Ultra-centrifugal Mill Research Articles

Comparison of noodle-making performance of purple-colored whole wheat flour prepared with a jet mill and an ultra-centrifugal mill.

This study explores the impact of milling methods on the quality and noodle-making performance by comparing jet-milled (WF-JM) and ultra-centrifugally milled (WF-UM) purple-colored whole wheat flours. WF-JM exhibits smaller starch granules and a fragmented protein matrix attributed to the increased milling pressure. Physicochemical analyses reveal lower moisture and higher damaged starch in WF-JM. Rheological analyses show lower viscosity in the WF-JM blends. The mixograph results reveal weaker dough-mixing stability and strength for WF-JM. Cooked noodles from WF-JM are uneven, in contrast to uniform WF-UM strands. Blending WF-UM enhances noodle quality. Overall, the noodle-making performance for WF-JM was inferior compared to WF-UM, confirming the significantly negative impact of damaged starch and fragmented protein matrix in whole wheat flour than the positive effect of particle size. This study highlights the complex interplay between milling methods, particle size, and physicochemical attributes, providing insights for optimizing whole wheat flour processing and product quality.

Impact of ultracentrifugal milling on the thermo-rheological, functional, and physicochemical properties of yellow and green pea flour

Pea seeds conversion into flour enhance their incorporation into diverse food systems. However, milling impacts changes in the flour's physicochemical and technofunctional properties. In this study, the impact of ultracentrifugal milling on the thermal, rheological, functional and physicochemical properties of flour from yellow and green pea varieties was investigated. Pea seeds were milled to maximum particle sizes of 0.25, 0.50 and 1.00 mm based on different screen aperture fitted to the ultracentrifugal mill. Scanning electron microscopy showed that flour samples milled with the 0.25 mm screen aperture had higher disentangled protein particles but more damaged starch particles compared to the 0.50 and 1.00 mm screens. The FTIR analysis indicated similar spectra with varying functional groups at corresponding wavelengths but different absorbance intensity. At 2853 cm−1 wavelength, additional peak for cellulose was detected in 0.25 mm milling condition but absent in other samples. Flour milled to 0.25 and 0.50 mm maximum particle size had the most desirable outcomes to rheological and thermal attributes. Principal component analysis score plots elucidated relationship between milling conditions, flour functionality and pea variety with PC1 at 46.64% and PC2 at 34.53%. These findings demonstrate that milling conditions can be a potential tool to manipulate pea flour functionality.

Combined Effects of Particle Size and Dough Improvers on Improving the Quality of Purple-Colored Whole Wheat Bread.

Consumers' interest in healthy products is increasing. However, the production of excellent-quality whole wheat bread (WWB) faces challenges due to the reduced gluten functionality and varied particle sizes of whole wheat flour (WWF). This study aimed to explore the enhancement of purple-colored WWB quality by controlling the particle size of WWF and using dough improvers. Six purple-colored WWFs were obtained using an ultra-centrifugal mill with different sieve openings (0.5 and 1.0 mm) and rotor speeds (6000, 10,000, and 14,000 rpm). The average particle diameter (d50) of the smaller particle size group (S) and the larger particle size group (L) based on the sieve opening ranged from 115 to 258 μm and 294 to 492 μm, respectively. Group S demonstrated higher water absorption, damaged starch, and gluten strength compared to group L. Additionally, group S exhibited a greater bread volume and height compared to group L. Among the tested dough improvers (vital wheat gluten, vitamin C, enzymes, and emulsifiers), vital wheat gluten was the most effective in improving the quality of purple-colored WWB. The improvement effect was significantly greater in group S than in group L. These findings suggest that controlling the particle size of purple-colored WWFs and utilizing dough improvers can result in superior-quality WWB.

Influence of Particle Size and Xylanase Pretreatment of Proso Millet Bran on Physical, Sensory and Nutritive Features of Gluten-Free Bread.

