Search Results (101)

Laser powder bed fusion (LPBF) of high-strength aluminum alloy 7075 (AA7075) is severely limited by hot cracking. However, the underlying mechanisms, particularly the coupling between thermal fields, solidification microstructure, and cracking behavior, remain insufficiently clarified. This study elucidates these mechanisms by integrating experimental characterization with thermal simulation to investigate the temperature field, microstructure, and cracking relationships in both AA7075 and a crack-resistant 7075-Er-Zr alloy. Results show that coarse hot crack morphology is highly dependent on linear energy density E_L. In AA7075, E_L < 450 J/m promotes laterally inclined cracks (short, narrow cracks extending from the melt pool boundary toward the track center), whereas E_L higher than that value leads to the continuous centerline cracks (long, wide cracks along the track center). Fine microcracks are also observed at melt pool boundaries. The 7075-Er-Zr alloy demonstrates superior crack resistance. At E_L = 600 J/m, longitudinal centerline cracks still penetrate along the track, but the alloy achieves crack-free tracks at 200 W with scanning speeds above 1000 mm/s, otherwise exhibiting only short discontinuous cracks. Microcracks at melt pool boundaries are markedly suppressed in the modified alloy. The enhanced crack resistance is attributed to Er/Zr-induced grain refinement and a transition to an equiaxed grain structure, which disrupts intergranular gaps. Critically, thermal simulations identify an annular region with a peak temperature gradient. In AA7075, this region develops aligned columnar grains that facilitate both microcracks and centerline cracks. In the 7075-Er-Zr alloy, microcracks are fully eliminated within this region. However, a residual crystallographic texture persists in the annular region, which promotes the continued occurrence of centerline cracks under high energy density (e.g., E_L = 600 J/m). The annular region remains a critical weak link, and its microstructural control determines the prevailing crack type. This work provides a fundamental understanding of the thermal-microstructural origins of cracking and offers a theoretical foundation for developing crack-resistant aluminum alloys via LPBF. Full article

Background: Osteocalcin is a bone-derived protein traditionally regarded as a marker of bone formation, but experimental and clinical studies have suggested potential endocrine effects on energy and glucose metabolism. In pediatric populations, particularly in the context of obesity, the relationships between circulating osteocalcin, adiposity, and metabolic health remain inconsistent and poorly defined. Objective: To investigate associations between serum total osteocalcin and anthropometric, metabolic, biochemical, and body composition parameters in children and adolescents with obesity, with particular emphasis on adiposity and mineral metabolism. Methods: This retrospective cross-sectional study included 155 children and adolescents aged 4–18 years with obesity. Anthropometric measurements, laboratory parameters, and body composition assessed by dual-energy X-ray absorptiometry were extracted from medical records. Associations between osteocalcin z-scores and clinical variables were evaluated using linear regression models. Multivariable and extended regression models were applied to assess independent associations. Results: Osteocalcin was positively associated with markers of mineral metabolism, including serum 25-hydroxyvitamin D₃ (β = 0.19, p = 0.012), serum calcium (β = 0.19, p = 0.015), and free triiodothyronine (β = 0.32, p < 0.001) in multivariable analyses. No independent associations were observed between osteocalcin and measures of adiposity, including body mass index, visceral adipose tissue index, leptin, or markers of glucose and lipid metabolism. Conclusions: In children and adolescents with obesity, circulating osteocalcin is primarily associated with mineral metabolism rather than adiposity or metabolic health. These findings support the interpretation of total osteocalcin as a clinically accessible marker of bone turnover and mineral homeostasis rather than a robust surrogate of metabolic dysfunction in pediatric obesity. Full article

