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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Phase, morphology, elemental composition, and formation mechanisms of biogenic and abiogenic Fe-Cu-sulfide nanoparticles: A comparative study on their occurrences under anoxic conditions

In this paper, we report on a systematic study on the physicochemical attributes of synthetic Fe-Cu-sulfide nanoparticles (NPs) precipitated under conditions similar to the anoxic, low temperature aqueous, sedimentary, soil and subsurface environments where these NPs have been repeatedly identified. Characterizing the basic attributes of these NPs is the first step in understanding their behaviors in various processes including in the bio-availability of essential and toxic metals, environmental remediation and resource recovery. All experiments are performed in the presence and absence of the sulfate-reducer Desulfovibrio vulgaris to elucidate biological controls on NP formation. First, the single-metal endmember NPs are determined by precipitation in solution containing either aqueous Fe(II) or Cu(II). Limited differences are observed between biogenic and abiogenic precipitates aged for up to one month; the Fe-only experiments resulted in 4-10 nm mackinawite (FeS) NPs that aggregate to form nanosheets up to ~1,000 nm in size, while the Cu-only experiments resulted in mixtures of covellite (CuS) NPs comprised of <10 nm fine nanocrystals, 20-40 x 6-9 nm nanorods and ~30 nm nanoplates. The crystal sizes of biogenic mackinawite and covellite are respectively larger and smaller than their abiogenic counterparts, indicating a mineral-specific response to biological presence. Structural defects are observable in the fine nanocrystals and nanorods of covellite in both biogenic and abiogenic experiments, indicative of intrinsic NP instability and formation mechanism via particle attachment. In contrast, covellite nanoplates are defect-free, indicating high stability and potentially rapid recrystallization following particle attachment. Next, mixed-metal sulfide NPs are precipitated at variable initial aqueous Fe-to-Cu ratios (2:1, 1:1 and 1:5). With increasing ratio of Fe-to-Cu, Fe-rich covellite, nukundamite (Cu 5.5 FeS 6.5 ), chalcopyrite (CuFeS 2 ), and Cu-rich mackinawite are formed. The Fe-rich covellite NPs are larger (100-200 nm) than covellite precipitated in the absence of Fe, indicating a role for Fe in promoting crystal growth. Chalcopyrite and nukundamite are formed through incorporation of Fe into precursor covellite NPs while retaining the original crystal morphology, as confirmed by doping a covellite suspension with aqueous Fe(II), resulting in the formation of chalcopyrite and nukundamite within days. Additionally, in the biological systems we observe the recrystallization of mackinawite to greigite (Fe 3 S 4 ) after six months of incubation in the absence of Cu, and the selective formation of chalcopyrite and nukundamite at lower initial Fe-to-Cu ratios compared to abiotic systems. These observations are consistent with NP precipitation that are influenced by the distinct (sub)micro-environments around bacterial cells compared to the bulk solution. Lastly, comparative TEM analyses indicate that the synthetic NPs are morphologically similar to NPs identified in natural environments, opening ways to studying behaviors of natural NPs using experimental approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Going Off Grid: A Comparative Study of the Lagrangian and Eulerian Perspectives of New Particle Formation Events

New particle formation and growth (NPF&G) is the process by which ultrafine particles are formed from gas-phase precursors. NPF&G is the dominant source of global aerosol number with important influences on climate. Most observations of NPF&G events are conducted at stationary sites; however, NPF&G observed from stationary sites is influenced by gradual or rapid changes in the air masses passing over the site, complicating NPF&G analysis. In this work, we use observations and a 3D aerosol model to compare aerosol size distributions at a stationary site (Southern Great Plains [SGP] observatory, Oklahoma, USA) and along Lagrangian trajectories crossing the site. The model simulates the NPF&G events reasonably well at SGP. Using the model to compare the Lagrangian and stationary perspectives, we can explain previously unanalyzable days with some evidence of NPF&G as either non-event or analyzable NPF&G days. We find most of the unanalyzable NPF&G days are due to isolated and inhomogeneous NPF&G occurring upwind of the stationary site, often in the outflow of urban regions. Finally, we compare formation rates of 3 nm particles, growth rates, and the survival probability of 3 nm particles growing to 25 nm between the stationary and Lagrangian perspectives. Because of the much larger number of analyzable days along the Lagrangian trajectories, this perspective potentially provides more robust statistics and better characterization of NPF&G event extremes. Our method for extracting chemical/physical properties along Lagrangian trajectories from 3D models can be applied to a wide range of science questions.

