Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Processing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Interinstitutional Study of the New EURO-GANEX Process Resistance by Gamma Irradiation Test Loops

As part of the homogeneous actinides recycling strategy, the EURO-GANEX process is one of the most promising options to achieve the goal of minor actinides recovery. However, EURO-GANEX also has various drawbacks that are being addressed. Improvements made to EURO-GANEX system have resulted in the emergence of the so-called New EURO-GANEX process, where the composition of the solvent has been modified by replacing TODGA and DMDOHEMA with cis-mTDDGA in the organic phase and SO3-Ph-BTP with PyTri-Diol in the aqueous phase in order to resolve important issues. The objective of this work is twofold: evaluate the gamma radiolysis resistance of the new EURO-GANEX process by dynamic irradiation conditions simulating the three main steps of the process and validate the design of CIEMAT Náyade, CEA Marcel and INL irradiation loop devices since each of them mimics different aspects of the real process. Náyade and the INL loops could irradiate together the organic and aqueous phases, whereas in the CEA loop, the irradiated solvent is recycled continuously inside a platform with several stages of mixer-settlers containing aqueous flows simulating the three main steps of the process. The extraction performances and changes in the composition of the solvent have been analysed during the irradiation experiment by different techniques: gamma spectrometry and ICP-MS/OES for cations or tracers extraction, and HPLC-MS to quantify the degradation and evaluate the degradation compounds. Additionally, in spite of some differences between the three-irradiation facilities, this inter-institutional study shows that they are three comparative tools, which provide results on the stability towards radiolysis of a liquid-liquid extraction system. Favourable extraction results for the different steps are obtained according to the static irradiation studies found in literature. However, the degradation of cis-mTDDGA is appreciable leading to degradation compounds, some of which form precipitates and produce important changes in viscosity, important aspects that must be addressed prior to the successful industrial application of the new EURO-GANEX process.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Direct Recycling of Lithium-Ion Battery Cathodes: A Multi-Stage Annealing Process to Recover the Pristine Structure and Performance

Direct recycling is an alternative low-cost process that retains the structure of the lithium-ion battery cathode rather than going through materials dissolution and repurification. While the process shows promise, various steps need to be better understood and studied to identify possible roadblocks, cost intensive steps, and needed variations in protocol that may be necessary based on the feedstock of recycled cathodes available. In this study, we have evaluated the process of thermal relithiation as it applies to end-of-life cathode materials. For recovered end-of-life cathodes, approximately 20% of the useable lithium has been lost due to solid electrolyte interface formation, parasitic reactions, and particle isolation; this lost lithium contributes to higher cell impedance and a gradual shift in electrode potentials. As a first step in the direct recycling process, this lithium needs to be restored not only to recover capacity but also to eliminate surface vacancies and hinder surface reconstruction that may increase impedance and impact performance. Here, we have optimized a coating method followed by a two-stage annealing process that restores a model delithiated NMC333 material to pristine performance. Comparisons to single-stage processes are made, and new characterization tools have been used to better understand the processes.

25 ENERGY STORAGE↗
DOE OSTI2019

Applying Environmental Release Inventories and Indicators to the Evaluation of Chemical Manufacturing Processes in Early Stage Development

As manufacturing processes are developed through the early stages of technology readiness, various assessments can be used to evaluate their performance. Performance indicators describe processes by transforming attributes into scores that represent desirable objectives. One type of assessment is obtained by determining the life cycle inventories of inputs and outputs for processes. For a functional unit of product, the user finds the resources used and the releases to the environment, which can be compared to results for similar processes and/or combined with other processes in the life cycle. In this work, an expanded range of process inputs and releases is modeled, including forklift/loader, fugitive, storage, boiler, and cooling tower emissions. A generic scenario approach for the cooling tower releases provides a first approximation of emission and wastewater flows. These inventory values are used in performance indicators that can be placed on a scale between fixed best- and worst-case limits with the GREENSCOPE methodology, thus allowing comparisons across various technologies. The processes of interest are two conversion pathways for producing cellulosic ethanol from biomass via thermochemical and biochemical routes. The results can be used in risk assessments, decision making, evaluation of research, and in spurring future technology development.

