Analysis of Chemical Compounds of Gaseous and Particulate Pollutants from the Open Burning of Agricultural HDPE Film Waste

Background and objective: Illegal open-air incineration, which is criticized as a leading source of air pollutants among agricultural activities, currently requires constant effort and attention. Countries around the world have been undertaking studies on the emission of heavy metal substances in fine dust discharged during the incineration process. A precise analytical method is required to examine the harmful effects of particulate pollutants on the human body.Methods: In order to simulate open-air incineration, the infrastructure needed for incineration tests complying with the United States Environmental Protection Agency (EPA) Method 5G was built, and a large-area analysis was conducted on particulate pollutants through automated scanning electron microscopy (SEM)-energy-dispersive X-ray spectroscopy (EDS). For the test specimen, high-density polyethylene (HDPE) waste collected by the DangJin Office located in Choongcheongnam-do was used. To increase the identifiability of the analyzed particles, the incineration experiment was conducted in an incinerator three times after dividing the film waste into 200 g specimens.Results: Among the metal particulate matters detected in the HDPE waste incineration test, transition metals included C (20.8-37.1 wt%) and O (33.7-37.9 wt%). As for other chemical matters, the analysis showed that metal particulate matters such as metalloids, alkali metals, alkaline earth metals, and transition metals reacted to C and C-O. Si, a representative metalloid, was detected at 14.8-20.8 wt%, showing the highest weight ratio except for C and O.Conclusion: In this study, the detection of metal chemicals in incinerated particulate matters was effectively confirmed through SEM-EDS. The results of this study verified that HDPE waste adsorbs metal chemicals originating from soil due to its own properties and deterioration, and that when incinerated, it emits particulate matters containing transition metals and other metals that contribute to the excessive production and reduction of reactive oxygen species.

Concrete Pavement Mixtures with High Supplementary Cementitious Materials Content: Volume 3

Fly ash is a by-product of coal combustion, made up of particles that are collected through various methods. This by-product has been used successfully as a partial Portland cement replacement in concrete, but the performance predictions of fly ash in concrete have been difficult to predict, especially at high fly ash replacement rates. This study focuses on comparing the performance of concrete with a variety of fly ash mixtures as well as the particle distribution and chemical makeup of fly ash. The slump, unit weight, compressive strength, and isothermal calorimetry tests were used to measure the performance of concrete at 0%, 20%, and 40% fly ash replacement levels. The particle distribution of fly ash was measured with an automated scanning electron microscope. Additionally, the major and minor oxides from the chemical makeup of fly ash were measured for each mixture and inputted into a table. The particle distribution and chemical makeup of fly ash were compared to the performance of slump, unit weight, compressive strength, isothermal calorimetry, and surface electrical resistivity.

Mineral Liberation: A Case Study for Buzwagi Gold Mine

Buzwagi Gold Mine (BGM) process plant was designed such that, after secondary grinding, gold and copper are recovered by flotation. However, the flotation circuit had been inefficient, and as a result, cyanidation of flotation tailings is currently conducted to improve gold recovery. The inefficient flotation is suspected to be due to mineralogical variations of ores treated. Hence, mineral liberation characteristics of three ore blends treated by BGM were investigated by automated Scanning Electron Microscope (SEM) whereby five fractions (i.e. -1 +0.5 mm, -0.5 +0.25 mm, -0.25 +0.125 mm, -0.125 +0.063 mm and -0.063 mm) were used. It was found that pyrite-pyrrhotite is the major valuable phase and the host of gold. Furthermore, pyrite-pyrrhotite was liberated at relatively coarse size (i.e. approx. 200-400 µm). Additionally, quartz, feldspar, muscovite and biotite-chlorite were the main gangue phases. Pyrite-pyrrhotite grain size distribution was coarser than most gangue minerals in the ore blends, indicating that most of the milling energy was lost in grinding of gangue phases. Since gold host phase (pyrite-pyrrhotite) was liberated at coarser sizes, it was concluded that the efficiency of gravity circuit could not be affected. However, the flotation process will still require finer feed (i.e. ≤ 125 µm) for its efficiency. Keywords: Mineral liberation; Gold ore blends; Flotation Performance; Pyrite-pyrrhotite; Automated Mineralogy

