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At least 631 records · Page 35

Impacts of half a degree additional warming on the Asian summer monsoon rainfall characteristics

This study investigates the impacts of global warming of 1.5 °C and 2.0 °C above pre-industrial conditions (Paris Agreement target temperatures) on the South Asian and East Asian monsoon rainfall using five atmospheric global climate models participating in the 'Half a degree Additional warming, Prognosis and Projected Impacts' (HAPPI) project. Mean and extreme precipitation is projected to increase under warming over the two monsoon regions, more strongly in the 2.0 °C warmer world. Moisture budget analysis shows that increases in evaporation and atmospheric moisture lead to the additional increases in mean precipitation with good inter-model agreement. Analysis of daily precipitation characteristics reveals that more-extreme precipitation will have larger increase in intensity and frequency responding to the half a degree additional warming, which is more clearly seen over the South Asian monsoon region, indicating non-linear scaling of precipitation extremes with temperature. Strong inter-model relationship between temperature and precipitation intensity further demonstrates that the increased moisture with warming (Clausius-Clapeyron relation) plays a critical role in the stronger intensification of more-extreme rainfall with warming. Lastly, results from CMIP5 coupled global climate models under a transient warming scenario confirm that half a degree additional warming would bring more frequent and stronger heavy precipitation events, exerting devastating impacts on the human and natural system over the Asian monsoon region.

54 ENVIRONMENTAL SCIENCES↗

New Era Towards Autonomous Additive Manufacturing: A Review of Recent Trends and Future Perspectives

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Fan, Haolin↗

Joint inference of multiplicative and additive systematics in galaxy density fluctuations and clustering measurements

Galaxy clustering measurements are a key probe of the matter density field in the Universe. With the era of precision cosmology upon us, surveys rely on precise measurements of the clustering signal for meaningful cosmological analysis. However, the presence of systematic contaminants can bias the observed galaxy number density, and thereby bias the galaxy two-point statistics. As the statistical uncertainties get smaller, correcting for these systematic contaminants becomes increasingly important for unbiased cosmological analysis. We present and validate a new method for understanding and mitigating both additive and multiplicative systematics in galaxy clustering measurements (two-point function) by joint inference of contaminants in the galaxy overdensity field (one-point function) using a maximum-likelihood estimator (MLE). We test this methodology with Kilo-Degree Survey-like mock galaxy catalogues and synthetic systematic template maps. We estimate the cosmological impact of such mitigation by quantifying uncertainties and possible biases in the inferred relationship between the observed and the true galaxy clustering signal. Our method robustly corrects the clustering signal to the sub-percent level and reduces numerous additive and multiplicative systematics from 1.5σ to less than 0.1σ for the scenarios we tested. In addition, we provide an empirical approach to identifying the functional form (additive, multiplicative, or other) by which specific systematics contaminate the galaxy number density. Even though this approach is tested and geared towards systematics contaminating the galaxy number density, the methods can be extended to systematics mitigation for other two-point correlation measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Additive and Subtractive Manufacturing Augmented Reality Interface (ASMARI)

Industry 4.0 represents the next evolution of industrial technology. Some of the key characteristics of Industry 4.0 include augmented reality and additive manufacturing. In support of this evolution, researchers at Oak Ridge National Lab created a prototype augmented reality (AR) interface, ASMARI. This prototype acts as a common interface for both industrial additive and subtractive machines. Additionally, in the changing industrial workspace of Industry 4.0, the role of humans will also change. This interface focuses on increasing productivity and situational awareness, while providing new interaction modalities for interacting with hardware. The prototype was also evaluated by multiple users who provided positive feedback on the system. Ultimately, the prototype represents a first step towards significant integration between augmented reality and additive manufacturing.