Millet bran is a by-product rich in dietary fibre, micronutrients and bioactive compounds which are often deficient in a gluten-free diet. Previously, cryogenic grinding has been shown to improve the functionality of bran to some extent, although it offered limited benefits for bread making. This study aims to investigate the effects of adding proso millet bran depending on its particle size and xylanase pretreatment on the physicochemical, sensory and nutritional properties of gluten-free pan bread. Coarse bran (d50=223 μm) was ground to medium size (d50=157 μm) using an ultracentrifugal mill or to superfine particles (d50=8 μm) using a cryomill. Millet bran presoaked in water (for 16 h at 55 °C) with or without the addition of fungal xylanase (10 U/g) replaced 10% of the rice flour in the control bread. Bread specific volume, crumb texture, colour and viscosity were measured instrumentally. Along with proximate composition, the content of soluble and insoluble fibre, total phenolic compounds (TPC) and phenolic acids as well as total and bioaccessible minerals of bread were assessed. Sensory analysis of the bread samples included a descriptive, hedonic and ranking test. Dietary fibre content (7.3-8.6 g/100 g) and TPC (42-57 mg/100 g) on dry mass basis of the bread loaves depended on bran particle size and xylanase pretreatment. The effect of xylanase pretreatment was most evident in the loaves with medium bran size in terms of higher content of fibre soluble in ethanol (45%) and free ferulic acid content (5%), improved bread volume (6%), crumb softness (16%) and elasticity (7%), but lower chewiness (15%) and viscosity (20-32%). Bread bitterness and dark colour were increased after adding medium-sized bran but its bitter aftertaste, crust crookedness, crumb hardness and graininess were reduced with xylanase pretreatment. Although bran addition impaired protein digestibility, it enriched the bread with iron (341%), magnesium (74%), copper (56%) and zinc (7.5%). Xylanase pretreatment of the bran resulted in the improved bioaccessibility of zinc and copper of the enriched bread compared to the control and bread without xylanase. Application of xylanase to medium sized bran obtained by ultracentrifugal grinding was more successful than its application to superfine bran obtained by the multistage cryogrinding as it resulted in more soluble fibre in gluten-free bread. Moreover, xylanase was proven beneficial in maintaining desirable bread sensory properties and mineral bioaccessibility.

Quality Characteristics and Antioxidant Activity of Fresh Noodles Formulated with Flour-Bran Blends Varied by Particle Size and Blend Ratio of Purple-Colored Wheat Bran

This study explored the noodle-making performance of flour blends with different particle sizes and blending ratios of purple-colored wheat bran and their antioxidant properties. The bran particle size was reduced using an ultra-centrifugal mill equipped with 1, 0.5, and 0.2 mm sieves. The damaged starch and swelling capacity of the bran were analyzed. Quality of the flour-bran blends at different blending ratios was analyzed by solvent retention capacity (SRC). Noodles made from the blends and their corresponding antioxidant activities were examined. The damaged starch and swelling capacity of bran were higher for smaller particles than for larger particles. Water and sodium carbonate SRC values of blends increased as the bran particle size decreased. The smaller the bran particles incorporated in the cooked noodles, the greater firmness and springiness measured. The antioxidant activity of noodles made with blends reflected better embedding of the small particles of bran than the large particles into noodle sheets. Small bran particles significantly enhanced noodles’ quality and antioxidant activity at higher blending ratios than large bran particles. Particle size reduction of bran enhanced the noodle-making performance of flour blended with purple-colored wheat bran; this could increase the utilization of bran to produce noodles with health benefits.

Physicochemical and Thermal Properties, and Starch Digestibility of Dry-Milled Rice Flours with Different Amylose Contents using an Ultra-Centrifugal Mill

Physicochemical and Thermal Properties, and Starch Digestibility of Dry-Milled Rice Flours with Different Amylose Contents using an Ultra-Centrifugal Mill

Toward a comprehensive understanding of ultracentrifugal milling on the physicochemical properties and aromatic profile of yellow pea flour

Yellow pea (Pisum sativum L., YP) grain is generally milled into flour for further processing or direct consumption. However, the comprehensive relationship between milling configurations and YP flour properties remains unclear. The aim of this study is to investigate the effect of configurations (screen aperture size and rotor speed) of ultracentrifugal mill on the physicochemical properties and aromatic profiles of YP flours. Starch damage, morphology, particle size distribution, pasting, thermal property, and aromatic profiles of YP flours were studied. Results show that starch damage increased significantly as the screen aperture size decreased. The YP flour produced with a 500 µm aperture screen had the most stable pasting and thermal properties. With untargeted metabolomic approaches, 2-ethyl-1-hexanol could potentially be applied as an aroma maker to distinguish if an excessive milling or inappropriate configurations of ultracentrifugal mill are applied. This work has furnished fundamentals for the milling and application of YP flour.