Towards a Fully Automated Scanning Probe Microscope for Biomedical Applications

The increase in capabilities of Scanning Probe Microscopy (SPM) has resulted in a parallel increase in complexity that limits the use of this technique outside of specialised research laboratories. SPM automation could substantially expand its application domain, improve reproducibility and increase throughput. Here, we present a bottom-up design in which the combination of positioning stages, orientation, and detection of the probe produces an SPM design compatible with full automation. The resulting probe microscope achieves sub-femtonewton force sensitivity whilst preserving low mechanical drift (2.0±0.2 nm/min in-plane and 1.0±0.1 nm/min vertically). The additional integration of total internal reflection microscopy, and the straightforward operations in liquid, make this instrument configuration particularly attractive to future biomedical applications.

Automated Gold Grain Counting. Part 2: What a Gold Grain Size and Shape Can Tell!

Glacial drift exploration methods are well established and widely used by mineral industry exploring for blind deposit in northern territories, and rely on the dispersion of mineral or chemical signal in sediments derived from an eroded mineralized source. Gold grains themselves are the prime indicator minerals to be used for the detection of blind gold deposits. Surprisingly, very little attention has been dedicated to the information that size and shape of gold grain can provide, other than a simple shape classification based on modification affecting the grains that are induced in the course of sediment transport. With the advent of automated scanning electron microscope (SEM)-based gold grain detection, high magnification backscattered electron images of each grain are routinely acquired, which can be used for accurate size measurement and shape analysis. A library with 88,613 gold grain images has been accumulated from various glacial sediment surveys on the Canadian Shield and used to detect trends in grains size and shape. A series of conclusions are drawn: (1) grain size distribution is consistent among various surveys and areas, (2) there is no measurable fine-grained gold loss due to natural elutriation in ablation or reworked till, or during the course of reverse circulation drilling, (3) there is no grain size sorting during glacial transport, severing small grains from large ones, (4) shape modification induced by transport is highly dependent on grain size and original shapes, and (5) the use of grain shape inherited from neighboring minerals in the source rocks is a useful feature when assessing deposit types and developing exploration strategies.

Automated Gold Grain Counting. Part 1: Why Counts Matter!

The quantitative and qualitative assessment of gold grains from samples of glacial till is a well-established method for exploring gold deposits hidden under glaciated cover. This method, which is widely used in the industry and has resulted in numerous successes in locating gold deposits in glaciated terrain, is still based on artisanal gravity separation techniques and visual identification. However, being artisanal, it is limited by inconsistent recoveries and difficulties associated with visually identifying the predominantly small gold grains. These limitations hinder its capacity to decipher subtle or complex signals. To improve detection limits through the recovery of small gold grains, a new approach has recently been introduced into the industry, which is commercially referred to as the “ARTGold” procedure. This procedure involves the use of an optimized miniature sluice box coupled with an automated scanning electron microscopy routine. The capabilities of this improved method were highlighted in this study by comparing till surveys conducted around the Borden gold deposit (Ontario, Canada) using the conventional and improved methods at both local and regional scales. Relative to that with the conventional approach, the improved method increased the recovery of gold grains from samples (regional and down-ice mineralization) by almost one order of magnitude. (regional and down-ice mineralization), dominantly in regard of the small size fractions. Increasing the counts in low-abundance regional samples allows for a better discrimination between background signals and significant dispersions. The described method offers an alternative for improving the characterization of gold dispersal in glaciated terrain and related gold deposit footprints.

