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At least 433 records · Page 24

Development of a continuous synthesis process for carbamazepine using validated in-line Raman spectroscopy and kinetic modelling for disturbance simulation

Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Conversion of broadband UV-visible to near infrared emission by LaMgAl11O19: Cr3+, Yb3+ phosphors

Highlights: • Energy transfers from Cr{sup 3+} single ions and Cr{sup 3+}-Cr{sup 3+} ion pairs to Yb{sup 3+} ions are both witnessed in LaMgAl{sub 11}O{sub 19}: Cr{sup 3+},Yb{sup 3+}. • Phonon-assisted energy transfer mechanism is verified based on doping concentration and temperature dependent luminescence behaviors. • The phosphor is possible to convert light in region of 250–650 nm into 980 nm light to enhance solar cell efficiency. - Abstract: The Cr{sup 3+}, Yb{sup 3+} co-doped LaMgAl{sub 11}O{sub 19} spectral conversion materials have been synthesized by solid-state reaction method. The phosphor can absorb photons in UV–vis spectral region and then give intense near-infrared emission around 980 nm originated from Yb{sup 3+}: {sup 2}F{sub 5/2} → {sup 2}F{sub 7/2} transition. Phonon-assisted energy transfers from Cr{sup 3+} ions and Cr{sup 3+}-Cr{sup 3+} ion pairs to Yb{sup 3+} ions are both witnessed in LaMgAl{sub 11}O{sub 19} host. The doping concentration and temperature dependent luminescence properties have been investigated. It is believed that Cr{sup 3+}, Yb{sup 3+} co-doped LaMgAl{sub 11}O{sub 19} phosphor might potentially act as spectral convertor for silicon-based solar cells to enhance the photovoltaic conversion efficiency.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Photoelectric characteristics of silicon carbide–silicon structures grown by the atomic substitution method in a silicon crystal lattice

Data obtained in an experimental study of the photoelectric characteristics of silicon–silicon carbide structures grown by the atomic substitution method on silicon (100) and (111) substrates are presented. It is found that the maximum sunlight conversion efficiency of a silicon–silicon carbide (silicon carbide–silicon) heterojunction is 5.4%. The theory of dilatation dipole formation upon synthesis by the atomic substitution method is used to account for the mechanism of electrical barrier formation at the silicon–silicon carbide interface.

36 MATERIALS SCIENCE↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

SU-F-T-262: Commissioning Varian Portal Dosimetry for EPID-Based Patient Specific QA in a Non-Aria Environment

Purpose: Development of an in-house program facilitates a workflow that allows Electronic Portal Imaging Device (EPID) patient specific quality assurance (QA) measurements to be acquired and analyzed in the Portal Dosimetry Application (Varian Medical Systems, Palo Alto, CA) using a non-Aria Record and Verify (R&V) system (MOSAIQ, Elekta, Crawley, UK) to deliver beams in standard clinical treatment mode. Methods: Initial calibration of an in-house software tool includes characterization of EPID dosimetry parameters by importing DICOM images of varying delivered MUs to determine linear mapping factors in order to convert image pixel values to Varian-defined Calibrated Units (CU). Using this information, the Portal Dose Image Prediction (PDIP) algorithm was commissioned by converting images of various field sizes to output factors using the Eclipse Scripting Application Programming Interface (ESAPI) and converting a delivered configuration fluence to absolute dose units. To verify the algorithm configuration, an integrated image was acquired, exported directly from the R&V client, automatically converted to a compatible, calibrated dosimetric image, and compared to a PDIP calculated image using Varian’s Portal Dosimetry Application. Results: For two C-Series and one TrueBeam Varian linear accelerators, gamma comparisons (global 3% / 3mm) of PDIP algorithm predicted dosimetric images and images converted via the inhouse system demonstrated agreement for ≥99% of all pixels, exceeding vendor-recommended commissioning guidelines. Conclusion: Combinations of a programmatic image conversion tool and ESAPI allow for an efficient and accurate method of patient IMRT QA incorporating a 3rd party R&V system.

