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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 ( https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Metabolic Costs of Walking with Weighted Vests

ABSTRACT Introduction The US Army Load Carriage Decision Aid (LCDA) metabolic model is used by militaries across the globe and is intended to predict physiological responses, specifically metabolic costs, in a wide range of dismounted warfighter operations. However, the LCDA has yet to be adapted for vest-borne load carriage, which is commonplace in tactical populations, and differs in energetic costs to backpacking and other forms of load carriage. Purpose The purpose of this study is to develop and validate a metabolic model term that accurately estimates the effect of weighted vest loads on standing and walking metabolic rate for military mission-planning and general applications. Methods Twenty healthy, physically active military-age adults (4 women, 16 men; age, 26 ± 8 yr old; height, 1.74 ± 0.09 m; body mass, 81 ± 16 kg) walked for 6 to 21 min with four levels of weighted vest loading (0 to 66% body mass) at up to 11 treadmill speeds (0.45 to 1.97 m·s −1 ). Using indirect calorimetry measurements, we derived a new model term for estimating metabolic rate when carrying vest-borne loads. Model estimates were evaluated internally byk-fold cross-validation and externally against 12 reference datasets (264 total participants). We tested if the 90% confidence interval of the mean paired difference was within equivalence limits equal to 10% of the measured walking metabolic rate. Estimation accuracy, precision, and level of agreement were also evaluated by the bias, standard deviation of paired differences, and concordance correlation coefficient (CCC), respectively. Results Metabolic rate estimates using the new weighted vest term were statistically equivalent (P< 0.01) to measured values in the current study (bias, −0.01 ± 0.54 W·kg −1 ; CCC, 0.973) as well as from the 12 reference datasets (bias, −0.16 ± 0.59 W·kg −1 ; CCC, 0.963). Conclusions The updated LCDA metabolic model calculates accurate predictions of metabolic rate when carrying heavy backpack and vest-borne loads. Tactical populations and recreational athletes that train with weighted vests can confidently use the simplified LCDA metabolic calculator provided as Supplemental Digital Content to estimate metabolic rates for work/rest guidance, training periodization, and nutritional interventions.

Sport Sciences↗
NASA NTRSDate not supplied

Thermoplastic Composite Aircraft Manufacturing Model

A manufacturing process to produce 80 single aisle sized thermoplastic composite aircraft a month is presented. Within the Hi-Rate Composite Aircraft Manufacturing (HiCAM) program a baseline aircraft fuselage was designed and modeled based on the Boeing 787 one-piece barrel build, but scaled down to a single aisle aircraft. Key Performance Parameters (KPPs) of recurring cost, non-recurring cost, and weight are calculated from the model. The outcome of this simulation indicated a prohibitively high non-recurring cost, so the thermoplastic team modeled the manufacturing flow for a panelized fuselage concept. The minimum success criteria is a 30% cost reduction and less than two percent increase in weight compared to the baseline aircraft. Automated Fiber Placement (AFP) is used to layup skins, stamp forming is used to make body frames, stringers, and passenger door surround parts. In the model, Co-Fusion was used to consolidate the skin while simultaneously welding on stringers to make stiffened panels. Additional welding technologies were considered to minimize fastener use and a vertical build concept was used for final assembly to reduce factory size. This manufacturing concept for a thermoplastic aircraft indicated a 39% cost and 12% weight savings compared to the baseline. Additional trade studies were conducted using Northrop Grumman’s Automated Stiffener Forming technology to make stringers and stamp forming instead of AFP to make skins.

thermoplastic composites↗
NASA NTRS2019

Modeling of Tunable Elastic Ultralight Aircraft

Aircraft weight is one of the most critical factors in the design and operation of modern vehicles. The ability to integrate ultra-light materials into the primary load bearing structures has the potential to reduce aircraft weight significantly. Ultralight materials tend to be lattice-based meta-materials that are difficult and computationally expensive to model. One of the advantages of meta-materials is to be able to tune or "program" their bulk material properties through the placement of heterogeneous components in the material. A large amount of time devoted to the simulation in the development time for the tuning of the material can be a barrier to the adoption of large scale lattice materials. In this paper, we present a workflow and analysis tool-set to provide first-order estimates for rapid development of engineered lattice materials for aerospace applications. We present results for estimating the displacement and maximum structural stresses.

cellular solids↗
DOE OSTI2022

Determining critical overlap concentration of polyethylene oxide to support excipient safety assessment of opioid products