Background/Objectives: This secondary and exploratory meta-analysis re-evaluated 30 randomized controlled trials on free and added sugars (FS) detailed in the European Food Safety Authority’s (EFSA) report on the tolerable upper intake level for dietary sugars, focusing on the influence of food source (beverages, foods, or mixed) on cardiometabolic and anthropometric health. Methods: The EFSA’s method of analyzing the relative FS intake (difference between treatment and comparator arms, Δ%E^fs) was used, with further adjustment for the reported intake of all sources of FS and energy. The EFSA’s “high vs. low” random-effects meta-analysis comparing groups with the highest and lowest FS intake was replicated, and additional exploratory dose–response meta-regressions (linear and non-linear) were performed, stratified by food source. Given the secondary and observational nature of the analysis, all source-stratified findings should be interpreted as hypothesis-generating, rather than causal. Results: There were no interactions between Δ%E^fs and food source for any outcome, and within a source there were linearly positive and statistically significant regressions for body weight (mixed), low-density lipoprotein cholesterol (LDL-C, foods), and uric acid (beverages). Across 13 outcomes, Δ%E^fs was positively and linearly related to greater fasting glucose, high-density lipoprotein cholesterol (HDL-C), and LDL-C, and non-linearly to body weight. However, the data were limited in their representation of FS intake at typical population levels, and there were insufficient data to investigate the effect of FS from foods on most anthropometric outcomes. Conclusions: Meta-regressive dose–responses revealed little relationship between Δ%E^fs from specific food sources and health outcomes, but such effects might be masked by confounding factors. Future trials that test realistic intakes of FS across diverse food matrices and account for dietary compensation would help to overcome limitations in the body of evidence. Full article

Functionally graded AA2024/B₄C metal matrix composites were fabricated via mechanical alloying and hot pressing to investigate structure–property–radiation shielding relationships. Single-layer, two-layer, and three-layer architectures with varying B₄C contents were systematically produced. Microstructural homogeneity and phase constitution were examined using SEM/EDS and XRD, while thermal stability was evaluated by thermogravimetric analysis. Density and porosity measurements were conducted to assess the influence of reinforcement distribution and functional grading on densification behavior. Gamma radiation shielding performance was experimentally evaluated using a ¹⁵²Eu source and an HPGe detector over a wide photon energy range. Key shielding parameters, including linear and mass attenuation coefficients, half-value layer, tenth-value layer, mean free path, and radiation protection efficiency, were determined. The results reveal that functional grading significantly enhances radiation attenuation compared to monolithic composites. The three-layer AA2024/B₄C composite exhibited the highest attenuation coefficients and the lowest HVL, TVL, and MFP values at all investigated energies, achieving nearly 100% improvement in shielding efficiency relative to unreinforced AA2024. These findings demonstrate that controlled B₄C distribution and layered composite architecture provide a synergistic improvement in thermal stability, physical integrity, and radiation shielding performance, positioning functionally graded AA2024/B₄C composites as efficient lightweight materials for advanced radiation shielding applications. These results indicate that the developed functionally graded AA2024/B₄C composites are promising candidates for advanced radiation shielding applications in nuclear facilities, aerospace structures, and medical radiation protection systems, where lightweight and high-performance materials are critically required. Full article

Based on first-principles calculations and linear-response time-dependent density functional theory within the random phase approximation (LR-TDDFT-RPA), this work systematically investigates the modulation of Dirac plasmons in germanene via carrier doping, biaxial strain, and substrate effects. The results demonstrate that carrier doping induces highly tunable Dirac plasmons whose excitation energy follows the ω ∝ n^1/4 scaling relation, leading to a sublinear increase with doping concentration. Furthermore, biaxial strain effectively modulates the Fermi velocity, and the established ω ∝ √V_F relationship directly explains the observed linear tuning of plasmon energy with strain. More importantly, the combined modulation of carrier density and strain enables a significantly broader plasmon energy range (0.16–0.61 eV) than achievable through individual parameter control. When supported on hBN substrates, germanene maintains the characteristic √q plasmon dispersion despite band hybridization and a redshift in energy, a behavior well explained by the 2D free electron gas model. This study provides important theoretical insights into the multi-parameter control of Dirac plasmons and supports the design of germanene-based tunable nanophotonic devices. Full article

