Results for “grinding”

DOE OSTI2021

Fine grinding of thermoplastics by high speed friction grinding assisted by guar gum

High speed friction grinding has been used to grind plant and food substances in water but never been explored for grinding of thermoplastics like polylactic acid (PLA), low and high density polyethylene and polypropylene. Such grinding was investigated in this work and was made possible by using 0.5% guar gum solution instead of just water because increasing the viscosity of water reduced their settling and the speed of passing through the grinder. Additionally, tensile, flexural, and impact strengths of the plastics were studied and higher grinding efficiency of PLA could be explained by its low elongation-at-break compared to low density polyethylene, high density polyethylene, and polypropylene. The microplastics (2000–45 μm) were studied for mass and particle size distributions and by scanning electron microscopy, 13 C CP/MAS NMR, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. In addition, viscosity of guar gum and contact angles was measured. This new technology can produce finely ground microplastics (710–45 μm) for a variety of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Pilot plant reliability metrics for grinding and fast pyrolysis of woody residues

Here we report on the effects of loblolly pine residue variability on material throughput, pilot plant uptime, operator intervention, product yield, and product quality for grinding, fast pyrolysis, and hydrotreating operations. Preprocessing throughput using a hammer mill varied between 31-48% of nameplate capacity (5 tons/hr). Grinder overloads in the size reduction step were more prevalent for lower ash and higher moisture materials. Fast pyrolysis throughput varied between 57-72% of nameplate capacity (20 kg/hr) and bio-oil yields varied between 46-53% (feedstock carbon to oil, dry basis). During fast pyrolysis operations, downtime was caused by bridging in the feed and char removal systems and plugging in the condensation system. Cohesion of feedstock and char leading to system plugging was less frequent for higher ash feedstocks, and differences in condenser plugging behavior between high and low ash feedstocks were observed. The catalyst stability of the bio-oil stabilization step was strongly dependent on the sulfur content in the bio-oil, which was higher for the high-ash residue oils. Lower moisture content in the starting biomass was consistent with lower sulfur content in bio-oil. Yields and properties of hydrotreated fuel products showed minimal deference among the bio-oils.

Klinger, Jordan↗

DOE OSTI2022

To grind or not to grind? The influence of mechanical and thermal treatments on the $\mathrm{Cu/Zn}$ disorder in $\mathrm{Cu}$ 2 $\mathrm{ZnSn}$($\mathrm{S}$ x $\mathrm{Se}$ 1-x ) 4 monograins

We report that Kesterite-type based thin film solar cell technologies are mainly based on polycrystalline absorber layers. A promising low cost alternative technology uses Cu 2 ZnSn(S x Se 1-x ) 4 (CZTSSe) monograins (single crystals of 20–100 μm size) which are fixed in a polymer matrix to form a flexible solar cell. The Cu/Zn disorder is discussed as a possible reason for band tailing causing voltage losses limiting the efficiency of CZTSSe-based devices. The experimental determination of the order parameter Q which is a quantitative measure of Cu/Zn disorder, requires a differentiation between the isoelectronic cations Cu + and Zn 2+ . An in-depth analysis of neutron diffraction data allows the determination of type and concentration of intrinsic point defects including a distinction between Cu and Zn. Neutron diffraction requires large sample volumes, thus monograins offer the unique possibility to correlate structural disorder in CZTSSe with device performance parameters. In this study we tackle the influence of grinding the monograins on stoichiometry deviations, the Cu/Zn disorder as well as intrinsic point defects and optoelectronic properties of CZTSSe monograins. Moreover, an easy methodology based on Raman scattering spectroscopy is proposed for the assessment of Cu/Zn disorder in the CZTSSe compounds.