Borish, Michael↗

Long-term nitrogen addition modifies microbial composition and functions for slow carbon cycling and increased sequestration in tropical forest soil

Nitrogen (N) deposition is a component of global change that has considerable impact on belowground carbon (C) dynamics. Plant growth stimulation and alterations of fungal community composition and functions are the main mechanisms driving soil C gains following N deposition in N-limited temperate forests. In N-rich tropical forests, however, N deposition generally has minor effects on plant growth; consequently, C storage in soil may strongly depend on the microbial processes that drive litter and soil organic matter decomposition. Here, we investigated how microbial functions in old-growth tropical forest soil responded to 13 years of N addition at four rates: 0 (Control), 50 (Low-N), 100 (Medium-N), and 150 (High-N) kg N ha -1 year -1 . Soil organic carbon (SOC) content increased under High-N, corresponding to a 33% decrease in CO 2 efflux, and reductions in relative abundances of bacteria as well as genes responsible for cellulose and chitin degradation. A 113% increase in N 2 O emission was positively correlated with soil acidification and an increase in the relative abundances of denitrification genes (narG and norB). Soil acidification induced by N addition decreased available P concentrations, and was associated with reductions in the relative abundance of phytase. The decreased relative abundance of bacteria and key functional gene groups for C degradation were related to slower SOC decomposition, indicating the key mechanisms driving SOC accumulation in the tropical forest soil subjected to High-N addition. However, changes in microbial functional groups associated with N and P cycling led to coincidentally large increases in N 2 O emissions, and exacerbated soil P deficiency. These two factors partially offset the perceived beneficial effects of N addition on SOC storage in tropical forest soils. Finally, these findings suggest a potential to incorporate microbial community and functions into Earth system models considering their effects on greenhouse gas emission, biogeochemical processes, and biodiversity of tropical ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Impacts of the Additive Manufacturing Process on the Roughness of Engine Scale Vanes and Cooling Channels

Abstract By leveraging the additive manufacturing (AM) platform, development time and costs for turbine component testing can be reduced relative to traditional investment casting. Surface roughness is a key characteristic of the additive manufacturing process that can impact flow, heat transfer, and mechanical integrity of printed components. There are multiple design and build considerations that result in variability in surface roughness, especially when additively fabricating complicated three-dimensional vanes and internal cooling passages. This study characterizes the surface roughness of internal cooling passages, vanes, and flat external surface samples made using additive manufacturing, specifically the direct metal laser sintering process. The samples were manufactured with various wall thicknesses, layer thicknesses, build locations, build directions, and on different AM machines. A combination of computed tomography scanning and optical profilometry was used to evaluate surface roughness levels. The data indicate that the dominant factors in roughness for a given layer thickness are a function of wall thickness, build location, and build direction.

Engineering↗

Printability and Overall Cooling Performance of Additively Manufactured Holes With Inlet and Exit Rounding

Abstract To improve cooling effectiveness of gas turbine hardware, various film cooling hole shapes have previously been researched. Unique design modifications have recently been made possible through the design freedom allotted by additive manufacturing (AM). As one example, creating a rounded inlet for a film-cooling hole can mitigate separation at the inlet. This study explores various geometric features by exploiting the uses of additive manufacturing for shaped film cooling holes at engine scale. Both printability and cooling performance were evaluated. Resulting from this study, additively manufactured holes with hole inlet and exit rounding were printed with some variations from the design intent (DI). The largest deviations from the design intent occurred from dross roughness features located on the leeward side of the hole inlet. The measured overall effectiveness indicated that an as-built inlet fillet decreased in-hole convection as well as decreased jet mixing compared to the as-built sharp inlet. Including an exit fillet, which prevented an overbuilt diffuser exit, was also found to decrease jet mixing. A particular insight gained from this study is the importance of the convective cooling within the hole to the overall cooling performance. In-hole roughness, which is a result of additive manufacturing, increased convective cooling within the holes but also increased jet mixing as the coolant exited the hole. The increased jet mixing caused low overall effectiveness downstream of injection.

