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In contemporary society, the growing reliance on electronic devices has necessitated the phasing out of traditional Sn–Pb solder due to its health hazards, prompting a transition to environmentally friendly, lead-free alternatives.This study aims to address the challenges of poor interfacial reliability and high cost associated with eutectic Sn–Ag–Cu solders by investigating the creep properties and service life of a low-silver solder alloy, Sn-0.3Ag-0.7Cu, as a filler material.The creep behavior of Sn-0.3Ag-0.7Cu was analyzed through creep testing, and fracture modes were identified via microstructural and fracture surface analysis.The Anand viscoplastic model was employed to simulate and calibrate the creep behavior, with its accuracy validated via thermal cycling experiments.Furthermore, the creep behavior of Ball Grid Array (BGA) solder joints was simulated using Abaqus software to examine the impact of creep on joint longevity and the influence of temperature on performance.

This study investigates the microstructural evolution, mechanical properties, and fracture morphology of Q235/20# dissimilar steel welded joints subjected to both intermittent and fully tungsten inert gas (TIG) welding processes. The specimens, sized 200 mm × 200 mm × 12 mm, were analyzed using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), electron backscatter diffraction (EBSD), microhardness testing, and tensile testing to compare the effects of the two welding techniques. The results reveal that both welding processes produced well-formed joints with minimal metal spatter at the start, and no significant defects. Microstructural analysis showed that the intermittent welding process resulted in finer and more uniformly distributed grains compared to the fully welded joints. The welded metal predominantly consisted of lath martensite, which grew significantly larger during the second welding pass. The microstructure of the welds and their mechanical properties were found to be well-correlated. A higher lath martensite content was associated with increased microhardness and tensile strength. Under the intermittent welding process, the welded joints exhibited finer and more uniform grain structures, enhancing toughness. The microhardness distributions of both welding processes followed similar trends. In tensile tests, specimens welded using the intermittent process achieved up to 90% of the base metal's performance. The fracture morphology of these specimens was characterized by numerous dimples, indicating ductile fracture behavior. In conclusion, the intermittent TIG welding process yielded a more uniform microstructure and superior performance in Q235/20# dissimilar steel joints compared to the full welding process.

To explore the thermoformability of Mn–Cr–Ni–Co steel for ball mill liner, isothermal compression tests were performed on Mn–Cr–Ni–Co steel using a Gleeble-3800 thermal compressive testing machine. Flow stress curves at 900 °C–1200 °C and 0.01s−1∼10s−1 were obtained. Results show Mn–Cr–Ni–Co steel has obvious positive strain rate sensitivity, with peak stress decreasing with increasing temperature. A constitutive equation for Mn–Cr–Ni–Co steel was established using the Arrhenius model based on strain compensation, and fitted values were compared to experimental values. A hot working map for Mn–Cr–Ni–Co steel was established and analyzed. Hot working process parameters are: deformation temperature of 980∼1200 °C, strain rate of 0.04–1.78s−1, providing a basis for selecting the hot forging process of the ball mill liner. Forging and forming experiments of the ball mill liner were carried out using the optimal parameters of Mn–Cr–Ni–Co steel from the hot working map. The ball mill liner has good forming quality with a relatively uniform martensitic structure inside. Tensile and impact tests were performed on the ball mill liner. Compared to the mechanical properties of traditional cast Mn13 ball mill liners, results show the tensile strength increased by 159.75%, elongation by 18.8%, and impact capacity by about 16.7%.

Abstract Background Mechanical damage to plants triggers local and systemic electrical signals that are eventually decoded into plant defense responses. These responses are constantly affected by other environmental stimuli in nature, for instance, light fluctuation. In recent years, studies on decoding plant electrical signals powered by various machine learning models are increasing in a sense of early prediction or detection of different environmental stresses that threaten plant growth or crop yields. However, the main bottleneck is the low-throughput nature of plant electrical signals, making it challenging to obtain a substantial amount of training data. Consequently, training these models with small datasets often leads to unsatisfactory performance. Results In the present work, we set out to decode wound-induced electrical signals (also termed slow wave potentials, SWPs) from plants that are deprived of light to different extents. Using non-invasive electrophysiology, we separately collected sets of local and distal SWPs from the treated plants. Then, we proposed a workflow based on few-shot learning to automatically identify SWPs. This workflow incorporates data preprocessing, feature extraction, data augmentation and classifier training. We established the integral and the first-order derivative as features for efficiently classifying SWPs. We then proposed an Adversarial Autoencoder (AAE) structure to augment the SWP samples. Combining them, the Random Forest classifier allowed remarkable classification accuracies of 0.99 for both local and systemic SWPs. In addition, in comparison to two other reported methods, our proposed AAE structure enabled better classification results using our tested features and classifiers. Conclusions The results of this study establish new features for efficiently classifying wound-induced electrical signals, which allow for distinguishing dark-affected local and systemic plant wound responses. We also propose a new data augmentation structure to generate virtual plant electrical signals. The methods proposed in this study could be further applied to build models for crop plants using electrical signals as inputs, and also to process other small-scale signals.