Prediction model based on artificial neural network for pyrophyllite mechano-chemical activation as an integral step in production of cement binders

The optimal outputs of pyrophyllite mechano-chemical activation in an ultra-centrifugal mill performing under different technological conditions were determined by analytical modeling and verified via Artificial Neural Network in order to be employed in the production of cement-based binders. Cluster Analysis and Principal Component Analysis were utilized in assessment of the effect of activation process parameters on the activated pyrophyllite quality. Artificial Neural Network which performed with high prediction accuracy, i.e. 0.914 during the training period, was sufficient for precise prediction of activated pyrophyllite quality in a wide range of processing parameters. The probability of utilization of observed activation products was estimated through interrelation of technological parameters (mesh size sieve, activation period, specific energy consumption) and acquired characteristics of pyrophyllite (grain diameter, specific surface area). The optimal products singled out from each activation sequence were used as mineral additives in the mix-designs of four cement binders (cement replacement portion was 30%). Influence of activated pyrophyllite additions on the cement chemistry, mineral phase compositions and microstructures of the cement binders were monitored by instrumental techniques (DTA/TGA, XRD, SEM). Activated pyrophyllite showed characteristics of pozzolana as it slightly accelerated early stages of hydration, decreased cement hydration energy and increased the quantity of cement mineral alite at later hydration stages. Micron-sized crystalline foila characteristic for mechanically activated pyrophyllite formed micro-reinforcement within cement binder microstructure.

Cleaner preparation of poly(vinylidene fluoride)/barium titanate composites: Thermal, mechanical, and dielectric properties and relaxation dynamics

ABSTRACTTraditional polymer composite preparation techniques often employ organic solvents, which can damage the environment, to disperse inorganic fillers. In this article, classic nanocomposites with poly(vinylidene fluoride) (PVDF) polymer matrices and BaTiO3 nanoparticle (BTP) fillers were created by a clean method combining planetary ball milling with an ultracentrifugal mill and then hot pressed into thin films. The microstructures, properties and relaxation dynamics of the thin films were characterized and analyzed. Scanning electron microscopy results demonstrated that BTP was homogeneously dispersed in the PVDF matrix. The thermal, mechanical, and dielectric properties were comparable to those of composite films prepared by solution mixing. Dielectric analysis revealed that the dielectric constant of the thin films reached 14 (104 Hz) when the volume fraction of BTP was 30%; however, the dielectric loss was 0.1 (104 Hz). Additionally, the dielectric loss spectra fitted with the Havriliak−Negami (H−N) and Vogel Fulcher equations were employed to analyze the relaxation dynamics of the nanocomposites. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47254.

Whole Grain Wheat Flour Production Using an Ultracentrifugal Mill

Interest has been growing in whole grain products. However, information regarding the influence of the ultracentrifugal mill on whole grain flour quality has been limited. An experiment was conducted to produce whole wheat flour with hard red spring (HRS) wheat using an ultracentrifugal mill. This study determined the effect of centrifugal mill parameters as well as grain moisture (10–16%) on producing whole wheat flour and its final products. Mill parameters studied were rotor speed (6,000–15,000 rpm) and feed rate (12.5–44.5 g/min). Results showed that fine particle size (<150 µm) was favored by low seed moisture content (10–12%) and high rotor speed (12,000–15,000 rpm). Flour moisture content was positively related to seed moisture content. Wheat grain with low seed moisture content (10–12%) milled with high rotor speeds (12,000–15,000 rpm) produced desirable whole grain wheat flour quality, with 70–90% of fine particle size portion and low damaged starch (less than 11%). This whole wheat flour produced uniform and machinable dough that had low stickiness and formed bread with high loaf volume.

Effect of Single‐Pass and Multipass Milling Systems on Whole Wheat Durum Flour and Whole Wheat Pasta Quality

Single‐pass and multipass milling systems were evaluated for the quality of whole wheat durum flour (WWF) and the subsequent whole wheat (WW) spaghetti they produced. The multipass system used a roller mill with two purifiers to produce semolina and bran/germ and shorts (bran fraction). The single‐pass system used an ultracentrifugal mill with two configurations (fine grind, 15,000 rpm with 250 μm mill screen aperture; and coarse grind, 12,000 rpm with 1,000 μm mill screen aperture) to direct grind durum wheat grain into WWF or to regrind the bran fraction, which was blended with semolina to produce a reconstituted WWF. Particle size, starch damage, and pasting properties were similar for direct finely ground WWF and multipass reconstituted durum flour/fine bran blend and for direct coarsely ground WWF and multipass reconstituted semolina/coarse bran blend. The semolina/fine bran blend had low starch damage and had desirable pasting properties for pasta cooking. WW spaghetti was better when made with WWF produced using the multipass than single‐pass milling system. Mechanical strength was greatest with spaghetti made from the semolina/fine bran or durum flour/fine bran blends. The semolina/fine bran and semolina/coarse bran blends made spaghetti with high cooked firmness and low cooking loss.

