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At least 253 records · Page 14

A divergent synthetic route to functional copolymer libraries via modular polymers

High-throughput polymer synthesis enables rapid exploration of chemical space but remains limited by batch-to-batch inconsistencies that can obscure structure–property relationship trends. To address this challenge, we developed a synthetic approach to produce multifunctional copolymers using post-polymerization modification of activated ester modular polymers with commercially available amines. Easily derivitized parent polymers—poly(tetrafluorophenyl acrylate) and poly(tetrafluorophenyl styrene sulfonate)—were synthesized by RAFT polymerization to yield single polymer batches containing highly reactive tetrafluorophenyl esters or sulfonate esters on each repeat unit. Tuning post-polymerization modification reaction conditions enabled the addition of sub-stoichiometric amounts of amines (relative to the repeat unit) to yield partially functionalized intermediates that could then be further derivatized. Reaction monitoring by 19 F NMR spectroscopy confirmed good control over these sequential post-polymerization modifications. This synthetic route produced a variety of copolymers with defined comonomer ratios while preserving the underlying polymer structure (degree of polymerization, dispersity, tacticity) for both the acrylate and styrene sulfonate backbones. We further applied this approach in a divergent manner to create a small library of structurally distinct copolymers from a single parent batch in three synthetic steps. This modular, divergent synthesis demonstrates a general route to structurally consistent copolymer libraries that enable systematic studies of structure–property relationships and can accelerate functional materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters

In this paper, we propose a framework called FPDeep, which uses a hybrid of model and layer paral- lelism to configure distributed reconfigurable clusters to train DNNs. This approach has numerous benefits. First, the design does not suffer from batch size growth. Second, novel workload and weight partitioning leads to balanced loads of both among nodes. And third, the entire system is fine-grained pipeline. This leads to high parallelism and utilization and also minimizes the time features need to be cached while waiting for back-propagation.

Wang, Tianqi↗

SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees

Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.

97 MATHEMATICS AND COMPUTING↗

Heat transfer from glass melt to cold cap: Computational fluid dynamics study of cavities beneath cold cap

Efficient glass production depends on the continuous supply of heat from the glass melt to the floating layer of batch, or cold cap. Computational fluid dynamics (CFD) are employed to investigate the formation and behavior of gas cavities that form beneath the batch by gases released from the collapsing primary foam bubbles, ascending secondary bubbles, and in the case of forced bubbling, from the rising bubbling gas. The gas phase fraction, temperature, and velocity distributions below the cold cap are used to calculate local and average heat transfer rates as a function of the bubbling rate. It is shown that the thickness of the cavities is nearly independent of the cold cap shape and the amount of foam evolved during batch conversion. Furthermore, it is ~7 mm and up to ~15 mm for the cases without and with forced bubbling used to promote circulation within the melt, respectively. Using computed velocity and temperature profiles, the melting rate of the simulated high-level nuclear waste glass batch was estimated to increase with the bubbling rate to the power of ~0.3 to 0.9, depending on the flow pattern. The simulation results are in good agreement with experimental data from laboratory- and pilot-scale melter tests.

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Data for An End-to-End Pipeline for Succinic Acid Production at an Industrially Relevant Scale Using Issatchenkia orientalis

Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34–90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.

Metabolomics↗

Recipe for coating ceramic blades for ion trapping

The first batches of ion traps patterned and coated were processed per the standard 3-step clean, air fire, and metallization processes. The third or fourth lot using this process resulted in poorly adhering metallization. Up until this point, the standard process was used to metallize and pattern ceramic ion traps without fail. At about the 4th batch of parts something changed. After the 5th batch, the ceramic ion traps received generally came with some unknown contamination that does not come off in a standard 3-step clean (Lenium Vapor Degreaser, Acetone, IPA) and air fire (860C for 1 hour) for which this process removes the vast majority of all contamination for most ceramic metallization. This is highly unusual. Using HF + Boiling H 2 O 2 is extreme for cleaning the ceramic ion traps. The contamination was never identified and is stubborn to effectively clean. Standard as-fired ceramic should be very easy to clean as if s fired at temperatures greater than 1400°C and not much in terms of contamination should exist at these temperatures, so there must be an intermediate step/process which is imparting this contamination. It is likely a polishing compound or previous polishing contaminant, but also not easily visually distinguishable until after metallization. The halo marks observed on parts might be fingerprints (less likely) or potential polishing marks (more likely) as metallization typically doesn't cover/hide any damage or contamination, but rather quite clearly the opposite, it accentuates it. Blotchy appearances in the metallization usually indicated an adhesion issue. As a result of the fragility of the parts (yield loss due to handling) and difficulty in identifying the contamination during cleaning, we have taken a conservative approach of HF + H 2 O 2 cleaning for all batches after the contamination and adhesion issues were identified.

