Dissolution and phase transformation processes of hausmannite in acidic aqueous systems under anoxic conditions
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Geochemistry & Geophysics↗
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Towards the scale-up production of cellulose nanocomposites using melt processing: A critical review on structure-processing-property relationships
Cellulose nanomaterials (CNMs) naturally exist in plant biomass. The success of extraction of CNMs opened up a new era of using plant biomass for innovative industrial applications. Because CNMs are abundant, renewable, biodegradable, transparent, light weight and low in cost, they are ideal materials for large volume applications such as packaging, automotive, building and infrastructure. In many potential application areas, CNM-enable products appear in a composite form, mostly polymer composites. Additionally, the industrial-scale manufacturing of CNM/thermoplastic composites remains as a set of unsolved problems for academia and industry. A prime challenge in applications is the nanoscale dispersion of CNMs in thermoplastic matrices during melt processing. Both bench-scale and pilot-scale studies have been conducted to solve the dispersion issue of CNMs. In this article, research related to the dispersion of CNMs in thermoplastic matrices during melt processing were critically reviewed. All research papers were classified into three groups: chemically-aided dispersion, physically-aided dispersion and mechanically-aided dispersion. Numerous factors affect the CNM dispersion and the mechanical performance of its nanocomposites. There are material-related factors, including CNM types and forms, polymer matrices, surface modification, coupling agents, etc. Furthermore, extrusion processing parameters also play a significant role, covering screw rotation speed, extrusion barrel temperature settings and screw design. In addition, the material-related factors interact with the processing-related factors. Understanding all factors and their interactions are important for moving CNM nanocomposites research a step further towards industrial-relevant production, which is the final ambitious goal of this manuscript.
42 ENGINEERING↗
Simulations of ecosystem hydrological processes using a unified multi-scale model
This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling of hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater interactions.
Environmental Molecular Sciences Laboratory↗
Fatigue of laser powder bed fusion processed 17-4 stainless steel using prior process exposed powder feedstock
The rapid pace of development seen in the metal additive manufacturing (AM) process of laser powder-bed fusion (LPBF) requires in-step advances in processes qualification to enable full-scale adoption. This particularly applies to quantifying how powder feedstock conditions impact end-component quality. Here this study examines how in-machine 17-4 stainless steel powder feedstocks are affected by prior LPBF processes, and how these effects impact subsequent builds. Examinations of powder morphology, chemistry, flowability, and rheology were conducted to characterize the powder conditions. The resultant effects of powder feedstock condition on produced component quasi-static tensile and high-cycle fatigue properties were analyzed. Fatigue life was analyzed using a reliability modeling approach that enabled a robust statistical comparison of life. Powder characteristics were found to evolve with powder exposure to prior LPBF processes, particularly in the extremes of powder size distribution and measures of bulk flow. No significant effects of these changes on tensile properties were observed. Reliability modeling methods, including the lognormal and Weibull distributions as well as the empirical survival function, are shown to be effective tools for modeling fatigue variability in LPBF manufactured components. Through these tools, fatigue life was found to be invariant with changes in powder condition.
42 ENGINEERING↗
Effects of in-process cryocooling on metallurgical and mechanical properties of friction stir processed Al7075 alloy
Highlights: • For in-process cryocooling (IPC) during FSP, an efficient cooling fixture was designed & fabricated. • FSP of Al7075 alloy with IPC setup suppressed precipitate coarsening as well as grain growth. • Nanosize η′ precipitates (20–30 nm) in IPC condition increased work hardening capacity & strength. • Simultaneous improvement in ductility & strength occurred for sample FSPed with IPC. - Abstract: Friction stir processing (FSP) of heat treatable aluminum alloys is reported to deteriorate strength and hardness properties in spite of huge grain size refinement. The improvement in strength due to the grain size refinement after FSP could not be able to offset the reduction in strength due to coarsening or dissolution of the strengthening precipitate(s). To overcome this, the present work investigates an effective way of heat rejection from the FSP zone to control the precipitate evolution besides the grain size refinement during FSP of Al7075 alloy. The FSP was carried out with standardized process parameters (i.e. 720 rpm, 65 mm/min traverse speed) under two different cooling environments: (i) at normal air cooling and (ii) by rushing a chilled mixture (−30 °C) of liquid nitrogen and methanol through the bottom of the backing plate. Microstructural evolution was examined through optical, scanning and transmission electron microscopy and electron backscatter diffraction to confirm the grain size and morphology of precipitate(s) formed. The in-process cryocooling during the FSP led to 65 and 72% improvement in the Vickers hardness and tensile strength, respectively, in comparison to the solutionized base metal. The results have been analyzed in terms of precipitate interface characteristics and its strengthening effect, Hall–Petch strengthening due to grain size reduction and tradeoff between them.