The effect of mechano-chemical activation and surface treatment of limestone filler on the properties of construction composites

Abstract The effect of the combined actions of milling and hydrophobization procedures applied in construction composites synthesis was investigated. The mortars were prepared with cement (CEM I 42.5) and calcite aggregate complying the standard 1:3 mix ratio. The limestone filler (10 wt%) was added to the mixture upon its mechano-chemical activation in an ultra-centrifugal mill. The activation variables (milling time, rotor velocity, sieve mesh size) were altered to achieve the optimal quality of the powder. The treatment was optimized via chemometric tools. The r2 values (0.955–0.998) of second order polynomial models accurately predicted the output and the Standard score analysis chose the optimal activation parameters: 4.25 min; 48.58 m/s and 80 μm sieve. The selected filler and all three aggregate fractions were coated with stearic acid via dry procedure. The mortar mixes, prepared with uncoated (M1) and coated (M2) aggregate and filler, were cured for a period of 28 days during which compressive strength and water absorption were monitored. The dimensional changes in mortars were estimated via TMA dilatometer measurements. Thermo-analytical methods (DTA/TGA) were applied in the thermal behavior analysis. Mineralogical and morphological changes in the structure of hardened composite were detected by XRD and SEM, respectively. Limestone aggregate led to lower final compressive strengths in mortar, but it produced an infinitesimally small shrinkage at 1000 °C. The hydrophobization via stearic acid initiated the decrease in water absorption and formation of needle-like micro-network that filled structural voids reducing open porosity. The assessment of the effects of limestone utilization as a filler and as an aggregate on the mortar performances confirmed that this novel water-repellent composite is applicable in structural design.

Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling

The properties of seven montmorillonite-rich bentonites of different geological origin were investigated prior and subsequent to mechano-chemical processing in an ultra-centrifugal mill. The objective of the experiment was altering the bentonite types and activation parameters in order to determine the optimal milling conditions that produce material which is physico-mechanically and microstructurally applicable as a binder replacement and sorbent in the construction composites. The efficiency of bentonite activation was assessed by chemometrics and Artificial neural networks mathematical modeling. Principal component analysis and analysis of variance were used in the observation of the influence of input variables (bentonite chemical composition) and process parameters (milling duration, rotor velocity) on the product characteristics: density, specific surface area, grain size and distribution, cation exchange capacity, melting point, compressive strength, shrinkage and porosity. When the ANN models for the observed responses, related to predicted bentonite characteristics and quality, were compared to experimental results, they correctly predicted the responses. The processed data also adequately fitted to the regression second order polynomial models. The SOP models, which showed r2 values from 0.357 to 0.948, and were able to predict the observed responses in a wide range of processing parameters, while ANN models performed high prediction accuracy (0.776–0.901) and can be considered as precise for response variables prediction. The combination of the conducted mathematical analyses showed that that increase/decrease in output values was stabilized after 30min of activation. Mathematically attained interpretations were correlated with the results of the instrumental analyses (XRD, DTA/TG, SEM) to confirm the adoption of B6 bentonite as a preferable type and 30min as an optimal milling time for acquiring quality of clay powder that will be used in structural and thermal applications.