O’Donnell, Samuel E. [Colorado State Univ., Fort C↗
DOE OSTI2025

Agentic AI vs ML-Based Autotuning: A Comparative Study for Loop Reordering Optimization

High Performance Computing (HPC) applications rely heavily on code optimizations to achieve good performance on modern CPU and GPU architectures. Traditional Machine Learning auto-tuning approaches have demonstrated success in exploring high-dimensional spaces, but they often require expensive compile-run evaluations and lack adaptability for large HPC applications. The recent advances in Large Language Models (LLMs) and Agentic AI systems raise intriguing questions about the potential of these approaches to address specific optimization methodologies. This work aims to answer an essential question for the HPC community: “How Agentic AI Systems Compare to Traditional ML Autotuning Techniques?” To address this question, we present a comparative analysis between a traditional ML-based optimization approach and an Agentic AI system, evaluating their respective capabilities and limitations for loop-level optimization. In addition, we introduced a new Agentic AI system named LoopGen-AI using three different Large Language Models: GPT-4.1, Claude 4.0, and Gemini 2.5. A key finding is that LoopGen-AI achieves competitive per-formance with only a few program runs, the reasoning logs from the agents revealed that their decisions rely heavily on the combination of semantic understanding of the target kernel with dynamic feedback from the environment, highlighting a promising new dimension in performance tuning. In contrast, ML-based autotuners focus on statistical exploration, and require orders of magnitude more runs to reach peak performance. Additionally, our analysis shows that prompt engineering, particularly using Persona + Context Manager patterns, significantly impacts the effectiveness of Agentic AI. Our results indicate that while Agentic AI systems are not yet a complete replacement for ML-based autotuners, it can effectively complement traditional methods.

Rosas, Miguel Romero↗
DOE OSTI2011

Earthquake correlations and networks: A comparative study

We quantify the correlation between earthquakes and use the same to extract causally connected earthquake pairs. Our correlation metric is a variation on the one introduced by Baiesi and Paczuski [M. Baiesi and M. Paczuski, Phys. Rev. E 69, 066106 (2004)]. A network of earthquakes is then constructed from the time-ordered catalog and with links between the more correlated ones. A list of recurrences to each of the earthquakes is identified employing correlation thresholds to demarcate the most meaningful ones in each cluster. Data pertaining to three different seismic regions (viz., California, Japan, and the Himalayas) are comparatively analyzed using such a network model. The distribution of recurrence lengths and recurrence times are two of the key features analyzed to draw conclusions about the universal aspects of such a network model. We find that the unimodal feature of recurrence length distribution, which helps to associate typical rupture lengths with different magnitude earthquakes, is robust across the different seismic regions. The out-degree of the networks shows a hub structure rooted on the large magnitude earthquakes. In-degree distribution is seen to be dependent on the density of events in the neighborhood. Power laws, with two regimes having different exponents, are obtained with recurrence time distribution. The first regime confirms the Omori law for aftershocks while the second regime, with a faster falloff for the larger recurrence times, establishes that pure spatial recurrences also follow a power-law distribution. The crossover to the second power-law regime can be taken to be signaling the end of the aftershock regime in an objective fashion.