36 MATERIALS SCIENCE↗
Simulated aging processes of black carbon and its impact during a severe winter haze event in the Beijing-Tianjin- Hebei region
Black carbon (BC) can mitigate or worsen air pollution through perturbing meteorological conditions. BC aging processes are important for the evolution of particle size, concentration, and optical properties of BC that determines its influence on the meteorology. Here we use the online coupled Weather Research and Forecasting-Chemistry (WRF-Chem) model to quantify the role of BC aging processes, including physical processes (PP) and absorption enhancements (AE), in exerting BC-induced meteorological changes and the associated feedback to PM2.5 (particulate matter less than 2.5 µm in diameter) and O3 concentrations during a severe haze event in Beijing-Tianjin-Hebei (BTH) region during 21-27 February 2014. Our results show that, compared to the simulation without the PP treatment, the simulated near-surface BC concentration and BC mass loading in BTH region is lowered by 6.6 % and 12.1 %, respectively, during the haze event with the PP included. PP increases the proportion of large-size BC (particle diameter greater than 0.312 µm) from 28 %-33 % to 59 %-64 % below 1000 m in BTH region. Both PP and AE enhance the “dome effect” of BC. With both PP and AE considered, a reduction in PBL height due to BC-PBL interaction is 116.3 m (20.7 %), compared to 75.7 m (13.5 %) without AE and 66.6 m (11.9 %) without both PP and AE. However, during this haze event, anomalous northeasterly winds are produced by the direct radiative effect of BC, which further affects the mixing and transport of aerosols. When PBL height is decreased (from 10:00 to 21:00), combining all the impacts on multiple meteorological factors, BC effect without PP and AE, without AE, and with PP and AE, respectively, increases surface concentrations of PM2.5 by 8.3 µg m-3 (6.1 % relative to the mean value), 6.1 µg m-3 (4.5 %) and 9.6 µg m-3 (7.0 %) but decreases surface O3 concentrations by 2.8 ppbv (7.4 %), 4.0 ppbv (9.0 %) and 5.0 ppbv (10.8 %) in BTH region averaged over 21-27 February 2014. Our results highlight the importance of the aging processes and absorption enhancements of BC in simulating weather and air quality.
Chen, Donglin↗
The Cell Utilized Partitioning Model as a Predictive Tool for Optimizing Counter-Current Chromatography Processes
Counter-current chromatography (CCC) is capable of unique elution modes that isolate analytes using the movement of the stationary phase in addition to moving the mobile phase. These modes include elution-extrusion CCC (EECCC) and dual-mode CCC (DM CCC) that are not possible in traditional solid-liquid chromatography systems. Although EECCC and DM CCC are widely used to recover highly retained components, to our knowledge, optimizing the elution process in these modes with predictive models has not been reported. To address this gap, we developed a predictive model for CCC dubbed the Cell Utilized Partitioning (CUP) model. The CUP model accurately predicts the effluents of multicomponent separations in EECCC and DM CCC modes when compared to experimental data. Furthermore, CUP model simulations were extended to investigate the influence of operating and intrinsic parameters on the yield and productivity, and to compare the separation performances of EECCC and DM CCC in various conditions. The results demonstrate that low distribution constants, usually a KD less than 1, and a selectivity > 1.3, under specific flowrate ranges, increase both productivity and yield. From these results, generalized optimization and scaleup guidelines are proposed that can apply to research settings and to industrial processes to maximize preparative CCC performance.
BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
Dynamic Process Intensification of Binary Distillation via Periodic Operation
This paper applies the concept of dynamic intensification (defined as changes to the dynamics, operation strategy, and/or control of a process that lead to a substantially more efficient processing path) to binary distillation columns. The resulting strategy consists of manufacturing a target product as a blend of two auxiliary products, both having lower energy demands than a reference value, which corresponds to producing the target product(s) in a column operating at steady state. Here, a discussion of the appropriate control structures and switching strategies between the two auxiliary products is provided. An extensive case study concerning the separation of a methanol–1-propanol mixture was carried out, demonstrating that energy savings in the order of 1.4% are possible with no disruption in product quality or production rate.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Silver Nanocube and Nanobar Growth via Anisotropic Monomer Addition and Particle Attachment Processes
Understanding the growth mechanism of noble metal nanocrystals during solution synthesis is of significant importance for shape and property control. However, much remains unknown about the growth pathways of metal nanoparticles due to lack of direct observation. Using an in-situ transmission electron microscopy technique, we directly observed Ag nanocube and nanobar growth in aqueous solution through both classical monomer-by-monomer addition and non-classical particle attachment processes. During the particle attachment process, Ag nanocubes and nanobars formed via both oriented and non-oriented attachment. Our calculations, along with dynamics of the observed attachment, showed that van der Waals force overcame hydrodynamic and friction forces and drove the particles toward each other. During classical growth, an anisotropic growth was also revealed, and the resulting unsymmetrical shape constituted an intermediate state for Ag nanocube growth. We hypothesized that the temporary symmetry breaking resulted from different growth rates on {001} surfaces due to a local surface concentration variation caused by the imbalance between the consumption of Ag+ near the surface and the diffusion of Ag+ from bulk to surface.
Xiao, Dongdong↗
A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes
Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.
Chemical engineering↗
Real-time monitoring of calcification process by Sporosarcina pasteurii biofilm
Sporosarcina pasteurii is known to produce calcite or biocement in the presence of urea and Ca 2+ . Herein, we report the use of novel ultramicrosensors such as pH, Ca 2+ , and redox sensors, along with a scanning electrochemical microscope (SECM), to monitor a real-time, bacteria-mediated urea hydrolysis process and subsequent changes in morphology due to CaCO 3 precipitation. We report that the surface pH of a live biofilm changed rapidly from 7.4 to 9.2 within 2 min, whereas similar fast depletion (10 min) of Ca 2+ was observed from 85 mM to 10 mM in the presence of a high urea (10 g L -1 ) brine solution at 23 °C. Both the pH and the Ca 2+ concentration profiles were extended up to 600 μm from the biofilm surface, whereas the bulk chemical composition of the brine solution remained constant over the entire 4 h of SECM experiments. In addition, we observed a change in biofilm surface morphology and an increase in overall biofilm height of 50 μm after 4 h of precipitation. Electron microscopy confirmed the changes in surface morphology and formation of CaCO 3 crystals. Development of the Ca 2+ profile took 10 min, whereas that of the pH profile took 2 min. This finding indicates that the initial urea hydrolysis process is fast and limited by urease or number of bacteria, whereas later CaCO 3 formation and growth of crystals is a slow chemical process. The ultramicrosensors and approaches employed here are capable of accurately characterizing bioremediation on temporal and spatial scales pertinent to the microbial communities and the processes they mediate.
59 BASIC BIOLOGICAL SCIENCES↗
Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time
The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.