6061-T6 aluminum alloy plate (3 × 150 × 300 mm3) was welded by tungsten inert gas (TIG) welding. The welding process methods are single-pass welding process and full welding process respectively. The effects of different welding processes on the performance of TIG welding 6061-T6 aluminum alloy were compared and studied. The effects of microstructure and precipitation on the microhardness and tensile strength were analyzed by optical microscope, scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDS) characterization, electron backscattering diffraction (EBSD) characterization, microhardness and tensile test. The microstructure of the weld zone is mainly composed of aluminum solid solution (α-Al) dendritic structure and Al–Si eutectic structure. Through EBSD characterization analysis, the average grain size of the weld zone of the full welding process and the single-pass welding process is about 45 μm and 55 μm, and the grain size of the heat-affected zone and the weld zone of the two welded joints does not change significantly. The hardness curves of the two welded joints have the same distribution trend, which is roughly 'W' type distribution. In the tensile test, the tensile strength of the single pass welding process is lower than that of the full welding process, and the fracture of the tensile parts is dimple structure, which is ductile fracture. Through analysis and comparative study, the full welding process is better than the single-pass welding process when welding 6061-T6 aluminum alloy sheet.

At cold temperatures, the stress after welding a blast furnace shell is not completely released because of the fast cooling speed, which results in cracks. To solve this problem, an integrated method combining gray relational analysis, back propagation (BP) neural network, and genetic algorithm-BP (GA-BP) was proposed in this study. Its aim was to analyze the dominant mechanism of residual stress in multi-layer and multi-pass welding process under the heating of ceramic sheet and achieve super-objective collaborative optimization of residual stress. GRA indicated that through the correlation analysis of welding parameters, residual stress, maximum temperature of characteristic point, and deformation, welding speed was determined to be an all-important factor affecting welding quality. A BP prediction model of residual stress was established. The predicted value was in good agreement with the experimental value, and the maximum error was 8.75%. The influence of each factor on the quality of welding seam is not a single, but a complex mechanism of mutual influence. GA-BP determined the combination of low level welding speed 28 mm/min, medium level welding current 210A and medium and low level welding voltage 21V as the optimal solution of low residual stress. The maximum prediction error of residual stress was 13.76%. The experimental results show that the maximum prediction error of residual stress is 4.4%, and the optimized weld has better macro and micro structure, which proves the feasibility of the multi-objective optimization method. Most importantly, the proposed method can effectively identify the optimal welding parameters, which can provide a reliable theoretical basis for engineering practice.

Abstract Background Predicting relationships between plant functional traits and environmental effects in their habitats is a central issue in terms of classic ecological theories. Yet, only weak correlation with functional trait composition of local plant communities may occur, implying that some essential information might be ignored. In this study, to address this uncertainty, the objective of the study is to test whether and how the consistency of trait relationships occurs by analyzing broad variation in eight traits related to leaf morphological structure, nutrition status and physiological activity, within a large number of plant species in two distinctive but comparable harsh habitats (high-cold alpine fir forest vs. north-cold boreal coniferous forest). Results The contrasting and/or consistent relationships between leaf functional traits in the two distinctive climate regions were observed. Higher specific leaf area, photosynthetic rate, and photosynthetic nitrogen use efficiency (PNUE) with lower N concentration occurred in north-cold boreal forest rather than in high-cold alpine forest, indicating the acquisitive vs. conservative resource utilizing strategies in both habitats. The principal component analysis illuminated the divergent distributions of herb and xylophyta groups at both sites. Herbs tend to have a resource acquisition strategy, particularly in boreal forest. The structural equation modeling revealed that leaf density had an indirect effect on PNUE, primarily mediated by leaf structure and photosynthesis. Most of the traits were strongly correlated with each other, highlighting the coordination and/or trade-offs. Conclusions We can conclude that the variations in leaf functional traits in north-cold boreal forest were largely distributed in the resource-acquisitive strategy spectrum, a quick investment-return behavior; while those in the high-cold alpine forest tended to be mainly placed at the resource-conservative strategy end. The habitat specificity for the relationships between key functional traits could be a critical determinant of local plant communities. Therefore, elucidating plant economic spectrum derived from variation in major functional traits can provide a fundamental insight into how plants cope with ecological adaptation and evolutionary strategies under environmental changes, particularly in these specific habitats.