09 BIOMASS FUELS↗
DOE OSTI2024

Reduced‐Order Modeling for Linearized Representations of Microphysical Process Rates

Abstract Representing cloud microphysical processes in large scale atmospheric models is challenging because many processes depend on the details of the droplet size distribution (DSD, the spectrum of droplets with different sizes in a cloud). While full or partial statistical moments of droplet size distributions are the typical variables used in bulk models, prognostic moments are limited in their ability to represent microphysical processes across the range of conditions experienced in the atmosphere. Microphysical parameterizations employing prognostic moments are known to suffer from structural uncertainty in their representations of inherently higher dimensional cloud processes, which limit model fidelity and lead to forecasting errors. Here we investigate how data‐driven reduced‐order modeling can be used to learn predictors for microphysical process rates in bulk microphysics schemes in an unsupervised manner from higher dimensional bin distributions. Using simulations characteristic of marine stratiform clouds, we simultaneously learn lower dimensional representations of droplet size distributions and predict the evolution of the microphysical state of the system. Droplet collision‐coalescence, the main process for generating warm rain, is estimated to have an intrinsic dimension of three. This intrinsic dimension provides a lower limit on the number of degrees of freedom needed to accurately represent collision‐coalescence in models. We demonstrate how deep learning based reduced‐order modeling can be used to discover intrinsic coordinates describing the microphysical state of the system, where process rates such as collision‐coalescence are globally linearized. These implicitly learned representations of the DSD retain more information about the DSD than typical moment‐based representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn↗
DOE OSTI2015

Biochemical process of low level radioactive liquid simulation waste containing detergent

Research of biochemical process of low level radioactive liquid waste containing detergent has been done. Thse organic liquid wastes are generated in nuclear facilities such as from laundry. The wastes that are cotegorized as hazard and poison materials are also radioactive. It must be treated properly by detoxification of the hazard and decontamination of the radionuclides to ensure that the disposal of the waste meets the requirement of standard quality of water. This research was intended to determine decontamination factor and separation efficiensies, its kinetics law, and to produce a supernatant that ensured the environmental quality standard. The radioactive element in the waste was thorium with activity of 5.10{sup −5} Ci/m{sup 3}. The radioactive liquid waste which were generated in simulation plant contains detergents that was further processed by aerobic biochemical process using SGB 103 bacteria in a batch reactor equipped with aerators. Two different concentration of samples were processed and analyzed for 212 hours and 183 hours respectively at a room temperature. The product of this process is a liquid phase called as supernatant and solid phase material called sludge. The chemical oxygen demand (COD), biological oxygen demand (BOD), suspended solid (SS), and its alpha activity were analyzed. The results show that the decontamination factor and the separation efficiency of the lower concentration samples are higher compared to the samples with high concentration. Regarding the decontamination factor, the result for 212 hours processing of waste with detergent concentration of 1.496 g/L was 3.496 times, whereas at the detergent concentration of 0.748 g/L was 15.305 times for 183 hours processing. In case of the separation efficiency, the results for both samples were 71.396% and 93.465% respectively. The Bacterial growth kinetics equation follow Monod’s model and the decreasing of COD and BOD were first order with the rate constant of 0.01 hour{sup −1}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effect of fabrication processes on BaTiO 3 capacitor properties

There is an increasing desire to utilize complex functional electronic materials such as ferroelectrics in next-generation microelectronics. As new materials are considered or introduced in this capacity, an understanding of how we can process these materials into those devices must be developed. Here, the effect of different fabrication processes on the ferroelectric and related properties of prototypical metal oxide (SrRuO 3 )/ferroelectric (BaTiO 3 )/metal oxide (SrRuO 3 ) heterostructures is explored. Two different types of etching processes are studied, namely, wet etching of the top SrRuO 3 using a NaIO 4 solution and dry etching using an Ar + -ion beam (i.e., ion milling). Polarization-electric-field hysteresis loops for capacitors produced using both methods are compared. For the ion-milling process, it is found that the Ar + beam can introduce defects into the SrRuO 3 /BaTiO 3 /SrRuO 3 devices and that the milling depth strongly influences the defect level and can induce a voltage imprint on the function. Realizing that such processing approaches may be necessary, work is performed to ameliorate the imprint of the hysteresis loops via ex situ “healing” of the process-induced defects by annealing the ferroelectric material in a barium-and-oxygen-rich environment via a chemical-vapor-deposition-style process. This work provides a pathway for the nanoscale fabrication of these candidate materials for next-generation memory and logic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Investigating Powder Spreading Dynamics in Additive Manufacturing Processes by In-situ High-speed X-ray Imaging