79 ASTRONOMY AND ASTROPHYSICS↗
Impact of process temperature on GaSb metal-oxide-semiconductor interface properties fabricated by ex-situ process
We have studied the impact of process temperature on interface properties of GaSb metal-oxide-semiconductor (MOS) structures fabricated by an ex-situ atomic-layer-deposition (ALD) process. We have found that the ALD temperature strongly affects the Al{sub 2}O{sub 3}/GaSb MOS interface properties. The Al{sub 2}O{sub 3}/GaSb MOS interfaces fabricated at the low ALD temperature of 150 °C have the minimum interface-trap density (D{sub it}) of ∼4.5 × 10{sup 13 }cm{sup −2} eV{sup −1}. We have also found that the post-metalization annealing at temperature higher than 200 °C degrades the Al{sub 2}O{sub 3}/GaSb MOS interface properties. The low-temperature process is preferable in fabricating GaSb MOS interfaces in the ex-situ ALD process to avoid the high-temperature-induced degradations.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Graphics processing unit accelerated three-dimensional model for the simulation of pulsed low-temperature plasmas
A 3-dimensional particle-in-cell/Monte Carlo collision simulation that is fully implemented on a graphics processing unit (GPU) is described and used to determine low-temperature plasma characteristics at high reduced electric field, E/n, in nitrogen gas. Details of implementation on the GPU using the NVIDIA Compute Unified Device Architecture framework are discussed with respect to efficient code execution. The software is capable of tracking around 10 × 10{sup 6} particles with dynamic weighting and a total mesh size larger than 10{sup 8} cells. Verification of the simulation is performed by comparing the electron energy distribution function and plasma transport parameters to known Boltzmann Equation (BE) solvers. Under the assumption of a uniform electric field and neglecting the build-up of positive ion space charge, the simulation agrees well with the BE solvers. The model is utilized to calculate plasma characteristics of a pulsed, parallel plate discharge. A photoionization model provides the simulation with additional electrons after the initial seeded electron density has drifted towards the anode. Comparison of the performance benefits between the GPU-implementation versus a CPU-implementation is considered, and a speed-up factor of 13 for a 3D relaxation Poisson solver is obtained. Furthermore, a factor 60 speed-up is realized for parallelization of the electron processes.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Novel pre-alloyed powder processing of modified alnico 8: Correlation of microstructure and magnetic properties
Progress is reviewed on development of an improved near-final bulk magnet fabrication process for alnico 8, as a non-rare earth permanent magnet with promise for sufficient energy density and coercivity for electric drive motors. This study showed that alnico bulk magnets in near-final shape can be made by simple compression molding from spherical high purity gas atomized pre-alloyed powder. Dwell time at peak sintering temperature (1250 °C) greatly affected grain size of the resulting magnet alloys. This microstructure transformation was demonstrated to be useful for gaining partially aligned magnetic properties and boosting energy product. While a route to increased coercivity was not identified by these experiments, manufacturability of bulk alnico magnet alloys in near-final shapes was demonstrated, permitting further processing and alloy modification experiments that can target higher coercivity and better control of grain anisotropy during grain growth.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Alternate current magnetic property characterization of nonstoichiometric zinc ferrite nanocrystals for inductor fabrication via a solution based process
We investigate the ac magnetic behavior of solution processable, non-stoichiometric zinc ferrite nanocrystals with a series of sizes and zinc concentrations. Nearly monodisperse Zn{sub x}Fe{sub 3−x}O{sub 4} nanocrystals (x = 0–0.25) with an average size ranging from 7.4 nm to 13.8 nm are synthesized by using a solvothermal method. All the nanocrystals are in a superparamagnetic state at 300 K, which is confirmed by Superconductive Quantum Interference Device magnetometry. Due to the doping of non-magnetic Zn{sup 2+} into A site of ferrite, the saturation magnetization of nanocrystals increases as the size and Zn concentration increases. The ac magnetic permeability measurements at radio frequencies reveal that the real part of the magnetic permeability of similarly sized ferrite nanocrystals can be enhanced by almost twofold as the Zn{sup 2+} doping level increases from 0 to 0.25. The integration of 12.3 nm Zn{sub 0.25}Fe{sub 2.75}O{sub 4} nanocrystals into a toroidal inductor and a solenoid inductor prepared via a simple solution cast process yields a higher quality factors than air core inductors with the same geometries up to 5 MHz and 9 MHz, respectively, which is in the regime of the switching frequencies for the advanced integrated power converters.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Effect of process parameters on hardness, temperature profile and solidification of different layers processed by direct metal laser sintering (DMLS)
In DMLS process objects are fabricated layer by layer from powdered material by melting induced by a controlled laser beam. Metallic powder melts and solidifies to form a single layer. Solidification map during layer formation is an important route to characterize micro-structure and grain morphology of sintered layer. Generally, solidification leads to columnar, equiaxed or mixture of these two types grain morphology depending on solidification rate and thermal gradient. Eutectic or dendritic structure can be formed in fully equiaxed zone. This dendritic growth has a large effect on material properties. Smaller dendrites generally increase ductility of the layer. Thus, materials can be designed by creating desired grain morphology in certain regions using DMLS process. To accomplish this, hardness, temperature distribution, thermal gradient and solidification cooling rate in processed layers will be studied under change of process variables by using finite element analysis, with specific application to Ti-6Al-4V.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
The Dark Energy Survey Image Processing Pipeline
The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ~5000 deg 2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ~24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ~27 deg 2 . DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. In this paper, we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.
79 ASTRONOMY AND ASTROPHYSICS↗