36 MATERIALS SCIENCE↗

PDQ Users Manual. Manual Version 2, for PDQ Code Version 1.20

PDQ is a tool for the management of the input and execution of batch jobs for simulation codes that use a text based input system. It accomplishes this goal by operating at two levels. First, it takes input file templates (commonly known at LANL as input deck templates) and creates multiple instantiations by performing substitutions of data from table files into symbols (variables) found in the template. Second, it provides commands to submit the created files to the SLURM batch system for execution. These two activities taken together produce a whole that is greater than the sum of its parts and provides an elegant way of executing studies across multiple similar simulations while minimizing the risk of typographical errors in the input files. PDQ was originally developed as a job management system called XVS by Jeff McAninch while he was at LANL. Besides the capabilities described here, XVS had many other features specific for interactions with particular simulation codes. After Jeff’s departure, maintenance of XVS was taken over by Rendell Carver; he added some new features as well as kept it functioning as the batch system at LANL was changed from LSF to MOAB to SLURM. In 2017, Rob Pelak decided to develop a different version that removed the additional features (many of which were rendered obsolete with the retirement of the simulation code or batch system that they supported) and produced a cleaner “bare bones” version of XVS. A few other behaviors of XVS that Rob found irksome were altered. Rob gave the resulting code a new name: PDQ. In 2022 Danielle McDermott developed a version that runs under Python 3.X. As suggested by Rob, she used the python2to3 utility to identify most changes. Given that PDQ continues to operate with Python version 2.7 we have advanced the version number to 1.20.

97 MATHEMATICS AND COMPUTING↗

Preliminary IHLW Formulation Algorithm Description

This report documents the initial algorithm that could be used by the Waste Treatment and Immobilization Plant (WTP) in batching high-level waste (HLW) and glass-forming chemicals (GFCs) in the HLW melter feed preparation vessel (MFPV) (HFP-VSL-00001 and -00005). Not all Hanford tank waste can be accommodated by the models developed for this report and significant expansion of the model boundaries could be achievable to reduce the WTP mission life and total canister production count. The immobilized HLW (IHLW) must meet a series of constraints to be acceptable for disposal in the Monitored Geologic Repository, which are contained in the Specification 1 of the Contract (DOE 2000), the Waste Acceptance Product Specifications (WAPS, DOE 1996), and the Waste Acceptance System Requirements Document (WASRD, DOE 2007). The IHLW Waste Form Compliance Plan (WCP, 24590-HLW-PL-RT-07-0001, Rev 3) specifies that the formulation algorithm will be developed and used to comply with the constraints associated with glass composition and properties. This report is not an engineering calculation, does not provide design input, and is not an engineering study. Algorithm inputs include the chemical analyses of the blended HLW in the HLW blend vessel (HBV) (HLP-VSL-00028, the volume and composition of the MFPV heel, the volume and composition of the MFPV after waste addition, the volume and composition of MFPV batch after GFC addition, the compositions of individual GFCs, and the mass of glass in each canister. In addition to these inputs, uncertainties in the HLW composition and processing parameters are included in the algorithm. Using the above inputs, the algorithm calculates the following outputs: 1) the volume of HLW to be transferred from the HBV to the MFPV, 2) the mass of each GFC for addition to the MFPV, 3) the composition of the glass that will be produced along with uncertainties, and 4) the predicted properties, with associated uncertainties, of the resulting IHLW. The algorithm uses the property-composition models to calculate properties with associated uncertainties and compares them with various constraints to ensure that a processable feed is formulated and a compliant IHLW is produced. The GFC additions are determined using an optimization approach to provide high confidence that the HLW glass will meet all product quality requirements and key processing constraints. For most HLW batches there are many possible glass compositions that meet all constraints. In these cases, the glass composition is optimized for a series of target component concentrations and target property values. The algorithm also incorporates process measurement and product quality uncertainties, based on the work of Piepel et al. (2005). Estimates of the various process and measurement uncertainties that affect glass compositions and predicted glass properties have been previously reported (Piepel et al. 2005, 2006) and the impacts of these estimated uncertainties on the IHLW composition envelope that meets product quality and processing-related properties with sufficient confidence were evaluated. The details of work performed to date to develop this initial GFC addition and batching algorithm are summarized in Sections 4 and 5. An example data set is used to illustrate the calculations of the algorithm summarized in Section 6. Finally, in Section 7, there is a statement of the required work to achieve a final operational IHLW formulation control algorithm. This report is not an engineering calculation, does not provide design input, and is not an engineering study.