Aluminum alloy has the characteristics of light weight, high strength, corrosion resistance, easy forming, etc., and is widely used in manufacturing industry. The extrusion speed of aluminum alloy rim is not uniform, which affects the mechanical properties of the product. In order to solve these 1problems, the finite element analysis model of hot extrusion of aluminum alloy profiles was established in HyperXtrude software. The influences of different bar diameters, hot extrusion velocity, bar preheating temperature, die temperature and extrusion cylinder temperature on velocity difference and maximum extrusion pressure at the exit were analyzed. The results show that the designed hot extrusion rim die meets the requirements of strength and deformation, and the best extrusion process parameters of 7075 aluminum alloy rim profiles in improving profile quality and reducing energy consumption are obtained by Taguchi test gray correlation method.

Abstract Spectrum matching is the most common method for compound identification in mass spectrometry (MS). However, some challenges limit its efficiency, including the coverage of spectral libraries, the accuracy, and the speed of matching. In this study, a million-scale in-silico EI-MS library is established. Furthermore, an ultra-fast and accurate spectrum matching (FastEI) method is proposed to substantially improve accuracy using Word2vec spectral embedding and boost the speed using the hierarchical navigable small-world graph (HNSW). It achieves 80.4% recall@10 accuracy (88.3% with 5 Da mass filter) with a speedup of two orders of magnitude compared with the weighted cosine similarity method (WCS). When FastEI is applied to identify the molecules beyond NIST 2017 library, it achieves 50% recall@1 accuracy. FastEI is packaged as a standalone and user-friendly software for common users with limited computational backgrounds. Overall, FastEI combined with a million-scale in-silico library facilitates compound identification as an accurate and ultra-fast tool.

Conjunction gears, which are also known as helical gears with clutch gears, are used mainly in the transmission and shift design of automobile gearboxes. In this paper, focusing on the hot forging process and microstructure changes after forging, hot forging is proposed for manufacturing a conjunction gear according to the characteristics of a combination gear. Combined with finite element numerical simulation, by comparing changes in temperature, equivalent stress, equivalent strain, recrystallization fraction, and average grain size, the effect of the optimization of the forging process of a combined tooth billet is achieved using the response surface methodology. Finally, optimal forging process parameters are obtained through experimental research, and the quenched structure after hot forging is observed.

Based on the Gurson-Tvergaard-Needleman (GTN) damage model, the damage evolution and ductile fracture of 7075 aluminum alloy sheets during the tensile process were predicted. First, the true stress–strain curve and micro morphology of 7075 aluminum alloy at 310 °C∼460 °C were obtained using ultra-high temperature confocal microscope with tensile and compression functions, and the damage characteristics of the fracture position of the tensile specimen were observed by Scanning Electron Microscope (SEM). Then, using the finite element reverse calibration method, the identification method of GTN damage parameters under high temperature was systematically explained and the damage characteristic parameters of 7075 aluminum alloy under high temperature (310 °C∼460 °C) were obtained. The influence of fluctuations in damage parameters on the macroscopic mechanical behavior of materials and the influence of temperature on the value of material damage variables were analyzed. Finally, the void volume fraction of 7075 aluminum alloy at 360 °C was obtained by microscopic observation and compared with the void volume fraction obtained by the finite element reverse calibration method. The results show that the effect of temperature on void volume fraction is basically the same as that of plasticity. The change of void volume fraction has a greater impact on the mechanical properties of the material. There is a small gap between the void volume fraction obtained using the microscopic observation method and the void volume fraction obtained using the finite element reverse calibration method, which verifies the accuracy of the finite element reverse calibration method.