Intravenous administration of abuse-deterrent opioid products poses high safety risks, in part due to the presence of high molecular weight polymeric excipients. Previous in vivo studies in animal models have shown that the higher molecular weight (Mw) polymeric excipients like polyethylene oxide (PEO) were directly linked to such adverse responses as intravenous hemolysis and kidney damage. PEO polymers have been widely used in abuse-deterrent formulations (ADF) of opioid products, adding to concerns over the general safety of the opioid category due to the unknown safety risk from abuse via unintended routes. Here, the current study focused on the determination of the critical overlap concentration (c*) at various PEO molecular weights to aid in explaining differences in observed adverse responses from previous animal studies on the intravenous administration of PEO solutions. Adverse in vivo responses may be related to the viscoelastic regime of the polymer solution, which depends not only on Mw but also on concentration. Having a localized polymer concentration in the blood above the c*, i.e., the transition from the dilute to semi-dilute entangled viscoelastic regime, may influence the flow behavior and interactions of cells in the blood. The relationship of c* to this combination of physical, chemical, and rheological effects is a possible driving force behind adverse in vivo responses.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Thermoplastic Aircraft Manufacturing Model

A manufacturing process to produce 80 single aisle sized thermoplastic composite aircraft a month is presented. Within the Hi-Rate Composite Aircraft Manufacturing (HiCAM) program a baseline aircraft fuselage was designed and modeled based on the Boeing 787 one-piece barrel build, but scaled down to a single aisle aircraft. Key Performance Parameters (KPPs) of recurring cost, non-recurring cost, and weight are calculated from the model. The outcome of this simulation indicated a prohibitively high non-recurring cost, so the thermoplastic team modeled the manufacturing flow for a panelized fuselage concept. The minimum success criteria is a 30% cost reduction and less than two percent increase in weight compared to the baseline aircraft. Automated Fiber Placement (AFP) is used to layup skins, stamp forming is used to make body frames, stringers, and passenger door surround parts. In the model, Co-Fusion was used to consolidate the skin while simultaneously welding on stringers to make stiffened panels. Additional welding technologies were considered to minimize fastener use and a vertical build concept was used for final assembly to reduce factory size. This manufacturing concept for a thermoplastic aircraft indicated a 39% cost and 12% weight savings compared to the baseline. Additional trade studies were conducted using Northrop Grumman’s Automated Stiffener Forming technology to make stringers and stamp forming instead of AFP to make skins.

thermoplastic composites↗
DOE OSTI2020

Online adaptive basis refinement and compression for reduced-order models via vector-space sieving

In many applications, projection-based reduced-order models (ROMs) have demonstrated the ability to provide rapid approximate solutions to high-fidelity full-order models (FOMs). However, there is no a priori assurance that these approximate solutions are accurate; their accuracy depends on the ability of the low-dimensional trial basis to represent the FOM solution. As a result, ROMs can generate inaccurate approximate solutions, e.g., when the FOM solution at the online prediction point is not well represented by training data used to construct the trial basis. To address this fundamental deficiency of standard model-reduction approaches, this work proposes a novel online-adaptive mechanism for efficiently enriching the trial basis in a manner that ensures convergence of the ROM to the FOM, yet does not incur any FOM solves. The mechanism is based on the previously proposed adaptive $h$-refinement method for ROMs, but improves upon this work in two crucial ways. First, the proposed method enables basis refinement with respect to any orthogonal basis (not just the Kronecker basis), thereby generalizing the refinement mechanism and enabling it to be tailored to the physics characterizing the problem at hand. Second, the proposed method provides a fast online algorithm for periodically compressing the enriched basis via an efficient proper orthogonal decomposition (POD) method, which does not incur any operations that scale with the FOM dimension. We report these two features allow the proposed method to serve as (1) a failsafe mechanism for ROMs, as the method enables the ROM to satisfy any prescribed error tolerance online (even in the case of inadequate training), and (2) an efficient online basis-adaptation mechanism, as the combination of basis enrichment and compression enables the basis to adapt online while controlling its dimension.