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Summary of Savannah River Site FY22 Salt Waste Qualification Data

The Savannah River National Laboratory analyzed samples from Savannah River Site Waste Tank 41H, 21H and 42H to support qualification of Salt Waste Processing Facility (SWPF) Waste Batches 5, 6, and 7 for processing (the FY22 Salt Batch Qualification samples). None of the samples displayed any unusual or unexpected characteristics such as large amounts of solids, floating solids, or unusual color. Characterization of these samples confirmed similar chemical composition and characteristics to previous salt waste batches. These results were initially provided to Savannah River Mission Completion (Liquid Waste Operations subcontractor) as External Sample Results LIMS Reports and the Tank 41H (Salt Batch 5 sample) was also summarized in two separate technical reports. The analytical results (both rapid and long term) are now summarized and discussed in this technical report.

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The mechanical properties of Kel-F 800 (FK-800) as a function of crystallinity

Kel-F 800 is a copolymer of chlorotrifluoroethylene PTFE (75 wt. %) and vinylidene fluoride PVDF (25 wt. %). It has previously been used as a PBX binder for insensitive explosives such as PBX 9502 and LX-17. 3M started production of Kel-F 800 in 1957 and small-scale batches continued to be made until 2002 when production ceased due to environmental concerns regarding one of the emulsifiers used during production. Around 2000 the Kel-F 800 name was changed to FK-800 to avoid trademark concerns because rights to produce another polymer with a similar tradename (Kel-F 81) had been sold to another manufacturer. The Kel designation came from the original manufacturer of PCTFE (Kel-F 81), the Kellog company. To avoid confusion this document will only refer to Kel-F 800. In 2006, production of small-scale batches of Kel-F 800 was started again by 3M in response to customer enquiries. This new material, the first blended batch is referred to as LOT 1, was produced with a different emulsifier than used previously. Because Kel-F 800 is made in a small batch reactor, considerable variation in crystallinity can be expected from lot to lot and year to year. In many ways, this is not significant since the material is dissolved in a solvent (often MEK, ethylmethyl ketone or ethyl acetate) for PBX production purposes. This destroys the as received crystallinity and the resulting crystallinity in the processed material is a function of polymer molecular weight and thermal history. Producing large billets of Kel-F 800 from solvent extraction is not practical and so a compression molding technique has been used above the melting temperature. This method also removes residual crystallinity from the supplied granules. The molecular weight of a polymer can be estimated by several techniques, the most common being gel permittivity chromatography (GPC), size exclusion chromatography (SEC) and shear rheometry measurements of polymer/solvent solutions. Changes in molecular weight will affect the crystallization rate and the maximum crystallinity reached for a specific thermal history. Both references agree that the new LOT 1 material molecular weight falls within the deviation found from averaging previous historical lots of Kel-F 800.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dispersible Colloid Facilitated Release of Organic Carbon From Two Contrasting Riparian Sediments