The quality of the powder bed is known to be one of the main factors that influence the quality of the part being manufactured by powderbed- based additive manufacturing processes. For example, in the laser powder bed fusion process, it has been demonstrated that improving the powder bed density and homogeneity improves the final quality of the part. Understanding powder spreading dynamics in the powder-bed-based additive manufacturing processes is critical for designing spreading structures and spreading parameters, identifying defect formation mechanisms in the powder bed, and guiding the design of optimized feedstock powders. Extensive efforts have been devoted to understand the fundamental mechanism of the powder flow and spreading process. Various powder flow testers were used to study the flow behavior of powders used in additive manufacturing. However, the powder flow conditions in flow meters are different from those in real additive manufacturing conditions. Models have also been developed to simulate and study the spreading process. The discrete element method (DEM) is currently the main tool for computationally simulating the spreading process. However, these models are based on many physical assumptions. Visible light cameras have been used recently to conduct in-situ study of powder spreading in additive manufacturing. Due to the limited resolution and penetration depth of visible light, it is extremely difficulty to study the particle-scale powder spreading dynamics. Here, to overcome the challenges of studying powder spreading dynamics under real additive manufacturing conditions, we developed an experimental approach to study the particle-scale powder spreading process with high spatial and temporal resolution using the high-speed high-energy X-ray imaging facility at beamline 32-ID-B of the APS. Figure 1 shows an overview of the research setup. It is composed of a vacuum chamber (building environment), an automatic powder spreading system, a laser system, an X-ray source (X-ray outlet), and an X-ray detection/imaging system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Development of New Magnetron Sputter Deposition Processes for Laser Target Fabrication

Magnetron sputter deposition is an enabling technology for laser target fabrication. Solutions are readily available for the deposition of most sub-micron-thick elemental films on planar substrates. However, major challenges still remain for the development of robust deposition processes in regimes of ultrathick (over ~10 μm) coatings and nonplanar substrates. These challenging deposition regimes are directly relevant to laser target applications, including both sphero-cylindrical hohlraums and spherical ablators for inertial confinement fusion (ICF) targets. Understanding underlying physical mechanisms for a specific material system is crucial for process development, given the overall complexity of the deposition process, its nonlinear dependence on deposition parameters, and a very large process space, often precluding conventional process optimization approaches. Here, we describe our approach to developing new deposition processes and give practical advice with examples of new results from our ongoing studies of glassy boron carbide ceramics for next-generation ICF ablators and nonequilibrium gold-tantalum alloys for hohlraums for magnetized ICF schemes. Emphasis is given to two major challenges of ultrathick coatings related to achieving process stability and reducing residual stress.

36 MATERIALS SCIENCE↗
DOE OSTI2013

REPRODUCING THE OBSERVED ABUNDANCES IN RCB AND HdC STARS WITH POST-DOUBLE-DEGENERATE MERGER MODELS-CONSTRAINTS ON MERGER AND POST-MERGER SIMULATIONS AND PHYSICS PROCESSES

The R Coronae Borealis (RCB) stars are hydrogen-deficient, variable stars that are most likely the result of He-CO WD mergers. They display extremely low oxygen isotopic ratios, {sup 16}O/{sup 18}O {approx_equal} 1-10, {sup 12}C/{sup 13}C {>=} 100, and enhancements up to 2.6 dex in F and in s-process elements from Zn to La, compared to solar. These abundances provide stringent constraints on the physical processes during and after the double-degenerate merger. As shown previously, O-isotopic ratios observed in RCB stars cannot result from the dynamic double-degenerate merger phase, and we now investigate the role of the long-term one-dimensional spherical post-merger evolution and nucleosynthesis based on realistic hydrodynamic merger progenitor models. We adopt a model for extra envelope mixing to represent processes driven by rotation originating in the dynamical merger. Comprehensive nucleosynthesis post-processing simulations for these stellar evolution models reproduce, for the first time, the full range of the observed abundances for almost all the elements measured in RCB stars: {sup 16}O/{sup 18}O ratios between 9 and 15, C-isotopic ratios above 100, and {approx}1.4-2.35 dex F enhancements, along with enrichments in s-process elements. The nucleosynthesis processes in our models constrain the length and temperature in the dynamic merger shell-of-fire feature as well as the envelope mixing in the post-merger phase. s-process elements originate either in the shell-of-fire merger feature or during the post-merger evolution, but the contribution from the asymptotic giant branch progenitors is negligible. The post-merger envelope mixing must eventually cease {approx}10{sup 6} yr after the dynamic merger phase before the star enters the RCB phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Guided ink and process design for aerosol jet printing based on annular drying effects

Aerosol jet printing is a promising microscale additive manufacturing technology for emerging applications in printed and flexible electronics. However, the more widespread adoption of this emerging technique is hindered by a limited fundamental understanding of the process. This work focuses on a critical and underappreciated aspect of the process, the interaction between drying induced by the sheath gas and impaction. Combining focused experiments with support from numerical modeling, it is shown that these effects have a dramatic impact on key outputs of the process, including deposition rate, resolution, and morphology. These effects can amplify minor changes in ink composition or atomization yield, increasing process sensitivity and drift. Moreover, these effects can confound strategies for in-line process monitoring and control based on empirical observables. Strategies to directly manipulate this annular drying phenomenon are presented, providing a viable tool to tailor and study the process. This work clarifies coupled effects of printer design, ink formulation, and print parameters, establishing a more robust theoretical framework for understanding the aerosol jet printing process and advancing the maturity of this promising technology.