58 GEOSCIENCES↗
DOE OSTI2016

Radiation-Related New Primary Solid Cancers in the Childhood Cancer Survivor Study: Comparative Radiation Dose Response and Modification of Treatment Effects

Objectives: The majority of childhood cancer patients now achieve long-term survival, but the treatments that cured their malignancy often put them at risk of adverse health outcomes years later. New cancers are among the most serious of these late effects. The aims of this review are to compare and contrast radiation dose–response relationships for new solid cancers in a large cohort of childhood cancer survivors and to discuss interactions among treatment and host factors. Methods: This review is based on previously published site-specific analyses for subsequent primary cancers of the brain, breast, thyroid gland, bone and soft tissue, salivary glands, and skin among 12,268 5-year childhood cancer survivors in the Childhood Cancer Survivor Study. Analyses included tumor site–specific, individual radiation dose reconstruction based on radiation therapy records. Radiation-related second cancer risks were estimated using conditional logistic or Poisson regression models for excess relative risk (ERR). Results: Linear dose–response relationships over a wide range of radiation dose (0-50 Gy) were seen for all cancer sites except the thyroid gland. The steepest slopes occurred for sarcoma, meningioma, and nonmelanoma skin cancer (ERR/Gy > 1.00), with glioma and cancers of the breast and salivary glands forming a second group (ERR/Gy = 0.27-0.36). The relative risk for thyroid cancer increased up to 15-20 Gy and then decreased with increasing dose. The risk of thyroid cancer also was positively associated with chemotherapy, but the chemotherapy effect was not seen among those who also received very high doses of radiation to the thyroid. The excess risk of radiation-related breast cancer was sharply reduced among women who received 5 Gy or more to the ovaries. Conclusions: The results suggest that the effect of high-dose irradiation is consistent with a linear dose–response for most organs, but they also reveal important organ-specific and host-specific differences in susceptibility and interactions between different aspects of treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Comparative study on neutronics characteristics of a 1500 MWe metal fuel sodium-cooled fast reactor

Under the cooperative effort of the Civil Nuclear Energy R&D Working Group within the framework of the U.S.-Japan bilateral, Argonne National Laboratory (ANL) and Japan Atomic Energy Agency (JAEA) have been performing benchmark study using Japan Sodium-cooled Fast Reactor (JSFR) design with metal fuel. In this benchmark study, core characteristic parameters at the beginning of cycle were evaluated by the best estimate deterministic and stochastic methodologies of ANL and JAEA. The results obtained by both institutions show a good agreement with less than 200 pcm of discrepancy on the neutron multiplication factor, and less than 3% of discrepancy on the sodium void reactivity, Doppler reactivity, and control rod worth. The results by the stochastic and deterministic approaches were compared in each party to investigate impacts of the deterministic approximation and to understand potential variations in the results due to different calculation methodologies employed. From the detailed analysis of methodologies, it was found that the good agreement in multiplication factor from the deterministic calculations comes from the cancellation of the differences on the methodology (0.4%) and nuclear data (0.6%). The different treatment in reflector cross section generation was estimated as the major cause of the discrepancy between the multiplication factors by the JAEA and ANL deterministic methodologies. Impacts of the nuclear data libraries were also investigated using a sensitivity analysis methodology. Furthermore, the differences on the inelastic scattering cross sections of U-238, ν values and fission cross sections of Pu-239 and µ-average of Na-23 are the major contributors to the difference on the multiplication factors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

A Comparative Study of Deformation Behaviors Between Laser-Welded Joints and Base Metal of Ti-22Al-24.5Nb-0.5Mo Alloy