Engineering↗

Experimental and Numerical Investigation of Flow Boiling in Additive Manufactured Foam Structures With Vapor Pathways

Abstract The unique properties of metal foams make them potential candidates for a range of applications, including microsystem thermal management. Using additive manufacturing to create foam-type structures can improve upon prior thermal solutions by eliminating thermal interface materials and allowing for customization/local control of parameters. In the present investigation, flow boiling in additive-manufactured metal foams is investigated both experimentally and numerically. Two test samples, one with uniform structure and the other with pathways for vapor removal, are compared both experimentally and numerically. A conjugate computational fluid dynamics and heat transfer (CFD-HT) model utilizing a three-dimensional volume of fluid (VOF) model with accompanying evaporation/condensation model provided in-depth visualization of the boiling flow phenomena. The experiments generated the thermohydraulic performance over a range of heat fluxes, demonstrating that the sample incorporating dedicated vapor pathways performed better in both pressure and heat transfer performance metrics compared to the uniform foam. Additionally, negative system-level effects (i.e., hydraulic oscillations) were shown to be abated using the vapor removal structures. The numerical model yielded further insight into the factors contributing to the improved performance. Results indicated the pathways functioned as vapor removal channels, allowing the generated vapor to vent from the foam structure into the lanes. Further computational investigations demonstrated changes in flow regimes, where the addition of vapor channels caused the flow to change from churn to annular. Bubble behavior unique to the vapor pathway structure was studied, showing stagnant regions that eject vapor into the channel.

Engineering↗

Construction-Scale Concrete Additive Manufacturing and its Application in Infrastructure Energy Storage

Construction is filled with labor intensive, hazardous, and often wasteful processes. It is also an enormous industry, so improvements in efficiency could have a tremendous economic impact. Construction-scale additive manufacturing is one path toward achieving those improvements. In this paper, a construction-scale additive manufacturing system, called Sky-BAAM, is presented. In addition to possibly leading to more energy-efficient construction practices, leveraging additive manufacturing in construction opens the solution space to more energy efficient building design. One such design, the EMPOWER wall, is also presented in this paper. The exterior of the wall is shaped to maximize heat transfer, while acting as form work for an internal energy-storage system. This allows energy to be stored in the wall during off-peak times and retrieved during peak periods.

Atkins, Celeste↗

STRESS AND DISTORTION SIMULATION OF ADDITIVE MANUFACTURING PROCESS BY HIGH PERFORMANCE COMPUTING

Numerical simulation is an efficient way to better understand the thermal and mechanical evolution during additive manufacturing (AM) and to design and optimize the process. However, with today’s computational tools, pass-by-pass thermal-mechanical numerical simulation of the AM process is extremely time-consuming. In this study, a new finite element code recently developed in house at Oak Ridge National Lab was used for additive manufacturing simulation. Our new code effectively utilizes GPU based high-performance computers to allow for realistic simulation of the transient thermal and mechanical response of materials during additive manufacturing. A benchmark study on a cylinder model by powder bed selective laser melting was carried out and distortion profile was compared to the experimental measurements. The accuracy and efficiency of the code was also demonstrated by analyzing a wire and arc additive manufacturing (WAAM) model which consists of a base plate and four deposited layers.

Huang, Hui↗

Effects of O 2 addition on in-plasma photo-assisted etching of Si with chlorine

Addition of oxygen was used to control the in-plasma photo-assisted etching (PAE) of p-type Si(100) and poly-Si in a high density, inductively coupled, Faraday-shielded, Ar/Cl 2 (225/25 SCCM), 60 mTorr plasma. After etching, samples were transferred under vacuum to an UHV x-ray photoelectron spectroscopy chamber for surface analysis. Samples etched under PAE conditions (ion energies below the ionassisted etching, IAE, threshold) had a thicker surface oxide and lower [Cl] surface concentration, when compared to samples etched under IAE conditions (ion energies above the IAE threshold). PAE was found not to be affected by 0.1 or 0.25 SCCM O 2 addition, while etching stopped with more than 0.5 SCCM O 2 addition. IAE with RF power on the sample stage, resulting in -65 V self-bias, was not affected by up to 2 SCCM of oxygen addition but decreased rapidly when more than 5 SCCM O 2 was added to the plasma. These results imply that PAE may be completely suppressed, while IAE occurs unobstructed. The implications of these findings are discussed in view of applications involving continuous wave and pulsed-plasma processes.

