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At least 775 records · Page 43

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. Here are the results: We present individual model statistics to demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. In conclusion, it is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.

09 BIOMASS FUELS↗

Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic parameters of the system.

54 ENVIRONMENTAL SCIENCES↗

Open source implementation of glued sphere discrete element method and nonspherical biomass fast pyrolysis simulation

Here, in this research, a glued-sphere Discrete Element Method (DEM) method was implemented in the open-source, Computational Fluid Dynamics (CFD) software MFiX. The implementation was verified using a cylinder-wall collision and then validated by simulating the packing and fluidization of non-spherical particles. The validated code was applied to simulate fast pyrolysis of non-spherical biomass particles in a bubbling fluidized bed. The glued sphere occupancy ratio was proposed to quantify the quality of shape resolution using glued sphere. Shape resolution showed significant influence on the packing height in the simulation of particle packing and an occupancy ratio of 80 % was recommended. Its influence is minor in fully fluidized bed but can be 8 times higher in fixed fluidized bed. Three tested heat transfer models predicted similar yields of elongated biomass fast pyrolysis. The solver developed in this research can be used to simulate other multiphase reacting flows involving non-spherical particles.

42 ENGINEERING↗

Search for resonant $ \mathrm{t}\overline{\mathrm{t}} $ production in proton-proton collisions at $ \sqrt{s}=13 $ TeV

A search for a heavy resonance decaying into a top quark and antiquark $ \left(\mathrm{t}\overline{\mathrm{t}}\right) $ pair is performed using proton-proton collisions at $ \sqrt{s}=13 $ TeV. The search uses the data set collected with the CMS detector in 2016, which corresponds to an integrated luminosity of 35.9 fb$^{–1}$. The analysis considers three exclusive final states and uses reconstruction techniques that are optimized for top quarks with high Lorentz boosts, which requires the use of nonisolated leptons and jet substructure techniques. No significant excess of events relative to the expected yield from standard model processes is observed. Upper limits on the production cross section of heavy resonances decaying to a $ \mathrm{t}\overline{\mathrm{t}} $ pair are calculated. Limits are derived for a leptophobic topcolor Z$^{'}$ resonance with widths of 1, 10, and 30%, relative to the mass of the resonance, and exclude masses up to 3.80, 5.25, and 6.65 TeV, respectively. Kaluza-Klein excitations of the gluon in the Randall-Sundrum model are excluded up to 4.55 TeV. To date, these are the most stringent limits on $ \mathrm{t}\overline{\mathrm{t}} $ resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Forbidden scalar dark matter and dark Higgses

As experimental searches for WIMP dark matter continue to yield null results, models beyond the WIMP paradigm have proliferated in order to elude ever improving observational constraints, among them that of sub-GeV dark matter mediated by a massive vector portal (a dark photon) associated with a new dark U(1) gauge symmetry. It has been previously noted that for a significant range of the parameter space of this class of models, the annihilation of dark matter particles into a pair of dark photons can dominate the freeze-out process even when this process is kinematically forbidden for dark matter at rest — this is known as the “forbidden dark matter” (FDM) regime. Prior studies of this regime, however, assume that any “dark Higgs” associated with breaking the dark U(1) and imparting mass to the dark photon is decoupled from the dark matter and as such plays no role in the freeze-out process. In this paper, we explore the effects of a dark Higgs on sub-GeV dark matter phenomenology in this FDM regime by considering the simplest possible construction in which there exist non-trivial dark matter-dark Higgs couplings: a model with a single complex scalar DM candidate coupled directly to the dark Higgs field. We find that for a wide range of parameter space, the dark Higgs can alter the resulting relic abundance by many orders of magnitude, and that this effect can remain significant even for a small dark matter-dark Higgs coupling constant. Considering measurements from direct detection and measurements of the CMB, we further find that points in this model’s parameter space which recreate the appropriate dark matter relic abundance suffer only mild constraints from other sources at present, but may become accessible in near-future direct detection experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Search for natural and split supersymmetry in proton-proton collisions at $ \sqrt{s}=13 $ TeV in final states with jets and missing transverse momentum