Background: Anaplastic lymphoma kinase (ALK) is a validated oncogenic driver in non-small cell lung cancer and other malignancies, making it a clinically relevant target for small-molecule inhibition. Methods: Here, we report a computational discovery pipeline integrating structure-based virtual screening, machine learning-guided prioritization, molecular dynamics simulations, and binding free energy analysis to identify potential ALK inhibitors from a natural product-derived subset of the ZINC20 database. We trained and benchmarked eleven machine learning models, including tree-based, kernel-based, linear, and neural architectures, on curated bioactivity datasets of ALK inhibitors to capture nuanced structure-activity relationships and prioritize candidates beyond conventional docking metrics. Results: Six compounds were shortlisted based on binding affinity, solubility, bioavailability, and synthetic accessibility. Molecular dynamics simulations over 100 ns revealed stable ligand engagement, with limited conformational fluctuations and consistent retention of the protein’s structural integrity. Key catalytic residues, including GLU105, MET107, and ASP178, displayed minimal fluctuation, while hydrogen bonding and residue interaction analyses confirmed persistent engagement across all ligand-bound complexes. Binding free energy estimates identified ZINC3870414 and ZINC8214398 as top-performing candidates, with ΔG_total values of –46.02 and –46.18 kcal/mol, respectively. Principal component and dynamic network analyses indicated that these compounds restrict conformational sampling and reorganize residue communication pathways, consistent with functional inhibition. Conclusions: These results highlight ZINC3870414 and ZINC8214398 as promising scaffolds for further optimization and support the utility of integrating machine learning with dynamic and network-based metrics in early-stage kinase inhibitor discovery. Full article

In order to explore the essence of the anticoccidiosis of anticoccidial drugs under bioelectric currents, the intermolecular double-proton transfer and conformational transformation of 4-pyridone-3-carboxylic acid were investigated by quantum chemistry calculations (at the M06-2X/6-311++G**, M06-2X/aug-cc-pVTZ and CCSD(T)/aug-cc-pVTZ levels) and finite temperature string (FTS) under external electric fields. The solvent effect of H₂O on the double-proton transfer was evaluated by the integral equation formalism polarized continuum model. The results indicate that the influences of the external electric fields along the direction of the dipole moment on double-proton transfer are significant. The corresponding products are controlled by the direction of the external electric field. Due to the first-order Stark effect, some good linear relationships form between the changes of the structures, atoms in molecules (AIMs) results, surface electrostatic potentials, barriers of the transition state, and the external electric field strengths. From the gas to solvent phase, the barrier heights increased. The spatial order parameters (ϕ, ψ) of the conformational transformation could be quickly converged through the umbrella sampling and parameter averaging, and thus the free-energy landscape for the conformational transformation was obtained. Under the external electric field, there is competition between the double-proton transfer and conformational transformation. The external electric field greatly affects the cooperativity transfer, while it has little effect on the conformational transformation. This study is helpful in the selection and updating of anticoccidial drugs. Full article

In the realm of click-type reactions and their application to bioorthogonal chemistry in living organisms, metal-free [3+2] cycloadditions involving mesoionic rings and strained cycloalkynes have gained increasing attention and potentiality in recent years. While there has been a significant accretion of experimental data, biological assays, and assessments of reaction mechanisms, some pieces of the tale are still missing. For instance, which structural and/or stereoelectronic effects are actually interlocked and which remain unplugged. With the advent of data-driven methods, including machine learning simulations, quantitative estimations of relevant observables and their correlations will explore better the chemical space of these transformations. Here we unveil a series of linear relationships, such as Hammett-type correlations, as well as deviations of linearity, using the case study of phenylsydnone (and its 4-aryl-substituted derivatives) with a highly reactive bicyclo[6.1.0]nonyne carbinol. Through accurate estimation of activation barriers and prediction of rate constants, our findings further increase the significance of integrating strain release and electronic effects in organic reactivity. Moreover, such results could pave the way to use mesoionics cycloadditions as probes for measuring the extent of delocalization-assisted strain release, which can be applied to related reactions involving dipoles and strained rings. Full article