In aqueous systems, including groundwater, nano-colloids (1–100 nm diameter) and small colloids (<450 nm diameter) provide a vast store of surfaces to which organic carbon (OC) can sorb, precluding its normal bioavailability. Because nanomaterials are ubiquitous and abundant throughout Earth systems, it is reasonable that they would play a significant role in biogeochemical cycles. As such, mineral nano-colloids (MNC) and small colloids, formed through mineral weathering and precipitation processes, are both an unaccounted-for reservoir and unquantified vector for transport of OC and nutrients and contaminants within watersheds. Water extractions and leaching experiments were conducted under (1) aerobic (ambient) and (2) anaerobic (environmental chamber) conditions for each of two contrasting riparian sediments from (1) Columbia River, Washington and (2) Tims Branch, South Carolina. Water dispersible colloid-adsorbed OC was as high as 48% of OC for Tims Branch anaerobic batch water extraction and as low as 0% for Columbia River aerobic batch water extractions. Anaerobic leaching from column experiments yielded higher colloid and OC release rates. Transmission electron microscopy with electron dispersive spectroscopy mapping revealed organic carbon associated with aggregations of nano-particulate silicate minerals and Mossbauer identified nano-particulate goethite. This exploratory study demonstrates that mineral facilitated release of OC in riparian sediments is both significant and variable between locations.

Rod, Kenton A.↗

Evaluation of Material Balance Approaches for Hanford Direct-Feed Low Activity Waste Processing - 20022

The Hanford Site has accumulated millions of gallons of tank waste from reprocessing spent fuel to recover plutonium, uranium, cesium, and strontium. The supernatant from the accumulated tank waste will be treated using a Direct Feed Low-Activity Waste approach. The supernatant will be treated to remove solids and cesium in the Tank-Side Cesium Removal process in the Hanford tank farm, then vitrified in a semi-batch process in the Hanford Waste Treatment and Immobilization Plant (WTP). Currently, each batch of feed is sampled at three locations prior to being fed to the melter: the feed qualification tank in the Hanford tank farm as well as the concentrate receipt vessel (CRV) and melter feed preparation vessel (MFPV) in the WTP. The feed qualification sample is taken from a large batch of accumulated feed, only two to three samples are expected each year. Approximately 275 samples from the CRVs and 1100 samples from the MFPV are expected each year. An evaluation was performed to determine if a material balance based on the feed qualification sample could replace most of the sampling in the CRVs and MFPVs. The evaluation consisted of three elements: (1) determination of the practicality of using a material balance to estimate the stream composition of the CRV and MFPV contents, (2) evaluation of whether the material balance could be automated using the existing process control system, and (3) determination of the uncertainty in glass composition using the material balance approach. It is assumed that periodic sampling at the CRV and MFPV would be performed periodically to re-baseline the material balance, evaluations are in progress to determine the frequency of this periodic sampling. Process sample locations downstream of the melter were reviewed as well, but the partitioning of semi-volatile species in the melter was determined to preclude extending the material balance approach past the melter. It was determined that replacement of the CRV sample location was feasible and did not increase process uncertainty or significantly impact waste loading. Replacement of the MFPV sample was also determined to be feasible, but that measurement of the glass former chemical addition may be needed prior to addition of these chemicals to the MFPV. This measurement could be performed by an in situ laser-induced breakdown spectroscopy (LIBS) system. Limited tests were performed to evaluate LIBS for direct measurements of the low-activity waste melter feed. The use of a material balance would eliminate over 1200 samples each year if only 10% of the CRV and MFPV batches are sampled and could likely allow the WTP laboratory to operate on days only versus 24/7 operation. (authors)

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TCCR Operational Summary and Optimization for Tank 9 Processing - 20314