The tensile deformation behaviors of laser-welded Ti-22Al-24.5Nb-0.5Mo alloy joints have been investigated at room temperature and 650 °C using in situ tensile analysis methods. The α{sub 2} phase had a significant influence on deformation behaviors of base metal at room temperature and 650 °C. The microcracks mainly nucleated in B2/α{sub 2} phase boundaries or within α{sub 2} phase and then propagated along B2/α{sub 2} phase boundaries subsequently. Compared with the plastic fracture of base metal, the fracture modes of the fully B2-phase fusion zone at room temperature and 650 °C were quasi-cleavage and intergranular fracture, respectively. While dislocation slips became foremost deformation mode in the fusion zone at room temperature, there were a great amount of slip bands on the surface of grains caused by the slip systems. The microcracks of fusion zone at 650 °C nucleated and propagated along the grain boundaries of B2 phase. Owing to the lack of grain deformation, the cross-slip bands were in small quantities on the surface of B2 phase grains.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Comparative Studies on C-coated and Uncoated LiFePO4 Cycling at Various Rates and Temperatures using Synchrotron Based in situ X-ray Diffraction

The structural changes of LiFePO{sub 4} and C-coated LiFePO{sub 4} during charging at various C-rates and temperatures are investigated using synchrotron based in situ X-ray diffraction technique. The XRD patterns collected during cycling show the structural evidence of the positive effects of carbon coating on LiFePO{sub 4} for the electrochemical performance improvements at different temperatures, especially at low temperatures. At -10 C, the C-coated LiFePO{sub 4} shows comparable capacities with the sample cycled at room temperature when cycled at C/5 rate with a slight shift of the plateau to a higher voltage during charging. The in situ XRD patterns collected simultaneously show a complete phase transformation from triphylite to heterosite. At -20 C, the C-coated LiFePO{sub 4} delivers 55.6% of its theoretical capacities at C/5 rate. However, the plateau in the charging curve becomes sloppy and shifts to a higher voltage. The in situ XRD patterns show that the phase transformation from triphylite to heterosite is not completed when charged to 4.5 V due to the larger polarization when charged at -20 C.

25 ENERGY STORAGE↗
DOE OSTI2025

Comparative study between experimental measurements and model predictions of bubble rise velocity in molten LiCl-KCl

This research investigated the shape and rise velocities of gas bubbles (helium, nitrogen, argon, and krypton) in molten LiCl-KCl at 500 °C using a specialized optical visualization apparatus. The apparatus features a custom quartz rectangular prism cell housed in a furnace, enabling the application of the shadowgraph measurement technique. Bubbles with diameters between 0.45 and 3.2 mm were produced via a capillary, and their equivalent diameters and rise velocities were analyzed using high-resolution imaging and centroid tracking algorithms. Important non-dimensional parameters were calculated to characterize behavior. Bubbles with 0.03 < Eo < 1.32, 17 < Re < 718, and Mo order of 10 -11 were generated in the molten LiCl-KCl, revealing that bubbles with diameters less than 1.46 mm remain spherical, whereas those with larger diameters are ellipsoidal. The transition and oscillation onset for bubble shape occurred at larger diameters than those previously observed in air–water systems. Comparative analysis of the gas-molten salt data against existing air–water bubble rise velocity correlations highlighted inaccuracies in predictions, particularly across the different bubble regimes. An existing correlation was calibrated to the molten salt data to improve the bubble velocity predictions. In conclusion, this study contributes essential experimental data for the design and safety evaluation of molten salt reactors and offers insights for the optimization of sparge systems for fission product removal.

Bubble rise velocity↗
DOE OSTI2014

A comparative study of ethanol production using dilute acid, ionic liquid and AFEX™ pretreated corn stover