36 MATERIALS SCIENCE↗

SU-F-T-361: Dose Enhancement Due to Nanoparticle Addition in Skin Radiotherapy: A Monte Carlo Study Using Kilovoltage Photon Beams

Purpose: This study investigated the dose enhancement due to addition of nanoparticles with different types and concentrations in skin radiotherapy using kilovoltage photon beams. Methods: An inhomogeneous water phantom (15×15×10 cm{sup 3}) having the skin target layer (0.5–5 mm), added with different concentrations (3–40 mg/ml) of nanoparticles (Au, Pt, I, Ag and Fe{sub 2}O{sub 3}), was irradiated by the 105 and 220 kVp photon beams produced by a Gulmay D3225 Orthovoltage unit. The circular cone of 5-cm diameter and source-to-surface distance of 20 cm were used. Doses in the skin target layer with and without adding the nanoparticles were calculated using Monte Carlo simulation (the EGSnrc code) through the macroscopic approach. Dose enhancement ratio (DER), defined as the ratio of dose at the target with nanoparticle addition to the dose without addition, was calculated for each type and concentration of nanoparticle in different target thickness. Results: For Au nanoparticle, DER dependence on target thickness for the 220 kVp photon beams was not significant. However, DER for Au nanoparticle was found decreasing with an increase of target thickness when the nanoparticle concentration was increased from 18 to 40 mg/ml using the 105 kVp photon beams. For nanoparticle concentration of 40 mg/ml, DER variation with target thickness was not significant for the 220 kVp photon beams, but DEF was found decreasing with the target thickness when lower energy of photon beam (105 kVp) was used. DEF was found increasing with an increase of nanoparticle concentration. The higher the DEF increasing rate, the higher the atomic number of the nanoparticle except I and Ag for the same target thickness. Conclusion: It is concluded that nanoparticle addition can result in dose enhancement in kilovoltage skin radiotherapy. Moreover, the DER is related to the photon beam energy, target thickness, atomic number and concentration of nanoparticles.

60 APPLIED LIFE SCIENCES↗

Performance Improvement of Lithium Metal Batteries Enabled By LiBF 3 CN as a New Electrolyte Additive

A newly synthesized electrolyte additive, lithium trifluoro(cyano) borate (LiBF 3 CN), has been investigated for electrochemical performance improvement of lithium metal batteries. The LiBF 3 CN has a structure where one fluorine atom of BF 4 – is substituted with a cyano group (–CN) prepared by the reaction of boron trifluoride etherate with lithium cyanide. The electrochemical performance in symmetric Li/Li cells and NCM523/Li cells is significantly improved upon the incorporation of LiBF 3 CN as an electrolyte additive into a carbonate-based electrolyte. Extensive characterization of the deposited lithium metal reveals that a thin (≈20 nm) and robust SEI composed of LiN x O y , Li 3 N and Li 2 O is formed by the reductive decomposition of the LiBF 3 CN additive, which plays an important role in decreasing the resistance and stabilizing lithium deposition/stripping. The insight into the substitution effect of a functional group obtained from this work provides guidance for the design of new electrolyte additives.