Chemometric assessment of mechano-chemically activated zeolites for application in the construction composites

Abstract Natural zeolites of clinoptilolite type from seven deposits were submitted to mechano-chemical activation in a Retsch ultra-centrifugal mill. The zeolite types and activation parameters were altered during the experiment with an aim to determine the optimal combination that would produce powder with adequate physico-chemical and microstructural properties for application as a binder replacement and an ion-exchanger in the construction composites. The effects of input variables (chemical composition of the samples) and process parameters (the rotor velocity and the activation period) on the efficiency of zeolite activation were investigated in terms of dependent parameters such as: specific surface area, grain size distribution, cation exchange capacity, melting point, compression strength, shrinking, water absorption and apparent porosity. Cluster analysis, Principal component analysis and Standard score analysis were applied in the assessment of the acquired product quality. Artificial neural networks (ANN) were developed in mathematical modeling of observed responses. Subsequently the ANN was compared to experimental results and the developed second order polynomial models. Developed models showed r2 values in the 0.822–0.998 range, meaning that they were able to predict the observed responses in a wide range of processing parameters. ANN models performed high prediction accuracy (0.975–0.993) and can be considered as precise and very useful for response variables prediction. The combination of the conducted mathematical analyses isolated Z5 zeolite as a preferable type, and 20000 rpm and 30 min as an optimal activation set of parameters. Mathematically derived conclusions were confirmed by results of instrumental analyses (XRD, DTA/TG, SEM).

Effects of different mechanical treatments on structural changes of lignocellulosic waste biomass and subsequent Cu(II) removal kinetics

In this paper, the character of structural changes induced by different mechanical treatments to Prunus persica stones (PSs), and its subsequent effect on biosorption kinetics of Cu(II) were investigated. PSs were processed in vibratory disk mill (PS-V) and ultra-centrifugal mill (PS-C) and characterized by XRD, BET, SEM and FTIR spectroscopy. It was shown that PS-V was smaller and more reactive with less crystallinity index and hydrogen bond intensity compared to PS-C. In opposite, surface area of the PS-C was bigger than that of the PS-V. The total pore volume was about threefold, while the volume of micro pores was 9.29 times higher in PS-Cs than in PS-Vs.The kinetics of Cu(II) biosorption by both PSs was tested through various kinetic models: pseudo-first and pseudo-second order rate equations, Elovich equation, Boyd model, Weber–Morris and Urano–Tachikawa intraparticle diffusion model. For both sample types, Cu(II) biosorption occurred through combination of intraparticle and film diffusion mechanism, while kinetic results were best described by the pseudo-second order kinetic model. At the same time, the results indicated that together with kinetic rate the biosorption capacity of PS-C (21.20mgg−1) was higher than that of PS-V (16.30mgg−1).Mechanical activation like crushing and grinding will change material particle size, specific surface area and porosity, as well as its crystallinity. However, this paper elucidates that such physical structural changes will impact on heavy metal ions removal efficiency. This investigation suggests that the type of size reduction in lignocellulosic biosorbent preparation plays a very important role in overall biosorption performance, so it should be carefully considered every time when the mechanical treatment of material is necessary to be applied.

Energy conversion in phosphate ore grain mixture activated via ultra-centrifugal mill

The aim of this investigation was to establish the optimal processing parameters of the comminuted phosphate grain mixture mechanical treatment by monitoring and evaluating the activated product characteristics. An ultra-centrifugal mill with a peripheral comminuting path was used as activator in the experiment. A mathematical model based on the theoretical principles of the grain mixture mechanical processing was applied in order to characterize the phosphate activation procedure. As the energy conversion that takes place by the interaction mill–material during activation is recorded on the processed phosphate grains, the increase in potential energy of the activated grains was measured by means of an automatic grain counter. Following the operating hypothesis of the automatic grain counter, the energy conversion and the properties of phosphate grains induced by mechanical force were monitored and expressed in the form of the grain inertia change. The phosphate ore grain mixture used in the experiment was thoroughly analyzed, particularly in its activated state. Analytically obtained results were supported by X-ray diffraction analysis for identification of crystalline phases and change in crystallinity, and SEM microphotography of initial and activated phosphate grains. Diverse comparison analyses disclosed that the optimal set of activation process parameters could reduce the negative effect of phosphate sample immanent properties on the final score and furthermore enhance the material reactivity.

Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis

The impact of the mechanical processing parameters on the alumina grain-size distribution affiliated characteristics and on the γ to α phase transformation rate was investigated. The moderation in the alumina samples behavior has been correlated to the granulometric and mineralogical changes induced by activation via an ultra-centrifugal mill. The assessment of the activation process variables influence on the final quality of the product parameters was conveyed in order to optimize the mechanical treatment of the alumina, which otherwise could be regarded as either energetically or economically unsustainable procedure. The Response Surface Method, Standard Score Analysis and Principal Component Analysis were applied as means of the mechanical activation optimization. The r2 values obtained by developed models were in range from 0.816 to 0.988. The established mathematical models were able to precisely predict the quality parameters in a broad range of processing parameters. The Standard Score Analysis emphasized that the optimal output sample was obtained using a sieve mesh of 120μm set of processing parameters (SS=0.96). Diverse comparison analyses disclosed that the optimal set of activation process parameters could reduce the negative effect of γ-alumina samples immanent properties on the final score, and furthermore to enhance the rate of γ to α transition which would improve energetic and economic sustainability of the alumina phase transformation procedure.