14 SOLAR ENERGY↗

DOE OSTI2026

Subsurface mechanical damage of fused silica glass during grinding by various sub-aperture tools with and without ultrasonics

The subsurface mechanical damage (SSD) depth after grinding fused silica glass with a comprehensive set of sub-aperture fixed abrasive grinding tools [cup, wheel, belt, pad, and rotary face mill (with and without ultrasonics)] and process parameters has been statistically measured using the taper wedge technique and evaluated. Consistent with a previously reported grinding model [J. Non-Cryst. Solids 352, 5601–5617 (2006) Crossref , Materials Science and Technology of Optical Fabrication (Wiley & Sons, 2018)], based on the sliding indentation fracture by sliding particles or asperities where the normal load per particle determines the depth of the fracture (and ultimately the overall SSD depth), the dominant factor controlling SSD depth was found to be the abrasive size regardless of the tool type and process conditions. Compared to full aperture grinding methods, the overall SSD depth was higher using the sub-aperture tools, likely due to the higher effective pressure and higher load per particle distribution. Here, in addition to abrasive size, a significant reduction in SSD depth was achieved by: (1) reducing the load distribution on the abrasive particles via increase in contact area and/or decrease in mechanical loading; (2) using a more compliant host tool medium; and (3) in what we believe is a more novel way, using ultrasonics. Combining low abrasive size, larger contact area, and a compliant host, the 6 µm diamond in a resin matrix (Trizact) on a foam pad led to very low SSD depth (~ 4.6 µm), relatively fast grinding rate (186 mm 3 /h), and little or no figure degradation. This grinding tool/process is an attractive choice for final grind, resulting in significantly reduced polish out (i.e., “grey out”) times. With the rotary face mill tool, the use of ultrasonics consistently led to a SSD depth reduction (ranging from 17%–34%). A new fracture mechanics-based model, to the best of our knowledge, where the relevant normal load is parallel to the feed direction, has been developed to explain how ultrasonics leads to lower SSD depth. The key factors, supported by finite element stress analysis and load measurements, are (1) the initiation of fractures at higher z heights during the tool’s ultrasonic vertical oscillations, thus propagating less deep into workpiece; (2) reduction in load (and therefore reduction in fracture propagation distance) due to smaller tool-workpiece feed direction contact area (again caused by higher heights relative to depth of cut); (3) upward movement of the tool during oscillation leads to fracturing toward the surface instead into the depth; and finally (4) at tool’s lowest point of oscillation cycle, there may not be enough time for the fracture to propagate to its full length.

Optics and optical instruments↗

DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Exploratory investigation on the use of low-cost alternative media for ultrafine grinding of coal

In this study, the energy efficiency of three alternative grinding media including, coarse silica beads, fine silica beads, and granular sand, were evaluated and compared against standard stainless steel. Stirred mill test results show that both silica beads and granular sand were more efficient than stainless steel in producing ultrafine particles following the order of coarse silica beads>granular sand>fine silica beads>stainless steel. The finest product size corresponding to a P 80 value of 2.33 μm was generated by coarse silica beads with a nominal size of 420×1190 μm, which also consumed the least amount of grinding energy. The specific energy input was reduced by almost 50% as opposed to that of stainless steel, while the operating work index was reduced by 87%. Overall, the test data indicate that grinding media density, media particle size and shape all play a role in determining the optimized grinding behavior of the coal material.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Characterization of the Emissions and Crystalline Silica Content of Airborne Dust Generated from Grinding Natural and Engineered Stones