Savannah River Remediation (SRR) manages and operates the liquid waste facilities at Savannah River Site (SRS) for the Department of Energy (DOE). Stored liquid waste is a complex mixture of insoluble solids (sludge) and soluble salts in an alkaline solution. SRR has deployed the Tank Closure Cesium Removal (TCCR) system, a tank-side ion exchange process, to remove radioactive cesium from salt waste and enable onsite disposal of the resulting decontaminated salt solution as low-level waste at the Saltstone facilities. The TCCR system consists of two prefilters, four ion exchange (IX) columns, one resin trap, and a ventilation system. The IX process uses a form of inorganic crystalline silicotitanate (CST), which has a high affinity for cesium and other alkali metals, strontium, and actinides. This process is currently deployed utilizing salt feed from Tank 10, with future plans to dissolve solid salt in Tank 9 and transfer the salt solution to Tank 10 for processing through TCCR. The feed for TCCR must be created from salt-cake in Tank 10 through a dissolution process. Once enough salt has been dissolved, a qualification process is entered. This process characterizes the feed and ensures the cesium loading on the columns will not cause boiling of waste within the columns during or after processing. Once the batch has been qualified, salt waste is fed to the TCCR system through a transfer pump in the center of the tank. The waste is filtered through a set of two shielded, dead-end prefilters that prevent solids buildup in the columns. The filtered salt solution then travels to the shielded IX columns, which can be operated individually or in series, where the cesium is sorbed on the CST media. The decontaminated salt solution (DSS) then travels through a resin trap and out of the module to Tank 11. TCCR has successfully processed approximately 795,000 L of Tank 10H radioactive salt waste over two batches to date. There has not yet been a system induced shutdown. The prefilters performed as expected with only minor degradation in recovery of differential pressure after a backflush sequence. The time between backflushes decreased as each batch reached the end of processing. The hydraulics in the IXCs mostly performed as expected at all flow rates, except for one IXC that will be further investigated during Batch 3 processing. The TCCR system has shown some opportunities for more efficient processing during the length of the demonstration so far. For future processing of material from Tank 9H through Tank 10H and the TCCR unit, TCCR 1A will implement changes to the prefilters and the IXCs. The prefilters will have an increased surface area and a new filter media in an effort to increase time between filter swaps and improve backwashing cleaning capability. The IXCs will have a reduced diameter to allow for increased heat transfer out of the column and increased loading of Cs-137. Additionally, a new form of CST with an increased kinetic performance is being investigated for use during TCCR 1A operation. (authors)

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In-Band Scattering and Absorption of Infrared Blocking Foam Filters for Millimeter-wave Cameras

Expanded closed-cell polymer foams are widely used as thermal infrared (IR) blocking filters in millimeter-wave cameras, particularly for Cosmic Microwave Background observations. Precise knowledge of their millimeter-wave properties is essential for optimizing sensitivity. We present broadband (150 GHz - 2 THz) transmittance spectroscopy of Styroace-II and several Zotefoam filters, fitting their spectra with a radiative transfer model incorporating dielectric absorption and Rayleigh, Mie, and higher-order scattering. For a typical 5~cm thick filter stack at 280~GHz, Styroace-II exhibits ${\sim}10\%$ scattering with absorption estimated as ${\lesssim}5\%$ by effective-medium theory, while Zotefoam HD30 offers superior performance at ${\sim}3\%$ scattering and absorption likewise bounded to ${{\lesssim}0.3\%}$. Each model component is constrained at the ${\sim}0.1\%$ transmittance level for millimeter wavelengths. We observe batch-to-batch scattering variability of up to 2 percentage points in foams with multiple tested batches. Less commonly used Zotefoam formulations (LD15 and LD24) can further reduce in-band scattering to ${<}1\%$ while maintaining negligible in-band absorption and likely comparable IR blocking due to shared polyethylene absorption features and similar cell sizes. Based on this work, a filter constructed from the best measured LD24 batch has replaced the Styroace-II filter in a Simons Observatory 220/280 GHz Small Aperture Telescope.