Taste determination in small molecules is critical in food chemistry but traditional experimental methods can be time-consuming. Consequently, computational techniques have emerged as valuable tools for this task. In this study, we explore taste prediction using various molecular feature representations and assess the performance of different machine learning algorithms on a dataset comprising 2601 molecules. The results reveal that GNN-based models outperform other approaches in taste prediction. Moreover, consensus models that combine diverse molecular representations demonstrate improved performance. Among these, the molecular fingerprints + GNN consensus model emerges as the top performer, highlighting the complementary strengths of GNNs and molecular fingerprints. These findings have significant implications for food chemistry research and related fields. By leveraging these computational approaches, taste prediction can be expedited, leading to advancements in understanding the relationship between molecular structure and taste perception in various food components and related compounds.

The high-temperature deformation process and dynamic recrystallization (DRX) process of 21-4N were investigated under the conditions of the deformation temperature range of 1273~1453K, the strain rate range of 0.01~10s–1 and the deformation degree of 60% (the total deformation is 0.916) by using Gleeble-1500D thermal simulated test machine. The curves of stress-strain (σ – ε) were obtained, and the curves of work hardening rate (θ) and strain (ε) were obtained by taking derivative of σ – ε. The DRX critical strains under different conditions were determined by the curves of work hardening rate (θ – ε), and the DRX critical strain model was established. The peak strains of 21-4N were obtained by the curves of σ – ε, the relationship between peak stress (σp) and critical strain (εc) was determined, and the peak strain model was established. The DRX volume fraction models of 21-4N were established by using Avrami equation. The DRX grain size of 21-4N was calculated by Image Pro Plus 6.0, and its DRX grain size models were established.

The Gleeble-1500D thermal simulator was used for the isothermal compression test of 21-4N heat-resistant steel under the T range of 1273–1453 K and ε˙ of 0.01–10s−1. Using the obtained stress - strain data, various parameters of the Fields–Backofen (F-B), the modified F–B (m–F–B) equations and the modified Zerilli–Armstrong (m–Z–A) equations were calculated respectively. The constitutive equations of 21-4N heat-resistant steel based on the F–B, the m–F–B and the m–Z–A were established. Second, the predictive ability of the three constitutive equations were evaluated using the correlation coefficient (R), average absolute relative error (AARE) and the relative error (r). Third, the established model was imported into Deform-3D to simulate the valve forging process of 21-4N heat-resistant steel, and the distribution rules of the effective stress, effective strain, temperature and damage condition of the forging were analyzed. Finally, a hot forging experiment was performed on a 160t hot die forging press. Results show that the flow stress of 21-4N heat resistant steel is affected by temperature, strain rate and strain. The m–F–B and m–Z–A models can describe the rheological behavior of 21-4N heat-resistant steel, while the original F–B model has a high predictive ability, but only under low temperature, low strain rate and small deformation. The simulation process can be completed successfully, indicating that the established models can be used for the simulation study of the thermal deformation of 21-4N heat-resistant steel and all models are correct. The results can provide some important basic data for the simulation of 21-4N heat resistant steel in the plastic deformation process.

42CrMo steel belongs to low-alloy medium carbon steel and also belongs to ultra-high-strength steel. In this study, thermal compression tests (800°C - 1200°C, 0.01s-1 - 10s-1) and subsequent calculations proved that many material constants of 42CrMo alloy steel have a similar functional relationship with Z parameter: Material constants = a*Zb. The thermal processing maps under strains of 0.2, 0.4, 0.6 and 0.8 were established, and the practical application of the processing maps was verified in combination with metallographic diagram analysis. The optimum thermal processing parameters range of the material was obtained: the temperature range of 1000°C - 1125°C and the strain rate range of 3.16 s-1 - 10s-1.The dynamic recrystallization volume fraction model and grain size model of the material were established, and the typical sigmodal curve was obtained. The hot workability and recrystallization behavior of 42CrMo were further analyzed.

The dynamic recrystallization (DRX) behavior and microstructure evolution of 33Cr23Ni8Mn3N heat-resistant steel were studied by isothermal hot compression experiment within the temperature range of 1000 °C–1180 °C and strain rate of 0.01–10 s−1. Models for the DRX volume fraction and grain size of 33Cr23Ni8Mn3N heat-resistant steel were established, and comparison results showed high consistency for the predicted data from the models and those from scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The model was imported into Deform-3D, and hot compression was simulated by the finite element method (FEM). The simulation and experimental results were highly consistent. Thus, the established DRX model is an important reference for the microstructure evolution in 33Cr23Ni8Mn3N hot deformation behavior.

