain. We quantitatively model all dose-dependent data using the Ogden Hyperfoam strain-energy function within the framework of Tobolsky two-network scheme and attribute the above anomaly to a combined effect of radiation-induced thickness change (compression set) and inherent nonlinearity in the foam’s stress-strain response.

Coarse-grained models↗

Nature's Strongest Force

The strongest force in the universe is called, aptly, the strong force. We never get to witness its fearsome power because it works only across subatomic distances, where it binds quarks together inside protons and neutrons and joins those nucleons into atomic nuclei. Of the four basic forces of nature, the strong force is by far the most potent—it’s 100 trillion trillion trillion times stronger than the force of gravity. Additionally, it’s also the most mysterious.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exploring the kinetics of actinyl–EDTA reduction by ferrous iron using quantum-mechanical calculations

Here, the reduction of An(VI) (An = U, Np, and Pu) to An(IV) significantly decreases its solubility and mobility. This reaction can be hindered by complexation with inorganic (e.g., carbonate) or organic ligands. Ethylenediaminetetraacetic acid (EDTA) is one such organic ligand that forms stable complexes with actinides. Therefore, it may enhance the mobility of actinides. However, the redox kinetics and mechanisms of actinyl (An(V/VI)O 2 +/2+ )–EDTA are not well characterized yet and are thus studied here using quantum-mechanical calculations. The principle is to approach the actinyl–EDTA and Fe 2+ (reductant) in small incremental steps and calculate the system energy at each distance. The overall reaction is then delineated into sub-processes (encounter frequency in bulk solution, formation of outer-sphere complex, transition from outer- to inner-sphere complex, and electron transfer), and reaction rates are determined for each sub-process. The formation of outer-sphere complexes occurs rapidly in microseconds to seconds over a wide range of actinyl concentrations (pM to μM); in contrast, the transition to the inner-sphere complex is relatively slow (milliseconds to a few seconds). Immediate electron transfer to form the pentavalent actinide is observed along the reaction path for Np(VI) and Pu(VI), but not for U(VI). Surprisingly, in acidic conditions, one of the carboxylic groups gets protonated in EDTA of [UO 2 (edta)] 2- rather than one of the amino groups. This process-based series of calculations can be applied to any redox reaction and allows the prediction of changes to the rate law and rate-limiting step in a more fundamental way for different environments

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Programmable chiral states in flocks of active magnetic rollers

Inspired by nature, active matter exemplified by self-organization of motile units into macroscopic structures holds great promise for advanced tunable materials capable of flocking, shape-shifting, and self-healing. Active particles driven by external fields have repeatedly demonstrated potential for complex self-organization and collective behavior, yet how to guide the direction of their collective motion largely remains unexplored. Here, we report a system of microscopic ferromagnetic rollers driven by an alternating magnetic field that demonstrates programmable control of the direction of a self-organized coherent vortical motion (i.e., chirality). Facilitated by a droplet confinement, the rollers get synchronized and display either right- or left-handed spontaneous vortical motion, such that their moving direction determines the vortex chirality. Here, we reveal that one can remotely command a flock of magnetic rollers to switch or maintain its chiral state by modulating a phase shift of the sinusoidal magnetic field powering the active rollers. Building on our findings, we realize a self-assembled remotely controlled micro-pump architecture capable of switching the fluid transport direction on demand. Our studies may stimulate new design strategies for directed transport and flocking robotics at the microscale based on active colloids.

36 MATERIALS SCIENCE↗

Hybrid magnetic nanoparticles as efficient nanoheaters in biomedical applications

Heating at the nanoscale is the basis of several biomedical applications, including magnetic hyperthermia therapies and heat-triggered drug delivery. The combination of multiple inorganic materials in hybrid magnetic nanoparticles provides versatile platforms to achieve an efficient heat delivery upon different external stimuli or to get an optical feedback during the process. However, the successful design and application of these nanomaterials usually require intricate synthesis routes and their magnetic response is still not fully understood. In this review we give an overview of the novel systems reported in the last few years, which have been mostly obtained by organic phase-based synthesis and epitaxial growth processes. Since the heating efficiency of hybrid magnetic nanoparticles often relies on the exchange-interaction between their components, we discuss various interface-phenomena that are responsible for their magnetic properties. Finally, followed by a brief comment on future directions in the field, we outline recent advances on multifunctional nanoparticles that can boost the heating power with light and combine heating and temperature sensing in a single nanomaterial.