In a biorefinery producing cellulosic biofuels, biomass pretreatment will significantly influence the efficacy of enzymatic hydrolysis and microbial fermentation. Comparison of different biomass pretreatment techniques by studying the impact of pretreatment on downstream operations at industrially relevant conditions and performing comprehensive mass balances will help focus attention on necessary process improvements, and thereby help reduce the cost of biofuel production. An on-going collaboration between the three US Department of Energy (DOE) funded bioenergy research centers (Great Lakes Bioenergy Research Center (GLBRC), Joint BioEnergy Institute (JBEI) and BioEnergy Science Center (BESC)) has given us a unique opportunity to compare the performance of three pretreatment processes, notably dilute acid (DA), ionic liquid (IL) and ammonia fiber expansion (AFEX TM ), using the same source of corn stover. Separate hydrolysis and fermentation (SHF) was carried out using various combinations of commercially available enzymes and engineered yeast (Saccharomyces cerevisiae 424A) strain. The optimal commercial enzyme combination (Ctec2: Htec2: Multifect Pectinase, percentage total protein loading basis) was evaluated for each pretreatment with a microplate-based assay using milled pretreated solids at 0.2% glucan loading and 15 mg total protein loading/g of glucan. The best enzyme combinations were 67:33:0 for DA, 39:33:28 for IL and 67:17:17 for AFEX. The amounts of sugar (kg) (glucose: xylose: total gluco- and xylo-oligomers) per 100 kg of untreated corn stover produced after 72 hours of 6% glucan loading enzymatic hydrolysis were: DA (25:2:2), IL (31:15:2) and AFEX (26:13:7). Additionally, the amounts of ethanol (kg) produced per 100 kg of untreated corn stover and the respective ethanol metabolic yield (%) achieved with exogenous nutrient supplemented fermentations were: DA (14.0, 92.0%), IL (21.2, 93.0%) and AFEX (20.5, 95.0%), respectively. The reason for lower ethanol yield for DA is because most of the xylose produced during the pretreatment was removed and not converted to ethanol during fermentation. Compositional analysis of the pretreated biomass solids showed no significant change in composition for AFEX treated corn stover, while about 85% of hemicellulose was solubilized after DA pretreatment, and about 90% of lignin was removed after IL pretreatment. As expected, the optimal commercial enzyme combination was different for the solids prepared by different pretreatment technologies. Due to loss of nutrients during the pretreatment and washing steps, DA and IL pretreated hydrolysates required exogenous nutrient supplementation to ferment glucose and xylose efficiently, while AFEX pretreated hydrolysate did not require nutrient supplementation.

09 BIOMASS FUELS↗
DOE OSTI2018

Comparative study of bulk and nano-structured mesoporous SnO 2 electrodes on the electrochemical performances for next generation Li rechargeable batteries

For next generation Li-ion batteries, advanced electrode materials with high energy densities are mightily important issue. Since the partial oxidation of Sn with Li 2 O to form SnO x was demonstrated upon delithiation in SnO 2 anode, the additional conversion reaction has contributed that the theoretical capacity of SnO 2 can be extended from 783 to 1494 mAh g -1 . Herein, with the design of additional conversion reaction, we discuss key factors for high electrochemical performances of the SnO 2 anodes through comparative analysis between nano-structured mesoporous SnO 2 and conventional bulk SnO 2 , based on synchrotron radiation-based techniques, quantitative analysis of extended X-ray absorption fine structure spectra, and bond strength calculation. In this way, we demonstrate that the mesoporous SnO 2 has a nano-engineering structure, inducing the facilitated electrochemical reaction and the weak Sn-O bond strength that would have an advantage in the additional conversion reaction as well as a void structure, relieving the severe volume changes during lithiation/delithiation. Consequently, excellent electrochemical performance is obtained in the mesoporous SnO 2 . Furthermore, insight from this research enables important advance in the development of metal oxide-based anode materials by making irreversible reaction reversible, providing a realizable strategy for the design and creation of high-energy storage devices.