Abstract In this study, we systematically characterized the airborne dust generated from grinding engineered and natural stone products using a laboratory testing system designed and operated to collect representative respirable dust samples. Four stone samples tested included two engineered stones consisting of crystalline silica in a polyester resin matrix (formulations differed with Stones A having up to 90wt% crystalline silica and Stone B up to 50wt% crystalline silica), an engineered stone consisting of recycled glass in a cement matrix (Stone C), and a granite. Aerosol samples were collected by respirable dust samplers, total dust samplers, and a Micro-Orifice Uniform Deposit Impactor. Aerosol samples were analyzed by gravimetric analysis and x-ray diffraction to determine dust generation rates, crystalline silica generation rates, and crystalline silica content. Additionally, bulk dust settled on the floor of the testing system was analyzed for crystalline silica content. Real-time particle size distributions were measured using an Aerodynamic Particle Sizer. All stone types generated similar trimodal lognormal number-weighted particle size distributions during grinding with the most prominent mode at an aerodynamic diameter of about 2.0-2.3 μm, suggesting dust formation from grinding different stones is similar. Bulk dust from Stone C contained no crystalline silica. Bulk dust from Stone A, Stone B, and granite contained 60, 23, and 30wt% crystalline silica, respectively. In Stones A and B, the cristobalite form of crystalline silica was more plentiful than the quartz form. Only the quartz form was detected in granite. The bulk dust, respirable dust, and total dust for each stone had comparable amounts of crystalline silica, suggesting that crystalline silica content in the bulk dust could be representative of that in respirable dust generated during grinding. Granite generated more dust per unit volume of material removed than the engineered stones, which all had similar normalized dust generation rates. Stone A had the highest normalized generation rates of crystalline silica, followed by granite, Stone B, and Stone C (no crystalline silica), which likely leads to the same trend of respirable crystalline silica (RCS) exposure when working with these different stones. Manufacturing and adoption of engineered stone products with formulations such as Stone B or Stone C could potentially lower or eliminate RCS exposure risks. Combining all the effects of dust generation rate, size-dependent silica content, and respirable fraction, the highest normalized generation rate of RCS consistently occurs at 3.2-5.6 µm for all the stones containing crystalline silica. Therefore, removing particles in this size range near the generation sources should be prioritized when developing engineering control measures.

Public, Environmental & Occupational Health↗

DOE OSTI2024

Study of Mechanical Grinding Effects on Niobium Surface

Mechanical grinding is commonly employed to eliminate surface defects such as scratches and pits from niobium cavity surfaces or sheets before cavity fabrication. Subsequently, chemically buffered polishing or electropolishing is often utilized to completely remove residues of the polishing media and any defects induced by mechanical grinding, ensuring a pristine surface. In this study, we conducted a systematic investigation to assess the influence of mechanical grinding using silicon carbide (SiC) and aluminium oxide (Al2O3) polishing media on niobium surfaces. Additionally, the study examines the effects of post-mechanical grinding chemical treatments on surface quality.

Chouhan, V.↗

DOE OSTI2024

Study of Mechanical Grinding Effects on Niobium Surface

Mechanical grinding is commonly employed to eliminate surface defects such as scratches and pits from niobium cavity surfaces or sheets before cavity fabrication. Subsequently, chemically buffered polishing or electropolishing is often utilized to completely remove residues of the polishing media and any defects induced by mechanical grinding, ensuring a pristine surface. In this study, we conducted a systematic investigation to assess the influence of mechanical grinding using silicon carbide and aluminum oxide polishing media on niobium surfaces. Additionally, the study examines the effects of post-mechanical grinding chemical treatments on surface quality.

Chouhan, V.↗

DOE OSTI2021

Joint influence of γ–irradiation and high temperature shear grinding on the IR spectra and surface–energy properties of polyethylene

The optical and surface-energy properties of polyethylene (PE) subjected to γ-irradiation and post-radiation, high temperature, shear grinding are presented. Comparison of the IR spectra of the initial and γ-irradiated PE shows that oxygen-containing groups and unsaturated bonds in the polymer macromolecules are formed and accumulate during their radiolysis in air, increasing with γ-irradiation dose. A redistribution of the products of radiation-chemical conversion on the surface of the polymer granules throughout the entire volume of the powder occurs after high-temperature shear milling to a powder as observed in the IR spectrum. Polar functional groups due to oxidation reactions are observed on the surface layer of the sample after post-radiation grinding. Furthermore, the initial polymer surface is weakly basic with an acidity parameter of -0.34. The value of the acidity parameter of the sample made of ground irradiated PE has an acidic surface with an acidity parameter of 0.65. γ irradiation of the secondary processing of PE waste with high-temperature shear grinding is a promising approach to obtain a secondary PE powder with specified parameters and different degrees of functionalization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Balancing sugar recovery and inhibitor generation during energycane processing: Coupling cryogenic grinding with hydrothermal pretreatment at low temperatures