36 MATERIALS SCIENCE↗

Fast microflow kinetics and acid catalyst deactivation in glucose conversion to 5-hydroxymethylfurfural

5-Hydroxymethyl furfural (HMF) is an important platform chemical because it can be upgraded to various drop-in and performance-advantaged products. The cascade reaction of HMF production from glucose over a Lewis acid (CrCl 3 ) and a Brønsted acid (HCl) catalyst in aqueous media is investigated in a microreactor at short residence times and high temperatures. We study the formation of various chromium species using UV-visible spectrophotometry and elucidate the Cr(III) speciation. The catalyst reactivity increases sharply at short residence times, and then drops at long times. This indicates that the catalyst treatment plays a vital role in getting optimal reactivity, and recording the catalyst history is necessary. We develop a kinetic model to describe the catalyst speciation as well as the Lewis and Brønsted acid-catalyzed reaction kinetics using a hierarchical approach. Here, the model is in good agreement with experiments. We demonstrate the benefits of tandem Lewis-external added Brønsted acid catalysis in processing time, productivity, and catalyst stability. We apply this model to optimize the HMF yield and obtain ~36% yield at 200 °C in 7 min and report the highest productivity of ~15% yield per min, demonstrating the opportunity of reaching high productivity at short residence times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aqueous-phase effects on ethanol decomposition over Ru-based catalysts

The effects of an aqueous phase on ethanol decomposition for hydrogen production over a Ru(0001) catalyst surface model have been investigated from first principles. Solvent effects on the reaction mechanism and kinetic parameters have been quantified with the help of a microkinetic reactor model, density functional theory, and an implicit solvation scheme (iSMS). Our calculations indicate that in both vapor- and aqueous-phase reaction environments, the ethanol decomposition starts with acetaldehyde formation on the surface, some of which further dehydrogenates to ketenyl species (CHCO), where the C–C bond cleaves to form methylidyne (CH) and CO. In the vapor phase, adsorbed CH gets hydrogenated to methane, and CO desorbs or undergoes methanation reducing the amount of hydrogen produced. In contrast, under aqueous phase reaction conditions, the methanation is inhibited, and the water–gas shift (WGS) reaction is accelerated, leading to complete conversion of CO to CO 2 and H 2 . Furthermore, calculations indicate that the observed reaction behavior under aqueous phase reforming conditions originates primarily from the higher water chemical potential, and implicit solvent models predict only a small solvation effect.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Geometrical picture of the electron–electron correlation at the large- D limit

In electronic structure calculations, the correlation energy is defined as the difference between the mean field and the exact solution of the non relativistic Schrödinger equation. Such an error in the different calculations is not directly observable as there is no simple quantum mechanical operator, apart from correlation functions, that correspond to such quantity. Here, we use the dimensional scaling approach, in which the electrons are localized at the large-dimensional scaled space, to describe a geometric picture of the electronic correlation. Both, the mean field, and the exact solutions at the large-D limit have distinct geometries. Thus, the difference might be used to describe the correlation effect. Moreover, correlations can be also described and quantified by the entanglement between the electrons, which is a strong correlation without a classical analog. Entanglement is directly observable and it is one of the most striking properties of quantum mechanics and bounded by the area law for local gapped Hamiltonians of interacting many-body systems. This study opens up the possibility of presenting a geometrical picture of the electron–electron correlations and might give a bound on the correlation energy. Furthermore, the results at the large-D limit and at D = 3 indicate the feasibility of using the geometrical picture to get a bound on the electron–electron correlations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of radiation damage on the yielding and fracture of nanowires

Irradiated nanowires' strength can change with their diameter. Though damaged by radiation, defects get cleaned during loading, returning the nanowires to their pristine state. This suggests that radiation has little impact on their fracture behavior.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗

Topological perturbation to a standard dehydrogenation catalyst, Pt 3 Sn

Topological materials, which exhibit protected topological surface states (TSS) near the Fermi level, have been proposed to be good catalysts. Topological catalysis may be more prevalent than we suspect, and not limited to exotic new materials. Here we study a known dehydrogenation catalyst, Pt 3 Sn alloy, which happens to be a topological semimetal, and probe the participation of TSSs in catalytic dehydrogenation of methane catalyzed by this material. Through first principle modeling and detailed analysis of the electronic structure for topological and non-topological surfaces of Pt 3 Sn, we find that TSS get significantly altered by the binding of reaction intermediates, particularly H. However, this effect of TSS on the binding of the reagents is merely perturbative, as the majority of the adsorbate binding is achieved by not-surface-focused electronic states, located much deeper below the Fermi level. Therefore, the reaction energetics and selectivity are predominantly determined by electronic states other than TSS. The fact that TSS are available for the reagent binding does not alone guarantee that the catalysis is strongly driven by TSS. However, TSS are not to be ignored, as small changes in the energetics along the reaction profile can translate into substantial differences in the reaction rate. Hence, in our view, Pt 3 Sn – a topological material – is first and foremost a standard catalyst, with added topological features, and not purely a topological catalyst. Our results point at the need to carefully consider all the bonding effects at the topological material interface.