25 ENERGY STORAGE↗

Impact of Electrolyte Additives on the Lifetime of High Voltage NMC Lithium-Ion Pouch Cells

This work involves improving the lifetime of lithium-ion cells during high voltage cycling using electrolyte additives. Three generations of electrolyte additives were investigated and screened in NMC442/graphite pouch cells using a 24 h voltage-hold protocol at 40 degrees C to accelerate oxidative reactions occurring at 4.4 V. Once promising additives and combinations were identified, they were then tested in cobalt-free NMC640/graphite cells for long-term cycling to upper cutoff voltages of 4.3, 4.4, and 4.5 V at temperatures of 20, 40, and 55 degrees C. Degradation mechanisms were probed using dV/dQ analysis, micro-X-ray fluorescence spectroscopy, and electrochemical impedance spectroscopy. The primary failure mode of cells held at high voltages is due to increase in cell impedance, which is correlated to the dissolution of transition metals, specifically manganese, originating from the positive electrode. We believe this dissolution is presumably due to the formation of a high impedance rock salt surface layer on the NMC positive electrode particles. Such deleterious outcomes can be limited by selecting an appropriate electrolyte additive package. It is hoped that this paper can provide a starting point for developing NMC Li-ion cells that can operate to voltages as high as 4.4 V and still display long lifetimes.

Azam, Saad↗

The Role of Additives in Improving Performance in High Voltage Lithium-Ion Batteries with Potentiostatic Holds

In this work, various electrolyte additives designed for enhanced performance at high voltages were evaluated with elevated temperature potentiostatic holds with LiNi0.5Co0.2Mn0.3/Li4Ti5O12 full cells to determine their effect on the high voltage stability. Of the additives investigated, many showed increased oxidation current through the 60 hour potentiostatic holds test, and adversely affected both the capacity retention and interfacial impedance. Improved high voltage performance was observed with two additives, vinylene carbonate (VC) and 1,1,2,2- tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (TTE), which was attributed to two different mechanisms of improvement. This work challenges some conclusions in the available literature that an additive molecule that decomposes on the charged cathode surface and passivates the surface against electrolyte oxidation.

Tornheim, Adam↗

Lipophilic Additives for Highly Concentrated Electrolytes in Lithium-Sulfur Batteries

The use of concentrated electrolytes in batteries has been impeded in part by the lack of compatible electrolyte additives for protection of electrodes. Herein, a lipophilic additive tetrabutylammonium iodide (TBAI = [Bu4N]I) was introduced to concentrated electrolyte (CH3CN)(2)LiTFSI/TTE (TTE = 1,1,2,2-tetrafluoroethyl 2,2,3,3-tetrafluoropropyl ether) for Li-S batteries. Electrochemical and SEM/EDS analyses showed that the additive provided short-term capacity retention via removal of S deposits by in situ generated I-2. These results strongly suggest lipophilic salts as viable candidates for additives in concentrated electrolytes. (c) 2019 The Electrochemical Society.

Lau, Ka-Cheong↗

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗

ODI notebook additive_manufacturing_video_2022

Additive Manufacturing, video dataset Two-photon lithography (TPL) is a widely used 3D nanoprinting technique that uses laser light to create objects. Challenges to large-scale adoption of this additive manufacturing method include identifying light dosage parameters and monitoring during fabrication. A research team from LLNL, Iowa State University, and Georgia Tech is applying machine learning models to tackle these challenges-i.e., accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. Funded by LLNL's Laboratory Directed Research and Development Program, the project team has curated a video dataset of TPL processes for parameters such as light dosages, photo-curable resins, and structures. Both raw and labeled versions of the datasets are available on the links in the Open Data Initiative page. The code uses the labeled dataset. Notebook compiled by Nisha Mulakken (mulakken1@llnl.gov) for LLNL Open Data Initiative, Summer 2022. Original code provided by research team. Publications: X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "Automated detection of part quality during two-photon lithography via deep learning." Additive Manufacturing 36, December 2020: doi.org/10.1016/j.addma.2020.101444 X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "wo Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures." Data in Brief 32, October 2020. doi.org/10.1016/j.dib.2020.106119.

Mulakken, NishaJ↗