42 ENGINEERING↗
DOE OSTI2016

Production of the entire range of r -process nuclides by black hole accretion disc outflows from neutron star mergers

We consider r -process nucleosynthesis in outflows from black hole accretion discs formed in double neutron star and neutron star–black hole mergers. These outflows, powered by angular momentum transport processes and nuclear recombination, represent an important – and in some cases dominant – contribution to the total mass ejected by the merger. Here we calculate the nucleosynthesis yields from disc outflows using thermodynamic trajectories from hydrodynamic simulations, coupled to a nuclear reaction network. We find that outflows produce a robust abundance pattern around the second r -process peak (mass number A ~ 130), independent of model parameters, with significant production of A < 130 nuclei. This implies that dynamical ejecta with high electron fraction may not be required to explain the observed abundances of r -process elements in metal poor stars. Disc outflows reach the third peak (A ~ 195) in most of our simulations, although the amounts produced depend sensitively on the disc viscosity, initial mass or entropy of the torus, and nuclear physics inputs. Some of our models produce an abundance spike at A = 132 that is absent in the Solar system r -process distribution. The spike arises from convection in the disc and depends on the treatment of nuclear heating in the simulations. We conclude that disc outflows provide an important – and perhaps dominant – contribution to the r -process yields of compact binary mergers, and hence must be included when assessing the contribution of these systems to the inventory of r -process elements in the Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bulk viscosity from Urca processes: n p e μ matter in the neutrino-transparent regime

We study the bulk viscosity of moderately hot and dense, neutrino-transparent relativistic npeμ matter arising from weak-interaction direct Urca processes. This work parallels our recent study of the bulk viscosity of npeμ matter with a trapped neutrino component. The nuclear matter is modeled in a relativistic density functional approach with two different parametrizations—DDME2 (which does not allow for the low-temperature direct-Urca process at any density) and NL3 (which allows for low-temperature direct-Urca process above a low-density threshold). Here, we compute the equilibration rates of Urca processes of neutron decay and lepton capture, as well as the rate of the muon decay, and find that the muon decay process is subdominant to the Urca processes at temperatures T ≥ 3 MeV in the case of DDME2 model and T ≥ 1 MeV in the case of NL3 model. Thus, the Urca-process-driven bulk viscosity is computed with the assumption that pure leptonic reactions are frozen. As a result the electronic and muonic Urca channels contribute to the bulk viscosity independently and at certain densities the bulk viscosity of npeμ matter shows a double-peak structure as a function of temperature instead of the standard one-peak (resonant) form. In the final step, we estimate the damping timescales of density oscillations by the bulk viscosity. We find that, e.g., at a typical oscillation frequency f = 1~kHz, the damping of oscillation is most efficient at temperatures 3 ≤ T ≤ 5~MeV and densities n B ≤ 2n 0 where they can affect the evolution of the post-merger object.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows

In-situ and in-transit processing alleviate the gap between the computing and I/O capabilities by scheduling data analytics close to the data source. Hybrid in-situ processing splits data analytics into two stages: the data processing that runs in-situ aims to extract regions of interest, which are then transferred to staging services for further in-transit analytics. To facilitate this type of hybrid in-situ processing, the data staging service needs to support complex intermediate data representations generated/consumed by the in-situ tasks. Unstructured (or irregular) mesh is one such derived data representation that is typically used and bridges simulation data and analytics. However, how staging services efficiently support unstructured mesh transfer and processing remains to be explored. This paper investigates design options for transferring and processing unstructured mesh data using staging services. Using polygonal mesh data as an example, we show that hybrid in-situ workflows with staging-based unstructured mesh processing can effectively support hybrid in-situ workflows, and can significantly decrease data movement overheads.

data-driven↗
DOE OSTI2020

A Digital Twin Approach to Study Additive Manufacturing Processing Using Embedded Optical Fiber Sensors and Numerical Modeling