42 ENGINEERING↗
DOE OSTI2020

Best Practices for Shielding Analyses of Activated Metals and Spent Resins from Reactor Operation

This report investigated best practices for performing shielding evaluations of Type B waste packages, as defined in 10 CFR Part 71 regulations on packaging and transportation of radioactive material, or packages for which the contents are not defined before loading and may include a broad range of nuclides, geometries, and non-fuel materials. The following non-fuel waste streams were analyzed: Activated metals from decommissioned commercial power reactors, including Type 304 stainless steel, reactor vessel steel, and Inconel, Control blades from boiling water reactors, Neutron-activated corrosion products on surfaces of activated metals, and Spent resins from power plant operations. Measured elemental compositions, including major constituents and impurities, for steel and Inconel samples from commercial power reactors were used in activation calculations to determine radionuclide inventories in activated metals. For a simplified cask model, 60 Co contribution to the total external package dose rate at 30 days after shutdown varied from approximately 60% to 95%, depending on the activated metal, initial cobalt impurity concentration in the metal, and the thickness of the overpack gamma shield. Its maximum contribution to the total external package dose rate of approximately 100% was reached within the time interval of 2 to 5 years after shutdown and was maintained for up to 45 to 60 years after shutdown, depending on material, initial cobalt impurity concentration, and shield thickness. Thereafter, the 60 Co contribution to external package dose rate decreased with increasing decay time. Cobalt-60 is primarily produced by neutron reactions with the cobalt impurity in steel and Inconel. Other important radionuclides in activated metals contributing to package external dose rate are radionuclides with relatively short decay times, including 51 Cr, 59 Fe, 58 Co, and 54 Mn. These radionuclides may be represented as an equivalent 60 Co activity/source because 60 Co gamma ray emissions are bounding in terms of source strength and energy to other important radionuclides identified in the analyzed activated metals. Approaches for modeling the neutron-activated corrosion products that may be attached to activated reactor components were analyzed in this report. It was demonstrated that a surface source is more conservative than a uniform volumetric source for the treatment of neutron-activated corrosion products with respect to external package dose rates. An analysis of the maximum radionuclide loadings reported on spent resins identified the radionuclides 137 Cs, 60 Co, 134 Cs, 65 Zn, and 58 Co as the primary contributors to external package dose rate. For a resin cooled for 3.08 years, the external package dose rate was entirely produced by the reported 137 Cs and 60 Co inventory. The neutron sources from actinides found on spent resins or activated metals produced negligible dose rates and may be ignored in dose rate analyses. Effects of idealized waste material, source geometry, and spatial material/source distributions on external package dose rates were determined based on dose rate results for a simplified cask model under normal conditions of transport. Type 304 stainless steel, zirconium, and aluminum with adjusted mass densities based on a maximum content weight were analyzed for material modeling effects on external package dose rate. These materials produced identical external package dose rates within the statistical uncertainties of the dose rate estimates. Among four different source geometry configurations with homogeneous material of different mass densities, uniform volumetric source distribution, and the same source strength, the geometry configuration with lowest mass density (i.e., minimum self-shielding effect among the four cases) was most conservative. Spatial source distributions that better represent localized peak 60 Co activity values were more conservative than a uniform volumetric source distribution, assuming the same weight and total source strength per package. The increase in external dose rate caused by localized source peaks can be as much as the ratio between source peak activity density to average activity density, depending on the location of the activated metal with peak activity density. Therefore, the shielding analysis may be simplified if localized peak activities and the average activity per package can be measured/determined and documented at the time of cask loading. For simplicity, external package dose rates may be determined based on average source activity and a uniform volumetric source distribution. The dose rate results from that calculation model multiplied by the ratio of peak activity density to average activity density will produce maximum dose rate values for conservative estimates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Hundness versus Mottness in a three-band Hubbard–Hund model: On the origin of strong correlations in Hund metals☆

