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At least 127 records · Page 7

Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing

Additive manufacturing (AM) enables the fabrication of complex designs that are difficult to create by other means. Metal parts manufactured by laser powder bed fusion (LPBF) can incorporate intricate design features and demonstrate desirable mechanical properties. However, printing a part that is qualified for its intended application often involves reprinting and discarding many parts to eliminate defects, improve dimensional accuracy, and increase repeatability. The process of iteratively converging on the appropriate build parameters increases the time and cost of creating functional LPBF manufactured parts. This work describes a fast, scalable method for part-scale process optimization of arbitrary geometries. Additionally, the computational approach uses feature extraction to identify scan vectors in need of parameter adaptation and applies results from simulation-based feed forward control models. This method provides a framework to quickly optimize complex parts through the targeted application of models with a range of fidelity and by automating the transfer of optimization strategies to new part designs. The computational approach and algorithmic framework are described, a software package is implemented, the method is applied to parts with complex features, and parts are printed on a customized open architecture LPBF machine.

3D printing↗

Ammonia in northeast Colorado is increasing, rising most quickly in regions close to confined animal feeding operations

The Colorado Front Range urban corridor and nearby agricultural operations are important source regions of atmospheric ammonia (NH 3 ). Upslope flows periodically transport these emissions into Rocky Mountain National Park (RMNP), located 50 km west of the urban corridor, where wet and dry deposition of excess reactive nitrogen (N) impacts ecosystems. Here, we use a combination of in situ passive NH 3 measurements and NH 3 vertical column density retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) to assess variability and changes in NH 3 across three land use categories in the northeast Colorado source region (agricultural, urban, and remote) during the period 2013-2023. A strong seasonal cycle is present across the region with increased NH 3 during summer months. Elevated NH 3 is spatially correlated with the number of permitted animal units in confined animal feeding operations (CAFOs) within 12 km. Ground-level NH 3 concentrations are strongly positively correlated with monthly gridded IASI satellite column densities. Satellite retrievals reveal an increasing trend in NH 3 column amounts of ∼3% per year in agricultural and ∼2% per year in urban sub-regions. The magnitude of the trend observed in NH 3 columns averaged over the agricultural sub-region is > 3 times larger than observed near and over Denver. The largest increases in NH 3 are closely aligned with the distribution of CAFOs. Reductions in particle sulfate associated with declining sulfur dioxide (SO 2 ) emissions could account for only ∼0.1% per year increase in gaseous NH 3 . Wildfire smoke across the region has increased but appears unlikely to explain the majority of the observed NH 3 increase.

54 ENVIRONMENTAL SCIENCES↗

An experimental and modeling study of the application of membrane contactor reactors to methanol synthesis using pure CO 2 feeds

We describe here a post-combustion CO 2 capture and utilization (CCU) technology that converts the CO 2 into methanol (MeOH), a valuable chemical, thus providing a way to monetize the carbon captured to offset process costs. Methanol synthesis (MeS) has been discussed recently for application to CCU, but thermodynamic limitations make it difficult to convert in a single pass a large CO 2 fraction. Conventional catalysts show slow kinetics in converting CO 2 -rich syngas (or pure CO 2 ) into MeOH. Our Group developed a novel MeS process, employing a membrane contactor reactor (MCR) system that attains carbon conversions significantly higher than equilibrium. Our focus here is to process pure CO 2 streams by combining the MCR with a separate reactor, which converts the CO 2 into a syngas via the reverse water gas shift (RWGS) reaction. In this preliminary effort, the RWGS reactor (RWGSR) is assumed to reach equilibrium. Additional MeS kinetic rate data are generated validating experimentally the ability of the MeS-MCR to process as a feed the RWGSR exit stream. The performance of the combined (RWGSR/MeS-MCR) system is then simulated using a recently developed MeS-MCR model. In conclusion, the findings are encouraging, and research is currently ongoing to experimentally validate the RWGSR/MeS-MCR system performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulations of biomass compression-screw feeding using a compressible non-Newtonian constitutive model