Pretreatment of lignocellulosic biomass at high temperatures or with oxidizing chemicals generate various inhibitors that restrict the efficient bioconversion of sugars in subsequent steps. The present study systematically investigates individual and combinatorial effects of pretreatment parameters on the generation of inhibitors. Herein, a plot between pretreatment temperature and inhibitor revealed optimum pretreatment temperature for energycane bagasse i.e., 170 °C beyond which total inhibitor production increased exponentially. No inhibitor production was observed on mechanical processing i.e., disk milling/cryogenic grinding of biomass. Evaluation of response surface regression exhibited that biomass solids loading has a significant effect on inhibitor generation at higher temperatures. The concentrations of certain inhibitors such as acetic acid, furfurals, and HMF increased more than 3-folds on doubling the solids loading. Furthermore, a novel low-severity approach of low-temperature hydrothermal pretreatment coupled with cryogenic grinding for lignocellulosic biomasses has been introduced which improved sugar yields while maintaining a low inhibitor concentration.

09 BIOMASS FUELS↗

DOE OSTI2020

Effect of endoglucanase and high-pressure homogenization post-treatments on mechanically grinded cellulose nanofibrils and their film performance

In this study, the effects of mechanical grinding (G) assisted by endoglucanase (E) and high-pressure homogenization (H) post-treated cellulose nanofibrils (CNFs) and its film properties were investigated. Compared to only mechanical grinding, these two post-treatment processes improved the size uniformity of CNFs in width. Additionally, the crystallinity of GECNFs was increased by 4.3 % and the resulting film exhibited low oxygen permeability rate (6.33 mL/m 2 ·day). Moreover, the combination post-treatments of enzyme and homogenization improved the tensile strength and transparency of CNFs films from 132.31 MPa, 27.52 %– to 177.99 MPa, 61.75 %, respectively. Besides, a composite of acrylic resin ABPE-10 and GEHCNFs film under negative pressure improved the transparency (85.68 %) and water contact angle (104.11°) of film. This work also provides insight on the relationship between the CNFs morphology and their film properties, which can be used to improve the CNFs film performance and promote future applications of CNFs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Pilot Plant Reliability Metrics for Grinding and Fast Pyrolysis of Woody Residues

The reliability of biomass size reduction, feeding, and conversion processes remains a critical technical hurdle and important cost driver for biomass conversion systems. While Biorefinery projects have typically focused on scaling up conversion technologies that maximize yield of desired products, e.g. fuels and chemicals, solids handling and reactor feeding systems are often considered secondarily. These are frequently scaled down or adapted from other industries, without a full appreciation of how biomass heterogeneity and variability impact process reliability. Here we present the effects of feedstock variability on relative throughput, mass loss, plant uptime, operator intervention, product yield, and product quality for grinding and fast pyrolysis operations at the pilot scale. Loblolly pine residues were sourced and collected using commercial harvesting techniques. Grinding and pyrolysis experiments were performed at INL's Biomass Feedstock National User Facility and NREL's Thermal and Catalytic Process Development Unit, respectively. Preprocessing throughput using a hammer mill varied between 31-48% of nameplate capacity (5 tons/hr), and fast pyrolysis throughput varied between 57-72% of nameplate capacity (20 kg/hr) for an overall system throughput of 18-35% of nameplate capacity across biomass preprocessing and conversion to pyrolysis oil. Pyrolysis oil yields varied between 46-53% (feedstock carbon to oil, dry basis). Grinder overloads in the size reduction step were more prevalent for lower ash and higher moisture materials. During fast pyrolysis operations, downtime was caused by bridging in the feed and char removal systems and plugging in the condensation system, and significant variation in the type and frequency of operator intervention was observed between feedstocks. Cohesion of solids (feedstock and char) leading to system plugging appeared less problematic for higher ash feedstocks, and differences in condenser plugging behavior between high and low ash feedstocks indicates the composition and physical nature of the deposited material is important for process reliability and is feedstock dependent.