Hund metals are multi-orbital systems with moderate Coulomb interaction, U, among charges and sizeable Hund’s rule coupling, J(<U), that aligns the spins in different orbitals. They show strong correlation effects, like very low Fermi-liquid coherence scales and intriguing incoherent transport regimes, resulting in bad metallic behavior. But to what extent are these strong correlations governed by Mottness, i.e. the blocking of charge fluctuations close to a Mott insulator transition (MIT) induced by U, or by Hundness, a new route towards strong correlations induced by J? To answer this question, we study the full phase diagram of a degenerate three-band Hubbard–Hund model on a Bethe lattice at zero temperature using single-site dynamical mean-field theory and the numerical renormalization group as efficient real-frequency multi-band impurity solver. Hund metal behavior occurs in this minimal model for a filling close to n{sub d}=2, moderate U and sizeable J, the “Hund-metal regime”. In particular, strong correlations manifest themselves there by an unusually low quasiparticle weight. Generalizing previous results on this model, we show that “spin–orbital separation” (SOS) is a generic Hund’s-coupling-induced feature in the whole metallic regime of the phase diagram for 1<n{sub d}<3 and sizeable J. There orbital screening always occurs at much higher energies than spin screening below which Fermi-liquid behavior sets in. The low quasiparticle weight can then be directly explained in terms of the Hund’s-coupling-reduced Fermi-liquid scale. We carefully analyze the effect of J (Hundness), and the effect of the MIT at n{sub d}=2 and n{sub d}=3 (Mottness) on the energy scales and the nature of SOS. In the Hund-metal regime, far from any MIT, Hundness is shown to be the key player to induce strong correlations by constraining the spin rather than the charge dynamics. There, physical properties are governed by a broad incoherent energy regime of SOS where intriguing Hund metal physics occurs: large, almost unscreened spins are coupled to screened orbital degrees of freedom. With increasing proximity to an MIT correlations are further enhanced and the Fermi-liquid scale is further reduced. However, in the Hund-metal regime, this effect of Mottness is minor. In contrast, very close to the MIT at n{sub d}=2, the incoherent spin–orbital separation regime is strongly downscaled and becomes negligibly small, whereas Mottness – the localization of charges – becomes dominant in inducing strong correlations. Close to the MIT at n{sub d}=3, the SOS regime widens up because the orbital degrees of freedom get blocked by the formation of an S=(3/2) impurity spin, but its nature changes: the orbital and spin dynamics get decoupled. Our results confirm Hundness as a distinct mechanism towards strong correlations in the normal state of Hund metals, leading to various interesting implications for the nature of electronic transport.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Bayesian automated weighting of aggregated DFT, MD, and experimental data for candidate thermodynamic models of aluminum with uncertainty quantification

Atomic-scale modeling methods such as density functional theory (DFT) and molecular dynamics (MD) can predict the thermodynamic properties of materials at a lower cost than experimental measurements. However, their regular usage in thermodynamic model construction is hampered by the lack of quantitative agreement with experimental measurements and the lack of uncertainty estimates on the data. To make regular usage of this atomistic simulation data, it is important to assess whether the atomistic simulation datasets, by themselves or in combination with experimental measurements, result in the same physics-informed models best supported by experimental measurements alone. Here, models of aluminum thermodynamic properties are discussed using three data sources: atomistic calculations (DFT and MD), experiments, and a combination of atomistic calculations and experiments. The study shows that, after ensuring self-consistency in predicting key invariant points, both experimental measurements and atomistic calculations can significantly contribute to an optimal model.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Effectiveness of Chemoradiation for Head and Neck Cancer in an Older Patient Population

Purpose: The purpose of this study was to compare chemoradiation therapy (CRT) with radiation therapy (RT) only in an older patient population with head and neck squamous cell carcinoma (HNSCC). Methods and Materials: Using the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database (1992-2007), we identified a retrospective cohort of nonmetastatic HNSCC patients and divided them into treatment groups. Comparisons were made between CRT and RT cohorts. Propensity scores for CRT were estimated from covariates associated with receipt of treatment using multivariable logistic regression. Standardized mortality ratio weights (SMRW) were created from the propensity scores and used to balance groups on measured confounders. Multivariable and SMR-weighted Cox proportional hazard models were used to estimate the hazard ratio (HR) of death for receipt of CRT versus RT among the whole group and for separate patient and tumor categories. Results: The final cohort of 10,599 patients was 68% male and 89% white. Median age was 74 years. Seventy-four percent were treated with RT, 26% were treated with CRT. Median follow-up points for CRT and RT survivors were 4.6 and 6.3 years, respectively. On multivariable analysis, HR for death with CRT was 1.13 (95% confidence interval [CI]: 1.07-1.20; P<.01). Using the SMRW model, the HR for death with CRT was 1.08 (95% CI: 1.02-1.15; P=.01). Conclusions: Although the addition of chemotherapy to radiation has proven efficacious in many randomized controlled trials, it may be less effective in an older patient population treated outside of a controlled trial setting.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

A Human Life-Stage Physiologically Based Pharmacokinetic and Pharmacodynamic Model for Chlorpyrifos: Development and Validation