Thomas, Alex [Chicago U., Astron. Astrophys. Ctr.;↗

Metal leaching from Lithium-ion and Nickel-metal hydride batteries and photovoltaic modules in simulated landfill leachates and municipal solid waste materials

Photovoltaic (PV) modules and batteries can either be recycled or disposed of in landfills at end-of-life (EoL). This work focuses on disposal since the benefit of recycling PV modules and batteries is well established. This study characterizes the potential toxicity due to metals leaching from selected PV modules and batteries through both the Toxicity Characteristic Leaching Procedure (TCLP) and in-house batch leaching protocols to probe the impact on metallic ion mobility as a function of the different types of e-waste entering the waste stream, the magnitude of device damage when placed into the waste stream, and the simulated municipal solid waste (SMSW) composition. Our results showed that one PV module and three battery types in this study should be classified as hazardous waste within the U.S. However, for some of the other e-wastes, metals of concern including Cr, Cu, Hg, Ni, Pb, and Zn leached during the batch tests but not in the TCLP regulatory method. For most of the waste types, the amounts of metals that leached in the TCLP test and batch tests were much lower than the total extractable amounts, demonstrating the potential for additional unaccounted for amounts of metals to leach. Our results demonstrate that the TCLP regulatory method might fail at predicting potential leaching and at capturing the complexity of e-waste leaching in landfill conditions. It confirms that additional work is needed urgently to develop appropriate EoL procedures for MSW with PV and battery e-waste.

42 ENGINEERING↗

Summary of Results from November 2021 Qualification Samples for Tank Closure Cesium Removal 1A (TCCR 1A)

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal 1A (TCCR 1A) process to remove 137 Cs from tank waste supernate using an ion exchange process. As part of that process, Savannah River National Laboratory (SRNL) receives and analyzes samples in support of the qualification of each batch to be processed. SRNL recently received supernate samples retrieved from Tank 10H as well as in-tank batch contact samples for characterization in support of qualifying Batch 1 for processing through the TCCR 1A unit.

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Active Learning‐Driven Inkless Additive Nanomanufacturing for Printed Electronics

Inkless additive nanomanufacturing for printed electronics promises broad material and substrate versatility, yet the high-dimensional print parameter space makes tuning print parameters time-intensive. We present a Bayesian optimization study that constructs a digital twin from printed-silver data to benchmark surrogate models, acquisition functions, and batch sizes head-to-head to achieve user-specified target resistance. Tested surrogate models included Gaussian process, random forest, and Bayesian neural network surrogates with expected improvement and confidence bound acquisition functions. In total, we evaluate 48 unique model configurations alongside a random sampling baseline for comparison. For printed silver, the Bayesian neural network with a batch size of one achieved the lowest average cumulative regret, approximately four times more efficient on average than random sampling. To balance performance and substrate space, a random forest model with expected improvement and a batch size of four was chosen as the model for validation testing. Applying this chosen configuration to copper with an additional print parameter, the model achieved a resistance within 0.15 Ω of a 1 Ω target in fewer than 30 printed lines across five validation sets. Altogether, the workflow yields a tuned and validated model that efficiently guides experiments toward the target while simultaneously learning the parameter space.

Bevel, Colton [Auburn University, AL (United State↗

Enabling energy‐efficient manufacturing of pharmaceutical solid oral dosage forms via integrated techno‐economic analysis and advanced process modeling

Abstract The global pharmaceutical industry is a trillion‐dollar market. However, the pharmaceutical sector often lags in manufacturing innovation and automation which limits its potential to maximize energy efficiency. The integration of techno‐economic analysis (TEA) with advanced process models as part of an overarching smart manufacturing platform, can help industries create business models, which can be adapted for manufacturing to reduce energy consumption and operating costs while ensuring product quality which can further enable a more sustainable process operation. In this study, a rational design of experiment on three unit‐operations (wet granulation, drying, and milling) was performed on a batch (case 1) and continuous (case 2) pharmaceutical process to obtain experimental data. Process models for predicting product quality and energy efficiency of each of the three‐unit operations were developed. The experimental data were used to validate the models and good agreement was observed. The energy consumption of each unit operation was calculated using statistical models relating the power consumption and the process parameters. The developed process models and energy models were further integrated into a TEA framework, which quantified the energy and monetary cost of manufacturing for both batch and continuous manufacturing cases. With this integrated framework, energy costs savings of ~33% was obtained in the continuous manufacturing process (case 2) over the batch process (case 1).

Sampat, Chaitanya↗