A search for supersymmetry (SUSY) is performed in final states comprising one or more jets and missing transverse momentum using data from proton-proton collisions at a centre-of-mass energy of 13 TeV. The data were recorded with the CMS detector at the CERN LHC in 2016 and correspond to an integrated luminosity of 35.9 fb$^{−1}$. The number of signal events is found to agree with the expected background yields from standard model processes. The results are interpreted in the context of simplified models of SUSY that assume the production of gluino or squark pairs and their prompt decay to quarks and the lightest neutralino. The masses of bottom, top, and mass-degenerate light-flavour squarks are probed up to 1050, 1000, and 1325 GeV, respectively. The gluino mass is probed up to 1900, 1650, and 1650 GeV when the gluino decays via virtual states of the aforementioned squarks. The strongest mass bounds on the neutralinos from gluino and squark decays are 1150 and 575 GeV, respectively. The search also provides sensitivity to simplified models inspired by split SUSY that involve the production and decay of long-lived gluinos. Values of the proper decay length cτ$_{0}$ from 10$^{−3}$ to 10$^{5}$ mm are considered, as well as a metastable gluino scenario. Gluino masses up to 1750 and 900 GeV are probed for cτ$_{0}$ = 1 mm and for the metastable state, respectively. The sensitivity is moderately dependent on model assumptions for cτ$_{0}$ ≳ 1 m. The search provides coverage of the cτ$_{0}$ parameter space for models involving long-lived gluinos that is complementary to existing techniques at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for the associated production of the Higgs boson and a vector boson in proton-proton collisions at $ \sqrt{s} $ = 13 TeV via Higgs boson decays to τ leptons

A search for the standard model Higgs boson, decaying to a pair of $\tau$ leptons and produced in association with a W or a Z boson is performed. A data sample of proton-proton collisions collected at $\sqrt{s} =$ 13 TeV by the CMS experiment at the CERN LHC is used, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The signal strength is measured relative to the expectation for the standard model Higgs boson, yielding $\mu =$ 2.5$^{+1.4} _{-1.3}$. These results are combined with earlier CMS measurements targeting Higgs boson decays to a pair of $\tau$ leptons, performed with the same data set in the gluon fusion and vector boson fusion production modes. The combined signal strength is $\mu =$ 1.24$ ^{+0.29} _{-0.27}$ (1.00$^{+0.24} _{-0.23}$ expected), and the observed significance is 5.5 standard deviations (4.8 expected) for a Higgs boson mass of 125 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Improved multifidelity Monte Carlo estimators based on normalizing flows and dimensionality reduction techniques

Here, we study the problem of multifidelity uncertainty propagation for computationally expensive models. In particular, we consider the general setting where the high-fidelity and low-fidelity models have a dissimilar parameterization both in terms of number of random inputs and their probability distributions, which can be either known in closed form or provided through samples. We derive novel multifidelity Monte Carlo estimators which rely on a shared subspace between the high-fidelity and low-fidelity models where the parameters follow the same probability distribution, i.e., a standard Gaussian. We build the shared space employing normalizing flows to map different probability distributions into a common one, together with linear and nonlinear dimensionality reduction techniques, active subspaces and autoencoders, respectively, which capture the subspaces where the models vary the most. We then compose the existing low-fidelity model with these transformations and construct modified models with an increased correlation with the high-fidelity model, which therefore yield multifidelity estimators with reduced variance. A series of numerical experiments illustrate the properties and advantages of our approaches.

97 MATHEMATICS AND COMPUTING↗

A Deep Look Into the Future of Quantitative Imaging in Oncology: A Statement of Working Principles and Proposal for Change

The adoption of enterprise digital imaging, along with the development of quantitative imaging methods and the re-emergence of statistical learning, has opened the opportunity for more personalized cancer treatments through transformative data science research. In the last 5 years, accumulating evidence has indicated that noninvasive advanced imaging analytics (i.e., radiomics) can reveal key components of tumor phenotype for multiple lesions at multiple time points over the course of treatment. Many groups using homegrown software have extracted engineered and deep quantitative features on 3-dimensional medical images for better spatial and longitudinal understanding of tumor biology and for the prediction of diverse outcomes. These developments could augment patient stratification and prognostication, buttressing emerging targeted therapeutic approaches. Unfortunately, the rapid growth in popularity of this immature scientific discipline has resulted in many early publications that miss key information or use underpowered patient data sets, without production of generalizable results. Quantitative imaging research is complex, and key principles should be followed to realize its full potential. The fields of quantitative imaging and radiomics in particular require a renewed focus on optimal study design and reporting practices, standardization, interpretability, data sharing, and clinical trials. Standardization of image acquisition, feature calculation, and statistical analysis (i.e., machine learning) are required for the field to move forward. A new data-sharing paradigm enacted among open and diverse participants (medical institutions, vendors and associations) should be embraced for faster development and comprehensive clinical validation of imaging biomarkers. In this review and critique of the field, we propose working principles and fundamental changes to the current scientific approach, with the goal of high-impact research and development of actionable prediction models that will yield more meaningful applications of precision cancer medicine.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Ab initio informed 20 Ne(p, pα) 16 O reaction elucidates the emergence of alpha clustering from chiral potentials