One of the major challenges for metal-powder-based additive manufacturing is measuring and mitigating residual strain induced during the manufacturing processes. This article reports distributed fiber optic sensors embedded in Inconel alloy components as experimental means to validate numerical models of additive manufacturing process. Electroplating was used to deposit a metal protective jacket onto standard telecom single-mode fibers for strain measurements, Fiber sensors were embedded in an Inconel alloy substrate using the laser engineered net shaping (LENS) process. Here by using a Rayleigh-scattering optical frequency domain reflectometer (OFDR), temperature changes, and residual strain in the metal substrate were monitored with 5 mm spatial resolution during the LENS process. Using finite element analysis, temperature and strain profiles induced by the LENS deposition processes were also numerically studied. Discrepancies between the simulated temperature and strain profiles and those measured directly were less than 10%. Results presented in this article demonstrates a digital twin approach to fuse modeling results with distributed fiber sensor measurement data to study additive manufacturing process toward design and fabrication process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Influence of Tabula Rasa on Process- and Light-Induced Degradation of Solar Cells Fabricated From Czochralski Silicon

Monocrystalline Si solar cells are fabricated from Czochralski (Cz) Si, which contains 10 17 –10 18 cm -3 oxygen atoms. Cz Si undergoes degradation during high-temperature thermal processing steps, such as dopant diffusion to form the p - n junction. This degradation in the bulk minority carrier lifetime can be related to the formation of oxygen precipitates. We found that a high-temperature annealing process known as tabula rasa (TR) not only mitigates process-induced degradation via oxygen precipitate nuclei dissolution, but also modifies subsequent light-induced degradation. We report on the bulk carrier lifetime of n - and p -type Cz Si after TR, which homogenizes the interstitial oxygen in the bulk Si to its monoatomic form in either an N 2 or O 2 environment. A control sample, which was not subjected to a TR processing step, experienced severe process-induced degradation during a boron emitter thermal budget as oxygen precipitates were formed in the Si bulk. These precipitates could be imaged using photoluminescence. Additionally, samples that underwent a TR processing step prior to the boron emitter thermal budget show efficient gettering of metallic impurities compared to the control sample, which showed a decline in the implied open-circuit voltage after the gettering step. Furthermore, modification of the interstitial oxygen bonding by TR had a strong effect on the light-induced degradation kinetics. Instead of a typically observed monotonic decrease, minority carrier lifetime increases first, followed by a nonmonotonic decrease over a ~20 h period. Finally, we conclude that by modifying the interstitial oxygen bonding via TR pretreatment, p -type Cz Si wafers become substantially resistant to harsh solar cell processes and strongly modified light-induced degradation, which would open alternative ways to mitigate this degradation mechanism.

14 SOLAR ENERGY↗
DOE OSTI2021

Balanced stochastic versus deterministic assembly processes benefit diverse yet uneven ecosystem functions in representative agroecosystems

Ecological assembly processes, by influencing community composition, determine ecosystem functions of microbiomes. However, debate remains on how stochastic versus deterministic assembly processes influence ecosystem functions such as carbon and nutrient cycling. Towards a better understanding, we investigated three types of agroecosystems (the upland, paddy, and flooded) that represent a gradient of stochastic versus deterministic assembly processes. Carbon and nutrient cycling multifunctionality, characterized by nine enzymes associated with soil carbon, nitrogen, phosphorous and sulfur cycling, was evaluated and then associated with microbial assembly processes and cooccurrence patterns of vital ecological groups. Our results suggest that strong deterministic processes favour microorganisms with convergent functions (as in the upland agroecosystem), while stochasticity-dominated processes lead to divergent functions (as in the flooded agroecosystem). To benefit agroecosystems services, we speculate that it is critical for a system to maintain balance between its stochastic and deterministic assembly processes (as in the paddy agroecosystem). By doing so, the system can preserve a diverse array of functional traits and also allow for particular traits to flourish. To further confirm this speculation, it is necessary to develop a systematic knowledge beyond merely characterizing general patterns towards the associations among community assembly, composition, and ecosystem functions.

Liu, Wenjing↗
DOE OSTI2021

Processing and 3D printing of SiCN polymer-derived ceramics

Preceramic polymer resins are attractive for the 3D printing of net-shaped ceramic components. Recently various processes have been demonstrated for 3D printing of polymer-derived ceramics (PDCs). Ultimately in these processes, the process outcomes strongly depend on the process parameters. In particular, for PDCs the ceramic density, and ceramic yield are affected by the catalyst concentration and cross-linking duration. Here, we use thermal analysis and FTIR to quantify the interrelation of the process parameters on the process outcome for polysilazanes and demonstrate 3D printing of PDC components based on the best-identified process parameters. Furthermore, the results of this work can be used as guidelines for future additive manufacturing of PDCs.

36 MATERIALS SCIENCE↗