There is global interest in the conversion of biomass into sustainable low-carbon-footprint fuels and chemicals as an alternative to non-renewable fossil feedstocks. Feeding biomass solids into pressurized reactors is one of the key steps in biomass conversion. Predicting mechanical failure and energy requirements for this step helps avoid upstream processing bottlenecks and enables efficient operation of a biorefinery. Here, in this work, we developed a predictive computational model for biomass screw feeders that capture the highly viscous, non-Newtonian and compressible behavior of biomass slurries. Biomass compressible behavior is formulated by an equation of state and the non-Newtonian rheology is represented by a density-dependent viscosity model. Experimental data from two compression screw-feeder systems are presented as a validation for our model. Our model successfully predicted the location of the compressed biomass “plug”, biomass flow rate, and the required torque at different operating conditions for the experimental conditions studied in this work.

09 BIOMASS FUELS↗

De-Risking High-Recovery Brackish Water Desalination via Flow Reversal and Feed Flushing Using Techno-Economic Assessment

Novel desalination technologies have demonstrated enhanced performance and improved financial metrics over existing processes adopted by industry. Establishing quantitative performance targets is essential for achieving financial benefits over the current state of the art. Herein, we demonstrate how WaterTAP, a techno-economic assessment (TEA) tool, can be used to identify minimum performance metrics necessary to achieve financial benefit over using existing processes. This study evaluates the feasibility of increasing water recovery at the Chino Desalter I above 90 % through the addition of a third variable configuration reverse osmosis (VCRO) stage. Sensitivity analyses revealed flow reversal frequency, feed flushing volume (used as a cleaning step), and membrane lifespan are key factors influencing the financial viability of the VCRO process. The TEA analysis demonstrated that the system must achieve a recovery of 84 % and a 1-year membrane lifespan to have a breakeven LCOW, while achieving 90 % recovery can ultimately reduce the LCOW by 16 %. Notably, a trade-off between decreasing frictional losses and increased osmotic pressure across the recovery range, resulted in a stable specific energy consumption across the recovery range, enabling meaningful LCOW reductions without an energy penalty, a key finding that contrasts with conventional RO. This work demonstrates how TEA can guide system design by identifying key performance targets and exploring trade-offs, enabling data-driven decisions to de-risk innovative processes. These findings underscore the importance of leveraging TEA to evaluate scaling mitigation strategies and optimize inland desalination systems for sustainable and cost-effective operation.

14 SOLAR ENERGY↗

ACORN Review: NPK fertilizer use in loblolly pine plantations: Who are we really feeding?

Optimizing loblolly pine (Pinus taeda L.) productivity using fertilizers and various site management practices has been a goal of foresters for decades. Nitrogen (N), phosphorus (P), and potassium (K) are the three most operationally applied fertilizers to loblolly pine silviculture and are of primary importance to their total productivity. Fertilizer recommendations for N, P, and K in loblolly pine are primarily made on abiotic factors such as site and soil characteristics, while the biological factors controlling nutrient uptake are typically overlooked in the production and optimization of these stands. Arguably the most important of these biological factors are the diverse ectomycorrhizal fungal (ECM) communities that colonize the fine roots of almost all loblolly pine trees. The mantle formed by ECM fungi on short-root tips presents a barrier for direct apoplastic uptake of N, P, and K from soil solution by pine roots. In well-colonized roots, the tree is dependent on symplastic fungal transport of N, P, and K foraged from the soil by the extraradical hyphal network. This raises the question: Who are we really feeding if the ECM fungi are the ones assimilating most of the tree's total nutritional requirements? Considering multiple species of ECM fungi can inhabit a single root system, many questions remain regarding the drivers of colonization, why some species are more efficient at taking up and exchanging nutrients with their hosts than others, and why certain fertilizers directly affect the morphology of ECM growth. The purposes of this review here are (1) to explore how the most commonly commercially applied macronutrients, N, P, and K, affect the relationship between loblolly pine and ECM communities, and (2) to propose future directions to investigate, preserve, and manipulate these interactions in pine plantations to optimize productivity.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty propagation in feed-forward neural network models