We report on the first ab initio informed α knock-out reaction in the intermediate-mass region, with the aim to probe the underlying chiral potential and its impact on the emergence of alpha clustering in this mass region. The theoretical predictions of the α+ 16 O clustering in the 20 Ne ground state, based on the ab initio symmetry-adapted no-core shell model with continuum, yield a triple differential cross section for 20 Ne(p, pα) 16 O that is in a remarkable agreement with the data. This allows us to examine predictions of surface and in-medium α-cluster features that emerge from the underlying realistic nucleon-nucleon interaction with no parameters fitted to nuclear data beyond the two-body system, and to compare these to the successful antisymmetrized molecular dynamics approach.

Sargsyan, G. H. [Michigan State Univ., East Lansin↗

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION↗

Self-Assembled Monolayers of n-Alkanethiols Suppress Hydrogen Evolution and Increase the Efficiency of Rechargeable Iron Battery Electrodes

Iron-based rechargeable batteries, because of their low cost, eco-friendliness, and durability, are extremely attractive for large-scale energy storage. A principal challenge in the deployment of these batteries is their relatively low electrical efficiency. The low efficiency is due to parasitic hydrogen evolution that occurs on the iron electrode during charging and idle stand. In this study, we demonstrate for the first time that linear alkanethiols are very effective in suppressing hydrogen evolution on alkaline iron battery electrodes. The alkanethiols form self-assembled monolayers on the iron electrodes. The degree of suppression of hydrogen evolution by the alkanethiols was found to be greater than 90%, and the effectiveness of the alkanethiol increased with the chain length. Through steady-state potentiostatic polarization studies and impedance measurements on high-purity iron disk electrodes, we show that the self-assembly of alkanethiols suppressed the parasitic reaction by reducing the interfacial area available for the electrochemical reaction. We have modeled the effect of chain length of the alkanethiol on the surface coverage, charge-transfer resistance, and double-layer capacitance of the interface using a simple model that also yields a value for the interchain interaction energy. We have verified the improvement in charging efficiency resulting from the use of the alkanethiols in practical rechargeable iron battery electrodes. The results of battery tests indicate that alkanethiols yield among the highest faradaic efficiencies reported for the rechargeable iron electrodes, enabling the prospect of a large-scale energy storage solution based on low-cost iron-based rechargeable batteries.

Malkhandi, S↗

Structural visualization of transcription activated by a multidrug-sensing MerR family regulator

Bacterial RNA polymerase (RNAP) holoenzyme initiates transcription by recognizing the conserved –35 and –10 promoter elements that are optimally separated by a 17-bp spacer. The MerR family of transcriptional regulators activate suboptimal 19–20 bp spacer promoters in response to myriad cellular signals, ranging from heavy metals to drug-like compounds. The regulation of transcription by MerR family regulators is not fully understood. Here we report one crystal structure of a multidrug-sensing MerR family regulator EcmrR and nine cryo-electron microscopy structures that capture the EcmrR-dependent transcription process from promoter opening to initial transcription to RNA elongation. These structures reveal that EcmrR is a dual ligand-binding factor that reshapes the suboptimal 19-bp spacer DNA to enable optimal promoter recognition, sustains promoter remodeling to stabilize initial transcribing complexes, and finally dissociates from the promoter to reverse DNA remodeling and facilitate the transition to elongation. Our findings yield a comprehensive model for transcription regulation by MerR family factors and provide insights into the transition from transcription initiation to elongation.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating technology upgrades as a complement to traditional bill assistance programs

State programs to improve energy affordability and reduce energy burden (the share of income spent on energy) could mitigate concerns about rising electricity prices. Many states offer bill assistance and rebates for weatherization and rooftop solar to income-qualifying households. Here, we analyse how these approaches may complement one another to improve energy affordability. Results illustrate trade offs between program costs and energy burden reduction, as well as between a program’s upfront and ongoing costs. Generally, the three strategies complement one another to improve energy affordability at lower net present cost than bill assistance alone, with varying effects across regions. Weatherization can reduce the solar installation capacity needed, and both together can reduce or eliminate ongoing reliance on bill assistance. Under full uptake among cost-effective households, fully rebated weatherization and solar rebated at $0.48/Watt, combined with bill assistance, yield the same modelled net present cost as bill assistance alone while reducing the share of low-income owner-occupied households with high energy burdens from 66% to 19%, compared with 34% under bill assistance alone. Absent tax credits, weatherization still reduces energy burden and bill assistance program costs, whereas solar may not be cost-competitive.