60 APPLIED LIFE SCIENCES↗

Stabilized Nanocrystalline Alloys: The Intersection of Grain Boundary Segregation with Processing Science

Processing science for nanocrystalline metals has largely focused on far-from-equilibrium methods that can generate many grain boundaries with excess defect energy. Conversely, the science of stabilizing nanocrystalline alloys has largely focused on the lowering of that excess defect energy through grain boundary segregation, bringing nanocrystalline structures closer to equilibrium. With increasing technological adoption of stabilized nanocrystalline alloys, there is a substantial need for research at the intersection of these two fields. This review lays out the basic thermodynamic issues of the two subfields and surveys the literature on the most common processing methods, including severe plastic deformation, ball milling, physical vapor deposition, and electrodeposition. We provide an overview of studies that have examined grain boundary segregation through each of these methods and identify general themes. We conclude that there is substantial scope for more systematic work at the intersection of these fields to understand how nonequilibrium processing affects grain boundary segregation.

Materials Science↗

Highly efficient saturated visible up-conversion photoluminescent Y 2 O 3 :Er 3+ microspheres pumped with a 1.55 μm laser diode

Highly efficient saturation up-conversion (UC) luminescent Y2O3:Er3+ microspheres have been successfully prepared via a hydrothermal-homogeneous precipitation method. Bright visible luminescence can be clearly seen with a 1.55 mu m laser diode excitation power as low as similar to 0.03 W cm(-2). The up-conversion (UC) emission spectra indicate that the strongest red emission with a peak situated at similar to 660 nm originated from the I-4(9/2) -> I-4(15/2) transition of Er3+. The peaks situated at similar to 520 and 550 nm can be assigned to the transition from H-2(11/2)/S-4(3/2) state to the ground state of Er3+. The high efficient saturation up-conversion emission is related to the highly crystalline structure. These results indicate a new way to enhance UC radiation in rare-earth ion-doped materials prepared using a hydrothermal-homogeneous precipitation method.

Zhao, Jinbo↗

A Low-Enriched Uranium (LEU) option for the conversion of FRM II

The Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II) is Germany’s most powerful research reactor and uses Highly Enriched Uranium (HEU) fuel enriched at 93 %. The Technical University of Munich (TUM) operates the reactor and has been mandated to convert the FRM II to a lower-enrichment fuel. In preparation for the lower-enrichment fuel downselection, planned for 2023, TUM is evaluating multiple conversion scenarios. In this paper, it is demonstrated that a conversion of FRM II to Low-Enriched Uranium (LEU) is scientifically possible when using the novel monolithic U-10Mo fuel system, which is currently in the qualification process. As a research reactor, safety criteria, neutron flux distribution and cycle length are key metrics. To begin, neutronic and thermal-hydraulic models were created based on current technical drawings and relevant material properties. Specifically tailored computational methods and coupling schemes have also been developed to properly evaluate all relevant characteristics for the conversion of the FRM II reactor. Using these models and methods, a systematic parameter study was performed to explore the defined design space. The results of that study indicate that many LEU designs using monolithic U-10Mo appear to be viable to convert FRM II to LEU. One example of an LEU solution for the FRM II reactor that fulfills the stated safety, compatibility and scientific performance requirements is discussed in more detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Bridging Scales in Bioenergy and Catalysis: A Review of Mesoscale Modeling Applications, Methods, and Future Directions

Between the molecular and reactor scales, which are familiar to the chemical engineering community, lies an intermediate regime, here termed the “mesoscale,” where transport phenomena and reaction kinetics compete on similar time scales. Bioenergy and catalytic processes offer particularly important examples of mesoscale phenomena owing to their multiphase nature and the complex, highly variable porosity characteristic of biomass and many structured catalysts. In this review, we overview applications and methods central to mesoscale modeling as they apply to reaction engineering of biomass conversion and catalytic processing. A brief historical perspective is offered to put recent advances in context. Applications of mesoscale modeling are described, and several specific examples from biomass pyrolysis and catalytic upgrading of bioderived intermediates are highlighted. Methods including reduced order modeling, finite element and finite volume approaches, geometry construction and import, and visualization of simulation results are described; in each category, recent advances, current limitations, and areas for future development are presented. Owing to improved access to high-performance computational resources, advances in algorithm development, and sustained interest in reaction engineering to sustainably meet societal needs, we conclude that a significant upsurge in mesoscale modeling capabilities is on the horizon that will accelerate design, deployment, and optimization of new bioenergy and catalytic technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decreased land use intensity improves surface soil quality on marginal lands