This work is a continuation of our recent work on the prediction of hydrogen-bonding (HB) interaction enthalpies. In the present work, a simple method is proposed for the prediction of the HB interaction free energies. Quantum chemical (QC) calculations are combined with the Linear Solvation Energy Relationship (LSER) approach for the determination of novel QC-LSER molecular descriptors and the development of the method. Each hydrogen-bonded molecule is characterized by an acidity or proton donor capacity, ${\alpha }_G$, and/or a basicity or proton acceptor capacity, ${\beta }_G$. These descriptors suffice for the prediction of HB interaction free energy when the interacting molecules possess one acidic and or one basic site. In this case of two interacting molecules, 1 and 2, their overall HB interaction free energy is $c\left({\alpha }_{G1}{\beta }_{G2}+{\beta }_{G1}{\alpha }_{G2}\right)$, where c is a universal constant equal to (ln10)RT = 5.71 kJ/mol at 25 °C. This holds true over the full composition range, that is, regardless of which molecule is solute and which solvent. In the case of complex multi-sited molecules possessing more than one distant acidic site and/or more than one type of distant basic sites, two sets of ${\alpha }_G$ and ${\beta }_G$ descriptors are needed, one for the molecule as solute in any solvent and one for the same molecule as the solvent of any solute. Descriptors ${\alpha }_G$ and ${\beta }_G$ are reported for a number of common hydrogen-bonded molecules but they may be obtained for any other hydrogen-bonded molecule of interest from its molecular surface charge distribution already available or easily obtained via relatively cheap DFT/basis-set QC calculations. The new predictive scheme is validated against corresponding estimations of the widely used Abraham’s LSER model. The developments in the present work and the previous one are useful for solvation studies in chemical and biochemical systems and, particularly, for equation-of-state developments in molecular thermodynamics. The strengths and limitations of the new predictive method are critically discussed. Full article

Accurate estimation of the state of energy (SOE) in lithium-ion batteries is crucial for determining the output power and driving range of electric vehicles. However, in series-connected battery packs, inconsistencies among individual cells pose significant challenges for precise SOE estimation. This issue is particularly pronounced for lithium iron phosphate (LFP) batteries. Their relatively flat open-circuit voltage (OCV) curve makes the classic method of directly weighting the SOE of representative cells—commonly used for ternary batteries—ineffective. This is because the traditional method relies heavily on a linear relationship between the SOE and the voltage, which is not present in LFP batteries. To address this challenge, a novel SOE estimation approach based on the online construction of the battery pack’s comprehensive OCV curve is proposed in this paper. In this new approach, the weighting of representative cells shifts from a result-oriented mode to a key-parameter-oriented mode. By adopting this mode, the whole pack’s comprehensive OCV can be obtained training free and the pack’s SOE can be estimated online within an equivalent circuit model framework. The experimental results demonstrate that the proposed method effectively controls the SOE estimation error within 3% for series battery packs composed of cells with varying degrees of aging. Full article

Identifying efficient and physically meaningful descriptors is crucial for the rational design of hydrogen evolution reaction (HER) catalysts. In this study, we systematically investigate the HER activity of transition metal dichalcogenide (TMD) monolayers by combining density functional theory (DFT) calculations and machine learning techniques. By exploring the relationship between key electronic properties, including the conduction band minimum (CBM), p_z band center, and hydrogen adsorption free energy (ΔG_*H), we establish a strong linear correlation between the CBM and ΔG_*H, identifying the CBM as a reliable and physically meaningful descriptor for HER activity. Furthermore, this correlation is validated in vacancy-defected TMD systems, demonstrating that the CBM remains an effective descriptor even in the presence of structural defects. To enable the rapid and accurate prediction of the CBM, we develop an interpretable three-dimensional model using the Sure Independence Screening and Sparsifying Operator (SISSO) algorithm. The SISSO model achieves a high predictive accuracy, with correlation coefficients (r) and coefficients of determination (R²) reaching 0.98 and 0.97 in the training and 0.99 and 0.99 in the validation tests, respectively. This study provides an efficient computational framework that combines first-principles calculations and machine learning to accelerate the screening and design of high-performance TMD-based HER catalysts. Full article