The stress intensity factor is an important parameter to study the fracture problem. The occurrence and development of gear cracks can be measured and controlled， which is of great significance for studying the fatigue damage of cracks and predicting life. In order to study the variation law of three-dimensional crack stress intensity factor of spur gears， a three-dimensional finite element model with initial semi-elliptical cracks is established by Abaqus software. The stress intensity factor of the semi-elliptical crack front is calculated， and the influence of crack size， shape and load variation on the stress intensity factor at the leading edge is analyzed. The results show that the cracks of the roots of the teeth mainly manifested as open cracks during the expansion process. As the load increases， stress intensity factor KI also increases， but its distribution rules remain unchanged. With constant load， KI increases with the increase of crack size. In the establishment of semi-elliptical cracks， as the long axis increases， the KI fluctuations on the crack front gradually become smaller.

Cross wedge rolling has the advantages of high production efficiency, good product quality, high material utilization, environmental protection, and low cost. It is one of the best processing methods for producing shaft blanks. In this paper, a cross wedge rolling die of TC4 titanium alloy is studied. Based on the Archard wear model, a modified model suitable for cross wedge rolling die wear analysis is derived through finite element simulation. Then, the modified Archard wear model is imported into Deform-3D software for finite element analysis. Orthogonal experimental design is used to combine and analyze different process parameters. Finally, the beetle antennae search (BAS)-genetic algorithm (GA)-back propagation neural network (BPNN) algorithm is used to predict the degree of die wear and to optimize the simulation parameters, which can acquire the process parameters that have the least impact on die wear. The results show that the wear distributions of cross wedge rolling tools is uneven. In general, the most serious areas are basically concentrated in the wedge-shaped inclined plane and rectangular edge lines. The reason is that the tangential force and radial force received by the die are relatively large, which leads to increased wear. Moreover, the temperature change is most severe on the wedge-shaped ridge line. When in contact with the workpiece, the temperature rises sharply, which makes the local temperature rise, the mold hardness decrease, and the wear accelerate. Through response surface method (RSM) analysis, it is concluded that the deformation temperature is the main factor affecting wear depth, followed by the forming angle, and that there is an interaction between the two factors. Finally, the feasibility of the BAS-GA-BP algorithm for optimizing the wear behavior of dies is verified, which provides a new process parameter optimization method for the problem of die wear in the cross wedge rolling process.

In order to more accurately predict the plastic flow behavior of 33Cr23Ni8Mn3N heat-resistant steel, it provides a good foundation for numerical simulation. The selection of constitutive models is crucial. The Gleeble-1500D thermal simulation tester was used to perform thermal compression experiments on 33Cr23Ni8Mn3N heat-resistant steel under different deformation conditions. Based on the experimental data, the Johnson-Cook (JC), Fields-Backofen (FB) constitutive models and their modified constitutive models are established and compared. The characteristics of JC model, FB model, modified JC (m-JC) model, modified FB (m-FB) model and strain-compensated Arrhenius (strain-compensated Arr) model are demonstrated. It is determined that the strain-compensated Arr model has the best accuracy for predicting the thermal deformation behavior of 33Cr23Ni8Mn3N heat-resistant steel. In addition, finite element development was carried out and programming was performed using Absoft Pro Fortran 8.0 software. Various modified models are embedded in Deform-3D for numerical simulation comparison. The results of numerical simulation show that the strain-compensated Arr model is more suitable for finite element simulation of 33Cr23Ni8Mn3N heat-resistant steel. Keywords: 33Cr23Ni8Mn3N, Johnson-Cookmodel, Thermal deformation, Constitutive equation, Fields-Backofen model

A superhydrophobic surface with robust structures on a metallic surface could improve its application in various harsh conditions. Herein, we developed a new strategy to fabricate robust micro-/nanoscale hierarchical structures with electrical discharge machining and electrochemical etching on a titanium substrate. After modification by fluorinated silane, the static water contact angle and slide angle of the surface could reach 162 ± 2° and 4 ± 1°, respectively. The superhydrophobic surfaces showed good corrosion resistance and mechanical stability after scratching with sandpapers. In addition, the superhydrophobic surfaces had good self-cleaning performance even in an acidic environment as well as the potential to be used as guiding tracks in droplet microfluidics and lab-on-a-chip systems. These results are expected to be helpful in designing the surface of liquid float gyroscope parts.