The Conservation Reserve Program (CRP) has been a major factor in land transitions out of intensive row-crop management on marginally productive lands in the central United States. While CRP can protect these more environmentally sensitive lands against erosion and potential nutrient loss, information on how CRP affects soil quality over time is limited. Using a chronosequence with 0–40 yr of CRP conversion history, we evaluated soil quality under different land use intensities (CRP, pasture, row crop) using the Soil Management Assessment Framework (SMAF). Effects of slope classes (higher [14–25%] and lower [2–14%]) and soil depth (0–120 cm) were also evaluated. Our results show that the soils were functioning at 84 and 78% of their theoretical capacity under CRP and row crop, respectively. Conversion to CRP enhanced overall soil quality by increasing soil biological, physical, and chemical attributes, but soil nutrient availability decreased due to the absence of fertilizer application. Increasing soil organic C (SOC) enhanced overall soil quality because of its impact on soil biological, physical, chemical, and nutrient conditions. Conversion to CRP will likely have greater benefits for more environmentally sensitive soils (i.e., higher slope) as demonstrated by structural equation modeling. Land use effects were also depth dependent, with more prominent effects within the 0-to-5-cm than the 5-to-15-cm depth increment. Overall, our methods focused on key soil quality indicators, confirmed ecological benefits of CRP conversion, and provided guidance for improved and simplified land management recommendations.

54 ENVIRONMENTAL SCIENCES↗

Where, when, and why: Occurrence of fast-pairwise collective neutrino oscillation in three-dimensional core-collapse supernova models

Fast-pairwise collective neutrino oscillation represents a key uncertainty in the theory of core-collapse supernova (CCSN). Despite the potentially significant impact on CCSN dynamics, it is usually neglected in numerical models of CCSN because of the formidable technical difficulties of self-consistently incorporating this physics. In this paper, we investigate the prospects for the occurrence of fast flavor conversion by diagnosing electron neutrino lepton number (ELN) crossing in more than a dozen state-of-the-art three-dimensional CCSN models. ELN crossings provide a necessary condition for triggering flavor conversion. Although only zeroth and first angular moments are available from the simulations, our new method enables us to look into the angular distributions of neutrinos in momentum space and provide accurate insight into ELN crossings. Our analysis suggests that fast flavor conversion generally occurs in the postshock region of CCSNe, and that explosive models provide more favorable conditions for the flavor conversion than failed CCSNe. Here we also find that there are both common and progenitor-dependent characteristics. Classifying ELN crossings into two types, we analyze the generation mechanism of each case by scrutinizing the neutrino radiation field and matter interactions. We find key ingredients of CCSN dynamics driving the ELN crossings: proto-neutron star convection, asymmetric neutrino emission, neutrino absorptions, and scatterings. This study suggests that we need to accommodate fast flavor conversions in realistic CCSN models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗

Precursor Processing Development for Low Cost, High Strength Carbon Fiber for Composite Overwrapped Pressure Vessel Applications

Carbon fiber (CF) is central to produce lightweight, high pressure, composite overwrapped pressure vessels (COPVs), which are used for on-board storage of hydrogen for fuel cell vehicles. In 2015, carbon fiber cost accounted for 62% of the cost of a hydrogen storage system, as COPVs were manufactured with T700S CF at $\$ $29.40/kg CF. The high cost of hydrogen storage, largely attributed to the carbon fiber cost, limits the application of fuel cells in vehicles. Therefore, our team endeavored to develop fiber processing to demonstrate carbon fiber tensile properties similar to T700S with a production cost potential of $\$ $12.60/kg or less. Here, the overarching goal of the project was the development of low cost, high strength carbon fiber for composite overwrapped pressure vessels. Within the project, our team investigated a new low-cost, high-volume, high quality polyacrylonitrile (PAN)-based precursor terpolymer for the production of carbon fiber precursors, methods for increasing water and energy use efficiency in wash-water/solvent separation, and ultimately developed a multifilament spinning and conversion process for the production of hollow carbon fibers from a segmented arc spinneret utilizing a solution spinning method.

08 HYDROGEN↗

Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method

Abstract Fractionally doped perovskites oxides (FDPOs) have demonstrated ubiquitous applications such as energy conversion, storage and harvesting, catalysis, sensor, superconductor, ferroelectric, piezoelectric, magnetic, and luminescence. Hence, an accurate, cost-effective, and easy-to-use methodology to discover new compositions is much needed. Here, we developed a function-confined machine learning methodology to discover new FDPOs with high prediction accuracy from limited experimental data. By focusing on a specific application, namely solar thermochemical hydrogen production, we collected 632 training data and defined 21 desirable features. Our gradient boosting classifier model achieved a high prediction accuracy of 95.4% and a high F1 score of 0.921. Furthermore, when verified on additional 36 experimental data from existing literature, the model showed a prediction accuracy of 94.4%. With the help of this machine learning approach, we identified and synthesized 11 new FDPO compositions, 7 of which are relevant for solar thermochemical hydrogen production. We believe this confined machine learning methodology can be used to discover, from limited data, FDPOs with other specific application purposes.