Machine learning methodology for high throughput personalized neutron dose reconstruction in mixed neutron + photon exposures

We implemented machine learning in the radiation biodosimetry field to quantitatively reconstruct neutron doses in mixed neutron + photon exposures, which are expected in improvised nuclear device detonations. Such individualized reconstructions are crucial for triage and treatment because neutrons are more biologically damaging than photons. We used a high-throughput micronucleus assay with automated scanning/imaging on lymphocytes from human blood ex-vivo irradiated with 44 different combinations of 0–4 Gy neutrons and 0–15 Gy photons (542 blood samples), which include reanalysis of past experiments. We developed several metrics that describe micronuclei/cell probability distributions in binucleated cells, and used them as predictors in random forest (RF) and XGboost machine learning analyses to reconstruct the neutron dose in each sample. The probability of “overfitting” was minimized by training both algorithms with repeated cross-validation on a randomly-selected subset of the data, and measuring performance on the rest. RF achieved the best performance. Mean R2 for actual vs. reconstructed neutron doses over 300 random training/testing splits was 0.869 (range 0.761 to 0.919) and root mean squared error was 0.239 (0.195 to 0.351) Gy. These results demonstrate the promising potential of machine learning to reconstruct the neutron dose component in clinically-relevant complex radiation exposure scenarios.

Automated Gold Grain Counting. Part 1: Why Counts Matter!

The quantitative and qualitative assessment of gold grains from samples of glacial till is a well-established method for exploring gold deposits hidden under glaciated cover. This method, widely used by the industry and which produced numerous successes in locating gold deposits in glaciated terrain, is still based on artisanal gravity separation techniques and visual identification. However, being artisanal, it is limited by inconsistent recoveries and the difficulty to visually identify the predominantly occurring small gold grains. These limitations hinder its capability to deceipher subtle or complex signal. To improve detection limits through recovery of small gold grains, a new approach has recently been introduced in the industry (commercially referred as “ARTGold” procedure) using an optimized miniature sluice box coupled with an automated scanning electron microscopy routine. The capabilities of this improved method are highlighted by comparing till surveys conducted around the Borden gold deposit (Ontario, Canada) using the conventional and improved methods at both local and regional scales. Relative to the conventional approach, the improved method recovered almost one order of magnitude more gold grains from samples (regional and down-ice mineralization), dominantly in small size fractions. Increasing the counts in low-abundance regional samples enables better discrimination between background signals and significant dispersions. The method offers an alternative to improve characterization of gold dispersal in glaciated terrain and the related gold deposit footprints.

Energy Storage in Earth-Abundant Dolomite Minerals

Dolomite, a calcium magnesium mineral (CaMg(CO3)2), is considered an undesirable accompanying mineral in the phosphoric acid production process and, as such, large quantities of this mineral are available in Florida. This study is aimed toward the characterization of the high-concentration phosphatic dolomite pebbles (handpicked dolomites) received from the Florida Industrial and Phosphate Research Institute (FIPR) and investigate their feasibility for thermochemical energy storage (TCES). The chemical composition, structural and microstructural characteristics of commercial and handpicked dolomite minerals was studied using a variety of techniques such as X-ray Fluorescence (XRF), Fourier-transform infrared spectroscopy (FTIR), and an automated mineralogy Automated SEM-EDX Mineralogy (or automated scanning electron microscopy) with energy dispersive X-rays spectrometer (SEM-EDX), which confirmed the phosphatic pebbles received contains dolomite (CaMg(CO3)2) phase in a high percentage. Particle size and the surface area were measured using XRD and N2 adsorption, the Brunauer–Emmett–Teller (BET) methods. Thermogravimetric analysis (TGA) was used to determine the activation energy for the calcination and re-carbonation reactions of the dolomite pebbles in nitrogen (N2) and carbon dioxide (CO2) atmospheres at temperatures up to 800 °C. The present results exhibit, for the first time, the potential for using abundant, high phosphatic concentration dolomite possessing long-term cycling behavior for thermochemical energy storage applications in Concentrated Solar Power (CSP) plants.