The stress-strain curves of TA15 titanium alloy at 750 ∼ 950 °C and 0.001 ∼ 1 s ^−1 were obtained by hot compression with Gleeble-1500D. Based on the compression experimental data of TA15 titanium alloy, the Johnson-Cook high temperature thermal deformation constitutive equation was established. By calculating the constitutive equation, the flow stress was compared with the measured stress-strain curve, and the accuracy of the equation was verified. Then, based on the theory of hot processing map of dynamic materials, the hot processing map is drawn when the strain is 0.1, 0.2, 0.3, 0.4, 0.5 and 0.6. The reasonable range of hot processing map of TA15 titanium alloy was determined. When the temperature is between 750 °C–875 °C, the power dissipation factor decreases with increasing strain rate. The maximum power dissipation is distributed between 825 °C–950 °C. This indicates that recrystallization occurred within this range. The safe zone is mainly concentrated in the temperature range of 885 °C–950 °C, the strain rate is less than 0.1 s ^−1 . It can be seen that instability does not occur in the high temperature and low strain region. Therefore, at 885 ≤ T ≤ 950 °C, 0.001 ≤ $\dot{\varepsilon }$ ≤ 0.1 s ^−1 or 800 ≤ T ≤ 875 °C, 0.001 ≤ $\dot{\varepsilon }$ ≤ 0.002 s ^−1 , it is reasonable to perform high temperature deformation on TA15 titanium alloy.

Titanium alloy possesses high strength, good corrosion resistance, and high heat resistance; thus, it is widely used in the aerospace and other fields. Blades of titanium alloy are important components of aero-engines and are essential to the engines operation. In this work, a Ti-6Al-4V blade was formed by cross wedge rolling (CWR) to realize the near net-shape of an aero-engine blade. First, thermal simulation experiments of Ti-6Al-4V were carried out to obtain the thermal deformation constitutive equation of the alloy. The finite element software Deform-3D was then used to simulate the thermodynamic coupling of the forming process, and the metal flow, temperature, and stress⁻strain distribution laws during the forming process were analyzed. Finally, experimental verification of the Ti-6Al-4V blade was carried out by using an H500 CWR mill. The results revealed the feasibility of applying CWR to preform Ti-6Al-4V blades.

Valve microstructure is important during hot forging. Austenitic 21-4N steel is often used in exhaust valves. In this study, the microstructure evolution of the forging valve process was predicted using the internal state variables (i.e., average grain size, recrystallized fraction, and dislocation density) modus for 21-4N. First, 21-4N was subjected to hot compression tests on a Gleeble-1500D and static grain growth tests in a heating furnace. A set of uniform viscoplastic constitutive equations was established based on experimental data. Next, the determined unified constitutive equations were conducted in DEFORM-3D, and the microstructure evolution of 21-4N during forging was calculated. Finally, the simulation results of grain size evolution were validated via experiments. Results showed good consistency between the simulations and experiments. Thus, the models adequately predicted the microstructure evolution.

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The fifth wheel is a connecting device between the semi-trailer and the tractor, which plays the role of connecting and steering. According to the finite element analysis technology, the fifth wheel model is established by CREO software, and import the established model into Hyper-Works software, the static analysis and lightweight design of the structure are carried out by finite element simulation. Finally, the optimal solution of fifth wheel structure is obtained, the static performance of the optimized fifth wheel is verified, which proves that the optimized structure is reasonable and meets the requirements of strength and stiffness. After the optimization of fifth wheel for actual production test, the optimized fifth wheel to meet the requirements of national standards. [ABSTRACT FROM AUTHOR]

Copyright of Materials & Technologies / Materiali in Tehnologije is the property of Institute of Metals & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Materials & Technologies / Materiali in Tehnologije is the property of Institute of Metals & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Materials & Technologies / Materiali in Tehnologije is the property of Institute of Metals & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background High-fat diets (HFD) are known to enhance feed conversion ratio in broiler chickens, yet they can also result in hepatic fat accumulation. Bile acids (BAs) and gut microbiota also play key roles in the formation of fatty liver. In this study, our objective was to elucidate the mechanisms through which BA supplementation reduces hepatic fat deposition in broiler chickens, with a focus on the involvement of gut microbiota and liver BA composition. Results Newly hatched broiler chickens were allocated to either a low-fat diet (LFD) or HFD, supplemented with or without BAs, and subsequently assessed their impacts on gut microbiota, hepatic lipid metabolism, and hepatic BA composition. Our findings showed that BA supplementation significantly reduced plasma and liver tissue triglyceride (TG) levels in 42-day-old broiler chickens (P