Under the strategy of Healthy China, students’ physical health status not only affects their future life and studies but also influences social progress and development. By monitoring and measuring the daily PA levels of Chinese students over a week, this study aimed to fully understand the current PA status of students at different times, providing data support for improving students’ PA levels and physical health. (1) Wearable fitness trackers have advantages such as low cost, portable wearability, and intuitive test data. By exploring the differences between wearable devices and PA testing instruments, this study provides reference data to improve the accuracy of wearable devices and promote the use of fitness trackers instead of triaxial accelerometers, thereby advancing scientific research on PA and the development of mass fitness. A total of 261 students (147 males; 114 females) were randomly selected and wore both the Actigraph GT3X+ triaxial accelerometer and Huawei smart fitness trackers simultaneously to monitor their daily PA levels, energy metabolism, sedentary behavior, and step counts from the trackers over a week. The students’ PA status and living habits were also understood through literature reviews and questionnaire surveys. The validity of the smart fitness trackers was quantitatively analyzed using ActiLife software 6 Data Analysis Software and traditional analysis methods such as MedCal. Paired sample Wilcoxon signed-rank tests and mean absolute error ratio tests were used to assess the validity of the smart fitness trackers relative to the Actigraph GT3X+ triaxial accelerometer. A linear regression model was established to predict the step counts of the Actigraph GT3X+ triaxial accelerometer based on the step counts from the smart fitness trackers, aiming to improve the accuracy of human motion measurement by smart fitness trackers. There were significant differences in moderate-to-high-intensity PA time, energy expenditure, metabolic equivalents, and step counts between males and females (p < 0.01), with females having higher values than males in both moderate-to-high-intensity PA time and step counts. Sedentary behavior showed significant differences only on weekdays between males and females (p < 0.05), with females engaging in less sedentary behavior than males. (2) There was a significant difference in sedentary time between weekdays and weekends for students (p < 0.05), with sedentary time being higher on weekends than on weekdays. (3) Compared with weekends, female students had significantly different moderate-to-high-intensity PA time and sedentary time on weekdays (p < 0.01), while no significant differences were observed for male students. (4) Under free-living conditions, the average daily step count monitored by the smart fitness trackers was lower than that measured by the Actigraph GT3X+ triaxial accelerometer, with a significant difference (p < 0.01), but both showed a positive correlation (r = 0.727). (5) The linear regression equation established between the step counts monitored by the smart fitness trackers and those by the Actigraph GT3X+ triaxial accelerometer was y = 3677.3157 + 0.6069x. The equation’s R² = 0.625, with an F-test value of p < 0.001, indicating a high degree of fit between the step counts recorded by the Huawei fitness tracker and those recorded by the triaxial accelerometer. The t-test results for the regression coefficient and constant term were t = 26.4410 and p < 0.01, suggesting that both were meaningful. The tested students were able to meet the recommended total amount of moderate-intensity PA for 150 min per week or high-intensity PA for 75 min per week according to the “Chinese Adult PA Guidelines”, as well as the recommended daily step count of more than 6000 steps per day according to the “Chinese Dietary Guidelines”. (2) Female students had significantly more moderate-to-high-intensity PA time than male students, but lower energy expenditure and metabolic equivalents, which may have been related to their lifestyle and types of exercise. On weekends, female students significantly increased their moderate-to-high-intensity PA time compared with males but also showed increased sedentary time exceeding that of males; further investigation is needed to understand the reasons behind these findings. (3) The step counts monitored by the Huawei smart fitness trackers correlated with those measured by the Actigraph GT3X+ triaxial accelerometer, but the step counts from the fitness trackers were lower, indicating that the fitness trackers underestimated PA levels. (4) There was a linear relationship between the Huawei smart fitness trackers and the Actigraph GT3X+ triaxial accelerometer. By using the step counts monitored by the Huawei fitness trackers and the regression equation, it was possible to estimate the activity counts from the Actigraph GT3X+ triaxial accelerometer. Replacing the Actigraph GT3X+ triaxial accelerometer with Huawei smart fitness trackers for step count monitoring significantly reduces testing costs while providing consumers with intuitive data. Full article