Sensitivity to chemicals in animals and humans are known to vary with age. Age-related changes in sensitivity to chlorpyrifos have been reported in animal models. A life-stage physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model was developed to computationally predict disposition of CPF and its metabolites, chlorpyrifos-oxon (the ultimate toxicant) and 3,5,6-trichloro-2-pyridinol (TCPy), as well as B-esterase inhibition by chlorpyrifos-oxon in humans. In this model, age-dependent body weight was calculated from a generalized Gompertz function, and compartments (liver, brain, fat, blood, diaphragm, rapid, and slow) were scaled based on body weight from polynomial functions on a fractional body weight basis. Blood flows among compartments were calculated as a constant flow per compartment volume. The life-stage PBPK/PD model was calibrated and tested against controlled adult human exposure studies. Model simulations suggest age-dependent pharmacokinetics and response may exist. At oral doses ≥ 0.55 mg/kg of chlorpyrifos (significantly higher than environmental exposure levels), 6 mo old children are predicted to have higher levels of chlorpyrifos-oxon in blood and higher levels of red blood cell cholinesterase inhibition compared to adults from equivalent oral doses of chlorpyrifos. At lower doses that are more relevant to environmental exposures, the model predicts that adults will have slightly higher levels of chlorpyrifos-oxon in blood and greater cholinesterase inhibition. This model provides a computational framework for age-comparative simulations that can be utilized to predict CPF disposition and biological response over various postnatal life-stages.

Smith, Jordan N.↗
DOE OSTI2025

Population Balance Models for Catalytic Depolymerization: From Elementary Steps to Multiphase Reactors

Here, the ongoing accumulation of plastic waste in landfills and in the environment is driving research on chemical processes and catalysts to recycle polymers. Traditional modeling strategies are not applicable to these processes because they involve too many reactants and intermediates, one for each molecular weight and each functionalization. To model the kinetics, we have developed population balance models (PBMs) that account for macromolecular reactants in the bulk and macromolecular catalytic intermediates. These PBMs couple to each other through polymer adsorption and desorption models and to traditional rate equations for small molecule products and co-reactants (like hydrogen or ethylene). The models, in combination with experimental data, are being used in many ways: (i) to test mechanistic hypotheses, (ii) to extract rate parameters, (iii) to quantitatively compare catalyst activities, (iv) to account for mass transfer and vapor–liquid partitioning in two-phase reactors, and (v) to design novel support architectures and catalysts that mimic the processive action of natural depolymerization enzymes. Some key theoretical advances allow PBMs to be constructed from elementary rates and mechanisms, as opposed to traditional formulations with pseudoelementary rate parameters invoked as fitting parameters. We discuss ways to build these models “bottom-up” from first-principles calculations and ways to extract model parameters from “top down” analyses of rate data. The combination provides a quantitative bridge between first-principles calculations and the kinetics of complex macromolecular transformations for polymer upcycling and beyond.

Manis, Lela K. [University of Illinois at Urbana-C↗
DOE OSTI2013

Step-step interactions on GaAs (110) nanopatterns

The step-step interactions on vicinal GaAs (110) surface patterns have been extracted from the quantitative analysis of the terrace width distribution (TWD). We have specifically studied the interactions in near-equilibrium faceting and kinetics-driven step bunching and meandering formed by spontaneous self-organization or through the modification of GaAs growth kinetics by atomic hydrogen. We show that the experimental TWDs determined from atomic force microscopy measurements can be accurately described by a weighed sum of a generalized Wigner distribution and several Gaussians. The results of our calculations indicate that straight facets are formed during high temperature homoepitaxy due to attractive interactions between [110] steps. At low temperatures, steady state attractive interactions in [110] step bunches are preceded by a transition regime dominated by entropic and energetic repulsions between meandering [11n]-type steps (n {>=} 2), whose population density exceeds that of the [110] bunched steps. In addition, it has been found that atomic H reduces the attractive interactions between [110] bunched steps and enhances entropic and dipole-induced energetic repulsions between H-terminated [11n] steps through the inhibition of As-As bond formation at step edges. Our analysis has evidenced a correlation between the value of the adjustable parameter that accounts in our model for the specific weight of the secondary peaks in the TWD ({beta}) and the extent of transverse meandering on the vicinal surface.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dynamics and Power Balance of Near Unity Target Gain Inertial Confinement Fusion Implosions

The change in the power balance, temporal dynamics, emission weighted size, temperature, mass, and areal density of inertially confined fusion plasmas have been quantified for experiments that reach target gains up to 0.72. It is observed that as the target gain rises, increased rates of self-heating initially overcome expansion power losses. This leads to reacting plasmas that reach peak fusion production at later times with increased size, temperature, mass and with lower emission weighted areal densities. Analytic models are consistent with the observations and inferences for how these quantities evolve as the rate of fusion self-heating, fusion yield, and target gain increase. At peak fusion production, it is found that as temperatures and target gains rise, the expansion power loss increases to a near constant ratio of the fusion self-heating power. Finally, this is consistent with models that indicate that the expansion losses dominate the dynamics in this regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