We develop new uncertainty propagation methods for feed-forward neural network architectures with leaky ReLU activation functions subject to random perturbations in the input vectors. In particular, we derive analytical expressions for the probability density function (PDF) of the neural network output and its statistical moments as a function of the input uncertainty and the parameters of the network, i.e., weights and biases. A key finding is that an appropriate linearization of the leaky ReLU activation function yields accurate statistical results even for large perturbations in the input vectors. This can be attributed to the way information propagates through the network. We also propose new analytically tractable Gaussian copula surrogate models to approximate the full joint PDF of the neural network output. To validate our theoretical results, we conduct Monte Carlo simulations and a thorough error analysis on a multi-layer neural network representing a nonlinear integro-differential operator between two polynomial function spaces. Our findings demonstrate excellent agreement between the theoretical predictions and Monte Carlo simulations.

MLP networks↗

Artificial intelligence time series forecasting for feed-forward laser stabilization

Laser plasma accelerators, typically operating at 1–10 Hz repetition rates, have the ability to produce high-quality electron beams in compact, all-optical-driven configurations, with the electron beams uniquely suited for a wide variety of accelerator-based applications. However, fluctuations and drifts in the laser delivery to the meter-scaled and below plasma target (the electron beam source) will translate into electron beam source variations that can limit their utility for demanding applications like light sources or linear colliders. Commercially available active feedback laser stabilization systems are intrinsically bandwidth limited due to their integration with multi-inch corrective mirror mounts which minimizes their effectiveness. In this manuscript, we present a Neural Network time series forecaster that can predict laser position fluctuations of the laser delivery to the final target well ahead of a future laser shot. The Root-Mean-Square-Error (RMSE) of the prediction accuracy was < 2 μ m for a 1 / e 2 beam radius of 34 μ m . Our feed-forward approach serves as a first-step in circumventing the bandwidth limitations imposed by the currently available stabilization systems since it allows for mirrors to be moved into position ahead of time to offset the predicted future position drift. This will help advance laser plasma accelerator research by providing greater robustness and stability needed for its applications.

Berger, Curtis↗

Re-directing mixed-feed deconstruction products to hybrid polyesters: Tolerance windows for commodity plastics reconstruction

Solvolysis is a promising strategy for mixed-feed polyester recycling, but little attention has been given to downstream product separations or the impact of using imperfectly separated monomer mixtures in recycled polymer reconstruction. Here, we challenge the traditional need for high-purity monomers in polycondensation synthesis of engineering thermoplastics. Monomer mixtures are derived from catalyzed methanolysis of polyethylene terephthalate (PET), polybutylene terephthalate (PBT), and polybutylene adipate-co-terephthalate (PBAT), with separation scenarios ranging from high (99:1) to low (90:10) purity. We focus on challenging-to-separate products like ethylene glycol and 1,4-butanediol and evaluate tolerance for comonomer incorporation in recycled hybrid polyesters: polybutylene-co-ethylene terephthalate (PBET) and polybutylene ethylene adipate-co-terephthalate (PBEAT). Evaluations are made between “contaminant” monomer incorporation, and the resulting materials’ thermal properties, crystalline structure, tensile toughness, and rheology. Ultimately, we highlight that despite incorporation of contaminant monomer, high-performance hybrid polyesters of PET, PBT, and PBAT are obtained while reducing the strain of high-throughput separations.

36 MATERIALS SCIENCE↗

Atomically Dispersed Tin-Modified $\gamma$-alumina for Selective Propane Dehydrogenation under H 2 S Co-feed