Chemistry↗

The possibility of hydrogen-water demixing in Uranus, Neptune, K2-18 b and TOI-270 d

Context. The internal structures of Uranus and Neptune remain unknown. In addition, sub-Neptunes are now thought to be the most common type of exoplanets. Improving our understanding of the physical processes that govern the interiors of such planets is therefore essential. Phase separation between planetary constituents may occur, in particular, hydrogen-water immiscibility in cold, water-rich intermediate-mass planets. Aims. We assess whether hydrogen-water demixing could occur in Uranus, Neptune, K2-18 b and TOI-270 d, and investigate its effect on the planetary evolution and inferred internal structure. Methods. We couple planetary evolution models with recent ab initio calculations of the hydrogen-water phase diagram, allowing for temperature shifts to account for uncertainties in miscibility gaps. Results. We find that demixing may occur and could lead to a complete depletion of water in the outermost regions of Uranus and Neptune. Temperature offsets of up to 1100 K lead to a depleted region comprising as much as 16% of the planet’s mass, and an increase in planetary radius by nearly 20%. For K2-18 b, our models suggest that hydrogen-water demixing is ongoing and may explain the absence of water features in its JWST spectrum. A temperature offset of 500 K is required to get a complete depletion of water in the atmosphere of K2-18b. TOI-270d may also have experienced hydrogen-water demixing. When applying a similar temperature offset on the phase diagram as for K2-18 b, we find a partial depletion of water in the atmosphere of TOI-270 d, consistent with JWST’s detection of water. Conclusions. Hydrogen-water immiscibility may play a key role in shaping the structure and evolution of both Solar System giant planets like Uranus and Neptune, and cold/temperate exoplanets such as K2-18 b and TOI-270 d. Accounting for such internal processes is crucial to accurately interpret atmospheric observations from current (e.g., JWST) and upcoming (e.g., ARIEL) missions.

planets and satellites: composition↗

Measured Indoor Nitrogen Oxides in Homes with a Child with Asthma and Gas or Induction Electric Cooking

The Cooking Energy and Ventilation Impacts on Children's Asthma (CEVICA) study is a randomized control trial investigating the effects of replacing gas with induction electric ranges in the homes of children with asthma in California's San Joaquin Valley. Indoor air quality parameters and respiratory health indicators were measured over 2-week intensive at Baseline and after consecutive 3-month study phases, with half getting electric cooking at the start of Phase 1 and others in Phase 2. Indoor air measurements included time-integrated NO 2 and NO X by passive sampler and time-resolved NO 2 by electrochemical sensors. In the first 40 homes, data were collected during 61 intensives for gas cooking and 55 for induction. Cooking was identified using temperature sensors above the cooktop. Pollutant events were identified from sharp rises in concentrations Time integrated NOX species were lower with electric cooking, with mean differences of 14.2 ppb for NO 2 (95% CI: 9.6, 18.7; p < 0.001), 55.6 ppb for NO X (95% CI: 30.4, 80.9; p < 0.001), and 41.5 ppb for derived NO (95% CI: 19.7, 63.2; p < 0.001). A paired, within home analysis showed larger reductions in Group 2 (gas to induction) than Group 1 that remained electric across Phase 1 and Phase 2 for NO 2 (mean difference in As of 10.5 ppb; 95% CI: 5.6, 15.4; p < 0.001), NO X (32.3 ppb; 95% CI: 10.0, 54.5; p=0.007), and derived NO (21.8 ppb; 95% CI: 3.6, 40.0; p=0.022). Compared to electric cooking, gas had much higher rates of associated NO 2 events, and larger above-baseline NO 2 peaks. These preliminary results are consistent with prior findings that shifting to induction cooking can substantially lower indoor NO 2 compared with gas cooking.

Fang, Yi↗

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Yu, Haiwang↗

Green’s function coupled cluster simulation of the near-valence ionizations of DNA-fragments

Accurate description of the ionization process in DNA is crucial to the understanding of the DNA damage under exposure to ionizing radiation and the exploration of the potential application of DNA strands in nanoelectronics. In this work, by employing our recently developed Green’s function coupled-cluster library on supercomputing facilities, we have studied the spectral functions of several guanine–cytosine (G–C) base pair structures ([G–C]n, n = 1–3) for the first time in a relatively broad near-valence regime ([−25.0, −5.0] eV) in the coupled-cluster with singles and doubles level. Our focus is to give a preliminary many-body coupled-cluster understanding and guideline of the vertical ionization energy (VIE), spectral profile, and ionization feature changes of these systems as the system size expands in this near-valence regime. The results show that, as the system size expands, even though the lowest VIEs keep decreasing, the changes of spectral function profile and the relative peak positions get unexpectedly smaller. Further analysis of the ionized states associated with the most intensive peak in the spectral functions reveals non-negligible |2h, 1p⟩’s in the ionized wave functions of the considered G–C base pair systems. The leading |2h, 1p⟩’s associated with the main ionizations from the cytosine part of the G–C base pairs feature a transition from the intra-base-pair cytosine π → π* excitation to the inter-base-pair electron excitation as the size of G–C base pairs expands, which also indicates the minimum quantum region in the many-body calculations of DNA systems.

Peng, Bo (ORCID:0000000242267294)↗