09 BIOMASS FUELS↗

DOE OSTI2022

Metallic components with enhanced mechanical strength through surface mechanical grinding

A method of strengthening a component made of a metallic material. The method includes subjecting the component to a mechanical grinding process incorporating a relative motion between a tool and the component forming a gradient structure on the surface of the component, resulting in increased tensile strength of the component. A method of strengthening a component made of a TWIP steel. The method includes subjecting the component made of TWIP steel to a mechanical grinding process incorporating a relative motion between a tool and the component forming a gradient structure containing a surface nanolaminate layer, a shear band layer, and an inner deformation twinned layer, resulting in increased tensile strength of the component. A component made of a TWIP steel containing a gradient structure with a surface nanolaminate layer, a shear band layer, and a deformation twinned layer.

Ding, Jie↗

DOE OSTI2023

Metallic components with enhanced mechanical strength through surface mechanical grinding

A method of strengthening a component made of a metallic material. The method includes subjecting the component to a mechanical grinding process incorporating a relative motion between a tool and the component forming a gradient structure on the surface of the component, resulting in increased tensile strength of the component. A method of strengthening a component made of a TWIP steel. The method includes subjecting the component made of TWIP steel to a mechanical grinding process incorporating a relative motion between a tool and the component forming a gradient structure containing a surface nanolaminate layer, a shear band layer, and an inner deformation twinned layer, resulting in increased tensile strength of the component. A component made of a TWIP steel containing a gradient structure with a surface nanolaminate layer, a shear band layer, and a deformation twinned layer.

Ding, Jie↗

DOE OSTI2020

Grinding of additively manufactured silicon carbide surfaces for optical applications

Many of the properties of Silicon carbide (SiC) are advantageous for optical applications, such as telescope mirrors and industrial laser systems. However, the base shapes of complex components are costly and difficult to manufacture. Leveraging additive manufacturing, near net complex components are readily processed. In this work, we investigate the post processing of additively manufactured SiC (AM SiC) compared to chemical vapor deposited (CVD) SiC. The specific grinding energy for the AM SiC was lower than CVD, however the trends were the same. A specular finish was observed on both materials but the AM SiC finish was limited due to residual porosity.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Surface grain refinement of casting A380 aluminum alloy by ultrasonic-assisted surface mechanical grinding treatment

A novel surface processing technique, ultrasonic-assisted surface mechnical grinding treatment (U-SMGT), was proposed and applied to modify the surface micriostructure of the casting aluminum alloy (A380). Comprehensive post-process chracterization techniques including 3D profilometry, optical microscope, scanning electric microscopy (SEM), and electron backscatter diffraction (EBSD) were carried out to investigate the surface morphology and microstructure of the processed region (PR). It was found that a surface layer of grain refinement with a thickness of about 50 µm was formed. In the as-received base material (BM), large clusters of dendritic eutectic phase with a size of approximately 20 µm were isolated by α-Al matrix. Nano-indentation tests showed that hardness of the eutectic and α-Al in the as-received BM was 2.15 GPa and 1.2 GPa respectively. After U-SMGT, the large dendritic eutectic phase was broken down into much fine particles with an average size of 0.57 µm. These fine particles were uniformly distributed into the α-Al matrix. Nano-indentation measurement exhibited a hardness of 2.27 GPa within the processed region. The overall high hardness in the processed region is a result of the pinning effect of uniformly distributed fine dendrites and grain refinement of Al-matrix.

36 MATERIALS SCIENCE↗