Developing an earth-abundant catalyst that is sulfur-tolerant, active, and highly selective is of great interest for valorizing natural gas streams containing sour gas. Here, a tin-modified alumina catalyst is reported that is stable and selective for propane dehydrogenation in the presence of percent quantities of H 2 S in the feed. In particular, Sn/Al 2 O 3 –S catalysts with 1.5–5% Sn content exhibit 98% selectivity with up to 16% conversion at 560 °C during the fourth cycle. Experimental and computational characterization shows that the active sites are the defect tricoordinated Al atoms. H 2 S pretreatment further modifies a portion of these sites via exchanging a neighboring oxygen atom with sulfur, thereby rendering them more active and selective. At low loadings, Sn is atomically dispersed and selectively binds to hydroxyl groups or oxygen atoms on Al 2 O 3 . This prevents the formation of original (unmodified) defect sites on Al 2 O 3 and improves overall selectivity. The activity and selectivity of the catalyst are heavily dependent on the chemical potential of sulfur and hydrogen because they influence both the relative concentration of the two types of sites and the overall reaction mechanism. Finally, the catalyst can be regenerated fully under a pure H 2 S stream, thereby precluding treatment under oxygen, which can lead to sintering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A novel d-xylose isomerase from the gut of the wood feeding beetle Odontotaenius disjunctus efficiently expressed in Saccharomyces cerevisiae

Carbohydrate rich substrates such as lignocellulosic hydrolysates remain one of the primary sources of potentially renewable fuel and bulk chemicals. The pentose sugar d-xylose is often present in significant amounts along with hexoses. Saccharomyces cerevisiae can acquire the ability to metabolize d-xylose through expression of heterologous d-xylose isomerase (XI). This enzyme is notoriously difficult to express in S. cerevisiae and only fourteen XIs have been reported to be active so far. We cloned a new d-xylose isomerase derived from microorganisms in the gut of the wood-feeding beetle Odontotaenius disjunctus. Although somewhat homologous to the XI from Piromyces sp. E2, the new gene was identified as bacterial in origin and the host as a Parabacteroides sp. Expression of the new XI in S. cerevisiae resulted in faster aerobic growth than the XI from Piromyces on d-xylose media. The d-xylose isomerization rate conferred by the new XI was also 72% higher, while absolute xylitol production was identical in both strains. Interestingly, increasing concentrations of xylitol (up to 8 g L –1 ) appeared not to inhibit d-xylose consumption. The newly described XI displayed 2.6 times higher specific activity, 37% lower KM for d-xylose, and exhibited higher activity over a broader temperature range, retaining 51% of maximal activity at 30 °C compared with only 29% activity for the Piromyces XI.

59 BASIC BIOLOGICAL SCIENCES↗

The algae revolution 2.0: the potential of algae for the production of food, feed, fuel and bioproducts – why we need it now

Algae made our world possible, and it can help us make the future more sustainable; but we need to change the way we live and adopt new more efficient production systems, and we need to do that now. When the world was new, the atmosphere was mainly carbon dioxide, and no animal life was possible. Along came algae with the process of photosynthesis, and things began to change. Ancient cyanobacteria algae turned carbon dioxide into enormous sums of lipids, proteins and carbohydrates, while they secreted oxygen into the atmosphere. Over a billion years, as oxygen filled the air and algae filled the seas, animal life became possible. Eventually all that algae biomass became petroleum and natural gas, which for eons sat undisturbed in vast underground reservoirs, holding enormous sums of untapped energy. Less than 200 years ago humans learned to tap these energy reserves to create the world we know today, but in so doing, we have released millions of years of stored CO 2 back into the atmosphere. Algae can again help make the world a better place, but this will require new thinking and new ways of producing our food, feed and fuels. We need an algae revolution 2.0.

59 BASIC BIOLOGICAL SCIENCES↗

Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Wire-feed additive manufacturing (WFAM) produces superalloys with complex thermal cycles and unique microstructures, often requiring optimized heat treatments. To address this challenge, we present a hybrid approach that combines high-throughput experiments, precipitation simulation, and machine learning to design effective aging conditions for the WFAM Haynes 282 superalloy. Our results demonstrate that the γ’ radius is the critical microstructural feature for strengthening Haynes 282 during post-heat treatment compared with the matrix composition and γ’ volume fraction. New aging conditions at 770°C for 50 hours and 730°C for 200 hours were discovered based on the machine learning model and were applied to enhance yield strength, bringing it on par with the wrought counterpart. This approach has significant implications for future AM alloy production, enabling more efficient and effective heat treatment design to achieve desired properties.