The Gibbs free energies of gallic acid (GA) and its anionic forms in aqueous solution were computed utilizing density functional theory (DFT) at the LSDA, M062X, B3LYP/QZVP levels, in conjunction with the SMD solvation model. The pK_a values corresponding to the four-step deprotonation of GA were determined through a non-linear self-similar transformation expressed as, pK_a = a⋅pK_a(the)^c which establishes a link between theoretical and experimental pK_a values. This approach replaces the previously employed linear relationship, pK_a = a⋅pK_a(the) + b. The proposed model demonstrates high accuracy in reproducing the experimental pK_a1 = 4.16 ± 0.02, pK_a2 = 8.55 ± 0.01, pK_a3 =11.40 ± 0.10, pK_a4 =12.8 ± 0.40 values of GA, with a standard error (SE) of 0.045 and a mean absolute error (MAE) of 0.019 in pK_a unit. Furthermore, it facilitates the precise determination of the Gibbs free energy of the proton hydration, yielding ∆G(H⁺)_aq = 259.4272(75) [kcal mol⁻¹]. This result conforms acceptably with the experimental value of ∆G(H⁺)_aq = −259.5 [kcal mol⁻¹]. Full article

In this paper, we investigate the relationship between GaN exciton energy and temperature by using high-quality, strain-free GaN epilayers. Traditional models, such as Varshni’s model and the Bose–Einstein model, are primarily based on empirical fitting and give little or no consideration to electron–phonon interactions, which prevents them from accurately calculating GaN exciton energy over a wide temperature range. Considering the interaction of electrons and phonons, we use singular functions, linear functions and power functions to express the phonon density of GaN, and then 2BE, singular-linear, power-law-delta, and power-law-v models are proposed. All of them provide results that are more consistent with actual measurements compared to traditional models. Among them, the singular-linear model summarizes the contributions of acoustic and optical phonons. The error associated with the singular-linear model is smaller than that of the 1BE and Varshni models across nearly the entire temperature range. Therefore, the singular-linear model is a better choice. Full article

The thermodynamic study of protein folding shows the generation of a narrow range of ΔG° values, as a net result of large changes in the ΔH° and TΔS° values of the folding process. The obvious consequence of this narrow range of values is that a linear enthalpy–entropy relationship, showing apparent enthalpy–entropy compensation (EEC), is clearly observed to be associated with the study of protein folding. Herein, we show the ΔH°, TΔS°, and ΔG° values for a set of 583 data from protein folding processes, at various temperatures, as calculated by using the Gibbs–Helmholtz equations. This set of thermodynamic data was calculated from the melting temperature (Tm), the melting enthalpy (ΔHm), and the change in heat capacity (ΔCp°) values, all of them associated with the heat-induced protein unfolding processes and included in the ProTherm Data Base. The average values of enthalpy (ΔH°av), entropy (TΔS°av), and free energy (ΔG°av) for the folding process were calculated within the range of temperature from 0 °C to the average value of Tm. The values and temperature dependency of TΔS°av within this temperature range are practically equal to those corresponding to ΔH°av, while ΔG°av remains small and displaying a curve with a minimum at about 10 °C and a value of ΔG° = −30.9 kJ/mol at the particular temperature of 25 °C. The large negative value of TΔS°av, together with the also large and negative value of ΔCp°av, suggests large conformational changes and important EEC, thus causing the small average value of ΔG° for protein folding, which is enough to guarantee both protein stability and molecular flexibility to allow for adaptation to the chemical potentials of the environment. Our analysis suggests that EEC may be the quantum-mechanical evolutive mechanism to make functional proteins adaptative to environmental temperature and metabolite concentrations. The analysis of protein folding data, compared with those of protein–ligand interaction, allows us to suggest strategies to overcome EEC in the design of new drugs. Full article