Effects of mechanical activation on the parameters of talc quality for ceramics production – Chemometric approach

Talc is broadly used in the ceramic materials industry, either as a basic raw material, or as filler, due to its chemical inertia, fragmentation proneness, thermal stability, and refractoriness. The mechanical activation is frequently employed in the direct enhancement of talc properties, and thereby in the design of talc based composites with advanced performances. The differences in the set of the process parameters measured before and after talc activation via ultra-centrifugal mill Retsch ZM-1, and their influence on the grain-size distribution related characteristics have been investigated. The mechanical treatments are energetically unsustainable procedures, therefore the talc activation was optimized on basis of assessment of the process variables (number of rotor revolutions, current intensity, activation period, circumferential rotor speed and mill capacity) effect on the final quality of product parameters (mesh sizes, cumulative oversizes, average grain size, level of micronization kinetics, mesh size appropriate to 95% micronized product cumulative undersize and specific surface area). The activated product parameters in all experimental sequences were obtained by the analytical procedure based on Rosin-Rammler-Sperling equation. Response surface method, standard score analysis and principal component analysis were used as a means of the optimization. Developed models showed r2 values in the range of 0.714–0.908 and they were able to accurately predict quality parameters in a wide range of process parameters. Standard score analysis highlighted that the optimal sample was obtained using sieve mesh of 120 μm set of processing parameters (SS = 1.0). Multiple comparison tests revealed that the optimal variation in the processing parameters could reduce the negative effect of talc samples inherent properties on the final score and improve the activation procedure energetic and economic sustainability.

Chemometric analysis of the influence of mechanical activation on the mica quality parameters

The differences in the set of the process parameters measured before and after mica mechanical activation and their influence on the grain size distribution related characteristics have been studied. The modification of the behavior for activated samples has been correlated to the particle size distribution effect produced by activation via an ultra centrifugal mill. The mechanical treatments are energetically and economically unsustainable procedures, therefore the mica activation was optimized on basis of assessment of the process variables effect on the final quality of product parameters. Response surface method, standard score analysis and principal component analysis were used as means of the optimization. Developed models showed r2 values in the range of 0.816–0.988 and they were able to accurately predict quality parameters in a wide range of processing parameters. Standard score analysis highlighted that the optimal sample was obtained using sieve mesh of 80μm set of processing parameters (SS=0.81). Multiple comparison tests revealed that the optimal variation in the processing parameters could reduce the negative effect of mica samples inherent properties on the final score and improve activation procedure energetic and economic sustainability.

Mechanically activated coal ash as refractory bauxite shotcrete microfiller: Thermal interactions mechanism investigation

A growing demand for refractory castables with advanced properties has given rise to a continuous technological evolution and highlighted the necessity for secondary raw materials reapplication even in refractory industry. For the experiment, refractory shotcretes with the same matrix composition were prepared from 30wt% of high aluminate cement, 40wt% of bauxite aggregate and 30wt% of chamotte filler. The request for obtaining a low-cement castable is fulfilled by application of mechanically activated coal ash as microfiller in one of the bauxite shotcretes. The fly ash was activated by means of vibratory disc mill and ultra-centrifugal mill, and results were compared. The shotcrete samples were dried at 110°C during 24h to create specimens for investigation of mechanical and thermal properties. The properties have been studied at temperatures ranging from room temperature to adopted maximal temperature 1400°C. At maximal 1400°C, the bauxite shotcretes were mainly composed of anorthite, corundum, mullite and cristobalite. Mechanisms of hydration and sintering were investigated by means of differential thermal analysis (DTA) at three different heating rates. DTA measurements showed different activation energies for ordinary bauxite shotcrete and shotcrete with microfiller. The evolution of the refractory shotcretes properties was investigated and correlated with microstructural changes induced by temperature and microfiller addition. The combination of advantages in investigated refractory shotcretes makes them suitable for use in severe conditions at high temperature applications especially in refractory industries.