25 ENERGY STORAGE↗
DOE OSTI2017

A Comparative study of two RVE modelling methods for chopped carbon fiber SMC

To achieve vehicle light-weighting, the chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, the Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed for material RVE property prediction. The two methods are compared in terms of the predicted elastic modulus and the predicted results are validated using the Digital Image Correlation (DIC) tensile test results. Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.

mesostructure reconstruction↗
DOE OSTI2018

A Comparative Study of Fracture Toughness at Cryogenic Temperature of Austenitic Stainless Steel Welds

The ITER magnet system is based on the “cable-in-conduit” conductor (CICC) concept, which consists of stainless steel jackets filled with superconducting strands. The jackets provide high strength, limited fatigue crack growth rate and fracture toughness properties to counteract the high stress imposed by, among others, electromagnetic loads at cryogenic temperature. Austenitic nitrogen-strengthened stainless steels have been chosen as base material for the jackets of the central solenoid and the toroidal field system, for which an extensive set of cryogenic mechanical property data are readily available. However, little is published for their welded joints, and their specific performance when considering different combinations of parent and filler metals. Moreover, the impact of post-weld heat treatments that are required for Nb{sub 3}Sn formation is not extensively treated. Welds are frequently responsible for cracks initiated and propagated by fatigue during service, causing structural failure. It becomes thus essential to select the most suitable combination of parent and filler material and to assess their performance in terms of strength and crack propagation at operation conditions. An extensive test campaign has been conducted at 7 K comparing tungsten inert gas (TIG) welds using two fillers adapted to cryogenic service, EN 1.4453 and JK2LB, applied to two different base metals, AISI 316L and 316LN. A large set of fracture toughness data are presented, and the detrimental effect on fracture toughness of post-weld heat treatments (unavoidable for some of the components) is demonstrated. In this study, austenitic stainless steel TIG welds with various filler metals have undergone a comprehensive fracture mechanics characterization at 7 K. These results are directly exploitable and contribute to the cryogenic fracture mechanics properties database of the ITER magnet system. Additionally, a correlation between the impact in fracture toughness and microstructure resulting from the above treatment is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Non-stationary Geostatistical Modeling: A Case Study Comparing LVA Estimation Frameworks

Incorporating locally varying anisotropy (LVA) in geostatistical modeling improves estimates for structurally complex domains where a single set of anisotropic parameters modeled globally do not account for all geological features. In this work, the properties of two LVA-geostatistical modeling frameworks are explored through application to a complexly folded gold deposit in Ghana. The inference of necessary parameters is a significant requirement of geostatistical modeling with LVA; this work focuses on the case where LVA orientations, derived from expert geological interpretation, are used to improve the grade estimates. The different methodologies for inferring the required parameters in this context are explored. The results of considering different estimation frameworks and alternate methods of parameterization are evaluated with a cross-validation study, as well as visual inspection of grade continuity along select cross sections. Results show that stationary methodologies are outperformed by all LVA techniques, even when the LVA framework has minimal guidance on parameterization. Findings also show that additional improvements are gained by considering parameter inference where the LVA orientations and point data are used to infer the local range of anisotropy. Considering LVA for geostatistical modeling of the deposit considered in this work results in better reproduction of curvilinear geological features.

58 GEOSCIENCES↗
DOE OSTI2019

A Comparative Study on Microstructures, Magnetic Features and Morphologies of Ternary Fe–Co–Ni Alloy Thin Films Electrochemically Fabricated at Different Deposition Potentials

Electrochemically fabricated ternary Fe–Co–Ni alloy thin films with different chemical compositions were obtained at different deposition potentials. An increase in the deposition potential increased the Ni content while it decreased the Co and Fe contents in the film structure. An anomalous co-deposition behaviour was also studied and the anomalous order of co-deposition was found to be Fe–Ni > Co–Ni > Fe–Co irrespective of deposition potential. Structural characterizations confirmed the presence of single face-centred cubic (fcc) phase structure with [111] preferred crystallographic orientation for all films. The size of the crystallites and the texture degree increased with increasing applied deposition potential. Smaller globular particles occurred on the surface structure of the film fabricated at higher deposition potentials compared to those grown at lower deposition potentials. A decrement detected in the coercive field with increasing applied deposition potential was related to the variations occurred in the chemical composition and the particle size.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Life Cycle Assessment of Innovative Carbon Dioxide Selective Membranes from Low Carbon Emission Sources: A Comparative Study