Forrester, Sydney P↗

Planar thermal Hall effect of topological bosons in the Kitaev magnet α-RuCl 3

The honeycomb magnet α-RuCl 3 has attracted considerable interest because it is proximate to the Kitaev Hamiltonian whose excitations are Majoranas and vortices. The thermal Hall conductivity κ xy of Majorana fermions is predicted to be half-quantized. Half-quantization of κxy/T (T, temperature) was recently reported, but this observation has proven difficult to reproduce. Here, we report detailed measurements of κ xy on α-RuCl3 with the magnetic field B ∥ a (zigzag axis). In our experiment, κ xy /T is observed to be strongly temperature dependent between 0.5 and 10 K. We show that its temperature profile matches the distinct form expected for topological bosonic modes in a Chern-insulator-like model. Our analysis yields magnon band energies in agreement with spectroscopic experiments. At high B, the spin excitations evolve into magnon-like modes with a Chern number of ~1. In conclusion, the bosonic character is incompatible with half-quantization of κ xy /T.

36 MATERIALS SCIENCE↗

Cross sections of 147–149 Sm( 6 Li,x) reactions for the production of 149 Tb for targeted alpha therapy

Terbium-149g (t 1/2 = 4.12 h) is of particular interest for targeted alpha therapy cancer treatment due to its ability to decay via both alpha and positron emission, making it a potential theranostic nuclide. Due to many challenges facing its production, there are limited facilities worldwide that have demonstrated the ability to produce this nuclide in quantities sufficient for medical research. Since the Cyclotron Institute at Texas A&M University is a specialized accelerator facility capable of accelerating a wide variety of ions, we are investigating production pathway options. One of the major challenges facing its production is the known co-production of the excited isomeric state, 149m Tb (t 1/2 = 4.1 min). However, this state does not decay to the ground state of 149g Tb, negating any potential contribution to its yield. Due to its short-half life, the cross section for the population of this state has never been measured. After calculating several potential reaction yields using predictive models, the reactions of 147–149 Sm( 6 Li,xn) 149 Tb were identified as candidates. Lithium-6 beams of varied energies between 45-65 MeV were impinged on enriched 147 Sm, 148 Sm, and 149 Sm targets at the Cyclotron Institute at Texas A&M University, and the reaction products were measured immediately following irradiation using high-purity germanium detectors, enabling detection of both 149m Tb and 149g Tb. Cross sections for all nuclides produced in sufficient activity in these reactions were also measured and reported here. We conclude that the population of 149m Tb is much preferred over population of the ground state for these 6 Li-induced reactions, and it is necessary to explore other options for 149g Tb production.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The DEHVILS in the details: Type Ia supernova Hubble residual comparisons and mass step analysis in the near-infrared

Measurements of type Ia supernovae (SNe Ia) in the near-infrared (NIR) have been used both as an alternate path to cosmology compared to optical measurements and as a method of constraining key systematics for the larger optical studies. With the DEHVILS sample, the largest published NIR sample with consistent NIR coverage of maximum light across three NIR bands ( Y, J , and H ), we check three key systematics: (i) the reduction in Hubble residual scatter as compared to the optical, (ii) the measurement of a “mass step” or lack thereof and its implications, and (iii) the ability to distinguish between various dust models by analyzing slopes and correlations between Hubble residuals in the NIR and optical. We produce SN Ia simulations of the DEHVILS sample and find that it is harder to differentiate between various dust models than previously understood. Additionally, we find that fitting with the current SALT3-NIR model does not yield accurate wavelength-dependent stretch-luminosity correlations, and we propose a limited solution for this problem. From the data, we see that (i) the standard deviation of Hubble residual values from NIR bands treated as standard candles are 0.007–0.042 mag smaller than those in the optical, (ii) the NIR mass step is not constrainable with the current sample size of 47 SNe Ia from DEHVILS, and (iii) Hubble residuals in the NIR and optical are correlated in the data. We test a few variations on the number and combinations of filters and data samples, and we observe that none of our findings or conclusions are significantly impacted by these modifications.

Astronomy & Astrophysics↗