08 HYDROGEN↗

TU-H-207A-01: Development of Conversion Factors to Account for Different CTDI Phantom Setups On a Wide-Beam CT Scanner

Purpose: A fundamental measure performed during an annual physics CT evaluation confirms that system displayed CTDIvol nearly matches the independently measured value in phantom. For wide-beam (z-direction) CT scanners, AAPM Report 111 defined an ideal measurement method; however, the method often lacks practicality. The purpose of this preliminary study is to develop a set of conversion factors for a wide-beam CT scanner, relating the CTDIvol measured with a conventional setup (single CTDI phantom) versus the AAPM Report 111 approach (three abutting CTDI phantoms). Methods: For both the body CTDI and head CTDI, two acquisition setups were used: A) conventional single phantom and B) triple phantom. Of primary concern were the larger nominal beam widths for which a standard CTDI phantom setup would not provide adequate scatter conditions. Nominal beam width (160 or 120 mm) and kVp (100, 120, 140) were modulated based on the underlying clinical protocol. Exposure measurements were taken using a CT pencil ion chamber in the center and 12 o’clock position, and CTDIvol was calculated with ‘nT’ limited to 100 mm. A conversion factor (CF) was calculated as the ratio of CTDIvol measured in setup B versus setup A. Results: For body CTDI, the CF ranged from 1.04 up to 1.10, indicating a 4–10% difference between usage of one and three phantoms. For a nominal beam width of 160 mm, the CF did vary with selected kVp. For head CTDI at nominal beam widths of 120 and 160 mm, the CF was 1.00 and 1.05, respectively, independent of the kVp used (100, 120, and 140). Conclusions: A clear understanding of the manufacturer method of estimating the displayed CTDIvol is important when interpreting annual test results, as the acquisition setup may lead to an error of up to 10%. With appropriately defined CF, single phantom use is feasible.

07 ISOTOPE AND RADIATION SOURCES↗

Data processing methods and data acquisition for samples larger than the field of view in parallel-beam tomography

Parallel-beam tomography systems at synchrotron facilities have limited field of view (FOV) determined by the available beam size and detector system coverage. Scanning the full size of samples bigger than the FOV requires various data acquisition schemes such as grid scan, 360-degree scan with offset center-of-rotation (COR), helical scan, or combinations of these schemes. Though straightforward to implement, these scanning techniques have not often been used due to the lack of software and methods to process such types of data in an easy and automated fashion. The ease of use and automation is critical at synchrotron facilities where using visual inspection in data processing steps such as image stitching, COR determination, or helical data conversion is impractical due to the large size of datasets. Here, we provide methods and their implementations in a Python package, named Algotom, for not only processing such data types but also with the highest quality possible. The efficiency and ease of use of these tools can help to extend applications of parallel-beam tomography systems.

36 MATERIALS SCIENCE↗

Gradient elution moving boundary electrophoresis enables rapid analysis of acids in complex biomass-derived streams

Biomass conversion processes such as pretreatment, liquefaction, and pyrolysis often produce complex mixtures of intermediates that are a substantial challenge to analyze rapidly and reliably. To characterize these streams more comprehensively and efficiently, new techniques are needed to track species through biomass deconstruction and conversion processes. Here, we present the application of an emerging analytical method, gradient elution moving boundary electrophoresis (GEMBE), to quantify a suite of acids in a complex, biomass-derived streams from alkaline pretreatment of corn stover. GEMBE offers distinct advantages over common chromatography-spectrometry analytical approaches in terms of analysis time, sample preparation requirements, and cost of equipment. As demonstrated here, GEMBE is able to track 17 distinct compounds (oxalate, formate, succinate, malate, acetate, glycolate, protocatechuate, 3-hydroxypropanoate, lactate, glycerate, 2-hydroxybutanoate, 4-hydroxybenzoate, vanillate, p-coumarate, ferulate, sinapate, and acetovanillone). The lower limit of detection was compound dependent and ranged between 0.9 and 3.5 umol/L. Results from GEMBE were similar to recent results from an orthogonal method based on GCxGC-TOF/MS. Altogether, GEMBE offers a rapid, robust approach to analyze complex biomass-derived samples, and given the ease and convenience of deployment, may offer an analytical solution for online tracking of multiple types of biomass streams.

09 BIOMASS FUELS↗