CALPHAD↗

β-decay feeding intensity distributions of 71,73 Ni

This paper presents the β-decay feeding intensity distribution and Gamow-Teller transition strength distribution of 71,73 Ni. These quantities were measured using the technique of total absorption spectroscopy at the National Superconducting Cyclotron Laboratory with the Summing NaI(Tl) detector. These measurements provide sensitive constraints to theoretical models used to predict β-decay properties far from stability for astrophysical applications. Specifically, for the astrophysical r process, the majority of the involved nuclei are not accessible by current facilities, and the nuclear input is mainly provided by theory. Furthermore, the present work reports on two neutron-rich nickel isotopes in the region where the weak r process is expected to be relevant in stellar nucleosynthesis. The experimental results are compared to two theoretical models, namely the shell model and the quasiparticle random-phase approximation, to help further refine theoretical calculations and aid in future r-process studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

β -decay feeding intensity distribution of Mn 64

Nuclei around the N=40 “Island of Inversion” exhibit interesting structure features that have been the focus of several experimental and theoretical studies. Here, the present work presents the first complete study of the β-decay feeding intensity distribution and Gamow-Teller distribution for the β decay of 64 Mn to 64 Fe up to ~10 MeV. The β-decay intensity function was extracted from Total Absorption Spectroscopy measurements made at the National Superconducting Cyclotron Laboratory with the Summing NaI(Tl) (SuN) detector. The experimental results are compared to shell model calculations with and without the inclusion of the νg 9/2 orbital. From this comparison it is clear that the νg 9/2 orbital is essential for the accurate description of the 64 Fe β-decay strength above ~3 MeV, emphasizing once again the transitional nature of this nucleus into the N=40 Island of Inversion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cross-Feedings, Competition, and Positive and Negative Synergies in a Four-Species Synthetic Community for Anaerobic Degradation of Cellulose to Methane

A synthetic community was designed using four microbial species that together performed distinct key metabolic processes in the anaerobic degradation of cellulose to methane and CO 2 . The microorganisms exhibited expected interactions, such as cross-feeding of acetate from a cellulolytic bacterium to an acetoclastic methanogen and competition of H 2 between a sulfate reducing bacterium and a hydrogenotrophic methanogen.

59 BASIC BIOLOGICAL SCIENCES↗

Acetonitrile Destruction in ETF Feed Solutions by UV/OX and Persulfate (Final Report)

The Hanford Site Effluent Treatment Facility (ETF) currently treats aqueous waste streams that include condensates from the 242-A evaporator, leachate from the Environmental Restoration Disposal Facility (ERDF), as well as laboratory wastes and, in the future, will treat liquid effluents from the Hanford Waste Treatment and Immobilization Plant (WTP) and Integrated Disposal Facility (IDF) leachate. Liquid effluents from the WTP will have significant concentrations of acetonitrile. Acetonitrile is formed by reaction of nitrates and sugar in the WTP low activity waste (LAW) melters and is prevalent in the submerged bed scrubber (SBS) and wet electrostatic precipitator (WESP) liquid effluents from WTP off-gas treatment. When these liquids are concentrated in the WTP Effluent Management Facility (EMF) evaporator in the direct feed low activity waste (DFLAW) flow-sheet, testing has shown that the majority of the acetonitrile partitions to the evaporator condensate. Since the evaporator condensate is directed to the ETF, this creates a potential issue with the ETF waste acceptance criteria and, specifically, the ETF Delisting Modification treatability envelope limits. Consequently, there is a need to assess possible mitigation approaches, one of which involves identification and assessment of potential treatment processes to destroy the acetonitrile, which is the subject of the present report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluation of Ammonium and Iodine Decontamination Factors for Hanford's Waste Treatment and Immobilization Plant Feed in the Effluent Treatment Facility

Savannah River National Laboratory (SRNL) reviewed the unit operations in the Effluent Treatment Facility (FTP) at the Hanford site to estimate the partitioning of iodine and ammonia when processing Waste Treatments and Immobilization Plant (WTP) feed. The evaluation consisted of literature and vendor data reviews and no experiments were performed. A list of the unit operations reviewed, along with estimated decontamination factors (DFs) for both iodine and ammonium are shown in the table below. With the exception of the Peroxide Decomposer, reasonable estimations of the decontamination factors for all operations are provided.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