Carbon capture has been an important topic of the twenty-first century because of the elevating carbon dioxide (CO2) levels in the atmosphere. CO2 in the atmosphere is above 420 parts per million (ppm) as of 2022, 70 ppm higher than 50 years ago. Carbon capture research and development has mostly been centered around higher concentration flue gas streams. For example, flue gas streams from steel and cement industries have been largely ignored due to lower associated CO2 concentrations and higher capture and processing costs. Capture technologies such as solvent-based, adsorption-based, cryogenic distillation, and pressure-swing adsorption are under research, but many suffer from higher costs and life cycle impacts. Membrane-based capture processes are considered cost-effective and environmentally friendly alternatives. Over the past three decades, our research group at Idaho National Laboratory has led the development of several polyphosphazene polymer chemistries and has demonstrated their selectivity for CO2 over nitrogen (N2). Poly[bis((2-methoxyethoxy)ethoxy)phosphazene] (MEEP) has shown the highest selectivity. A comprehensive life cycle assessment (LCA) was performed to determine the life cycle feasibility of the MEEP polymer material compared to other CO2-selective membranes and separation processes. The MEEP-based membrane processes emit at least 42% less equivalent CO2 than Pebax-based membrane processes. Similarly, MEEP-based membrane processes produce 34–72% less CO2 than conventional separation processes. In all studied categories, MEEP-based membranes report lower emissions than Pebax-based membranes and conventional separation processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Comparative study of A-site order in the lead-free bismuth titanates M{sub 1/2}Bi{sub 1/2}TiO{sub 3} (M=Li, Na, K, Rb, Cs, Ag, Tl) from first-principles

We investigate the possibility of enhancing chemical order in the relaxor ferroelectric Na{sub 1/2}Bi{sub 1/2}TiO{sub 3} upon substitution of Na{sup +} by other monovalent cations M{sup +} using total energy calculations based on density functional theory. All chemically available monovalent cations M{sup +}, which are Li, Na, Ag, K, Tl, Rb and Cs, are considered and an analysis of the structurally relaxed structures in terms of symmetry-adapted distortion modes is given in order to quantify the chemically induced structural distortions. We demonstrate that the replacement of Na{sup +} by other monovalent cations can hardly alter the tendency of chemical order with respect to Na{sub 1/2}Bi{sub 1/2}TiO{sub 3}. Only Tl{sub 1/2}Bi{sub 1/2}TiO{sub 3} and Ag{sub 1/2}Bi{sub 1/2}TiO{sub 3} show enhanced tendency for chemical ordering. Both heavy metals behave similar to the light alkali metals in terms of structural relaxations and relative stabilities of the ordered configurations. Although a comparison of the Goldschmidt factors of components (M TiO{sub 3}){sup −} reveals for Tl a value above the upper stability limit for perovskites, the additional lone-pair effect of Tl{sup +} stabilizes the ordered structure. - Graphical abstract: Amplitudes of chemically induced distortion modes in different ordered perovskites M{sub 1/2}Bi{sub 1/2}TiO{sub 3} and visualisation of atomic displacements associated with distortion mode X{sup +}{sub 1} in the 001-ordered compounds Li{sub 1/2}Bi{sub 1/2}TiO{sub 3} and Cs{sub 1/2}Bi{sub 1/2}TiO{sub 3}. Due to a substantial size mismatch between bismuth (green) and caesium (dark blue), incorporation of the latter leads to enhanced displacements of oxygen atoms (red) and suppresses displacements of titanium (silver) as compared to lithium (light blue) or other smaller monovalent cations. - Highlights: • Lead-free A-site mixed bismuth titanates M{sub 1/2}Bi{sub 1/2}TiO{sub 3} are studied by first-principles calculations. • Investigation of chemical ordering tendency for M=Li, Na, K, Rb, Cs, Ag, and Tl. • Group theoretical analysis of different ordered structures. • Ag and Tl compounds are the most promising candidates for study of chemical order dependent ferroelectric properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