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The solubility values of eight common alloying elements Al, Ca, Ce, Gd, Nd, Sn, Y and Zn in hcp Mg are experimentally measured from diffusion profiles obtained from diffusion multiples and liquid-solid diffusion couples (LSDCs) using electron probe microanalysis. These solubility values are used to establish solidus and solvus lines and compared with the experimental results reported in the literature as well as the computed phase boundaries using two CALPHAD (CALculation of PHAse Diagrams) databases. Our experimental values for Mg-Ca (530, 580, 600, 630 °C), Mg-Ce (605, 630 °C), Mg-Gd (570, 600, 630 °C) and Mg-Nd (615, 630 °C) are the first ever measurements of the hcp solidus for these four binary systems. Additional solubility data obtained from our experiments are reported for Mg-Al (375, 420, 450, 500, 550, 600 °C), Mg-Sn (375, 420, 500, 550, 600 °C), Mg-Y (590, 610, 630 °C), and Mg-Zn (275, 450, 500, 550 °C). Our experimental data are valuable input to future thermodynamic reassessments of the eight binary systems. This study also clearly shows the effectiveness of measuring solidus data using the elegant LSDCs. 

Cellulose-based conductive composite fibers hold great promise in smart wearable applications, given cellulose's desirable properties for textiles. Blending conductive fillers with cellulose is the most common means of fiber production. Incorporating a high content of conductive fillers is demanded to achieve desirable conductivity. However, a high filler load deteriorates the processability and mechanical properties of the fibers. Here, developing wet-spun cellulose-based fibers with a unique side-by-side (SBS) structure via sustainable processing is reported. Sustainable sources (cotton linter and post-consumer cotton waste) and a biocompatible intrinsically conductive polymer (i.e., polyaniline, PANI) were engineered into fibers containing two co-continuous phases arranged side-by-side. One phase was neat cellulose serving as the substrate and providing good mechanical properties; another phase was a PANI-rich cellulose blend (50 wt%) affording electrical conductivity. Additionally, an eco-friendly LiOH/urea solvent system was adopted for the fiber spinning process. With the proper control of processing parameters, the SBS fibers demonstrated high conductivity and improved mechanical properties compared to single-phase cellulose and PANI blended fibers. The SBS fibers demonstrated great potential for wearable e-textile applications. 

Fe2O3 is an appealing anode material due to its high specific capacity (1007 mAh g− 1), low cost, natural abundance, and nontoxicity. However, its unstable structure during cycling processes has hindered its potential. In this study, we present a “green” synthesis method to fabricate stable porous Fe2O3 encapsulated in a buffering hollow structure (p-Fe2O3@h-TiO2) as an effective anode material for Li-ion batteries. The synthesis process only involves glucose as an “etching” agent, without the need for organic solvents or difficult-to-control environments. Characterizations of the nanostructures, chemical compositions, crystallizations, and thermal behaviors for the intermediate/final products confirm the formation of p-Fe2O3@h-TiO2. The synthesized Fe2O3 anode material effectively accommodates volume change, decreases pulverization, and alleviates agglomeration, leading to a high capacity that is over eleven times greater than that of the as-received commercial Fe2O3 after a long cycling process. This work provides an attractive, “green” and efficient method to convert commercially abundant resources like Fe2O3 into effective electrode materials for energy storage systems. 

Electrochemical energy storage devices (EESDs) are critical technologies in modern economy, covering numerous fields such as portable electronics, electric vehicles, etc. The expanding market of EESDs demands for extra requirements such as safety, environmental friendliness and low cost, in addition to increasingly enhanced electrochemical properties. Natural proteins are abundant, versatile bio-macromolecules involving tremendous amount of amino acids/functional groups/heteroatoms, which greatly benefit sustainable technologies for advancing performances of EESDs. Recent years, significant research on utilizing natural proteins including plant/animal proteins to fabricate active materials for enhancing performance of EESDs has been well reported. Therefore, it is important to comprehensively summarize the progress and achievements, analyze the advantages/challenges, and predict the prospective for future protein-based strategies toward high performance EESDs, which are the contents of this review. The protein-derived active materials include activated carbons, silicon, sulfur, metal alloys, transitional metal compounds, and nonprecious metal catalysts. The resulting EESDs are associated with Li-/Na-/K-ion batteries, metal–air batteries, and redox flow batteries, as well as supercapacitors. The contributions of proteins to stabilizing/protecting electrodes, and thus enhancing performance of EESDs are specifically emphasized. Furthermore, studies on genetical engineering of proteins for directing self-assembly of active material nanoparticles are introduced. 

A systematic analysis was performed on Manning’s vacancy wind factor for diffusion in 13 binary solid solutions for which experimentally measured tracer diffusion coefficient data collected from the literature are reliable and comprehensive. Some straightforward yet interesting observations are reported, including a value of ~ 1.85 for the diamond cubic Ge-Si binary solid solution. It is recommended that the vacancy wind factor not be included in the CALPHAD diffusion coefficient (mobility) assessments since the effects have essentially been included in the fitting parameters. For those who use diffusion coefficients directly (not mobility parameters), the factor may still be ignored for both fcc and bcc solid solutions since the maximum effect is only a 28% and 38% increase in the interdiffusion (chemical diffusion) coefficients, respectively. The factor may be included for low diffusion coefficient systems of diamond cubic phases at low temperatures and especially for those systems whose tracer diffusion coefficients differ by orders of magnitude. 

Both CALPHAD (CALculation of PHAse Diagrams) and machine-learning (ML) approaches were employed to analyze the phase formation in 2,436 experimentally measured high entropy alloy (HEA) compositions consisting of various quinary mixtures of Al, Co, Cr, Cu, Fe, Mn, and Ni. CALPHAD was found to have good capabilities in predicting the BCC/B2 and FCC phase formation for the 1,761 solid-solution-only compositions, excluding HEAs containing an amorphous phase (AM) or/and intermetallic compound (IM). Phase selection rules were examined systematically using several parameters and it revealed that valency electron concentration (VEC) < 6.87 and VEC > 9.16 are the conditions for the formation of single-phase BCC/B2 and FCC, respectively; and CALPHAD could predict this with essentially 100% accuracy. Both CALPHAD predictions and experimental observations show that more BCC/B2 alloys are formed over FCC alloys as the atomic size difference between the elements increases. Four machine learning (ML) algorithms, decision tree (DT), k-nearest neighbor (KNN), support vector machine (SVM), and artificial neural network (ANN), were employed to study the phase selection rules for two different datasets, one consisting of 1,761 solid-solution (SS) HEAs without AM and/or IM phases, and the other set consisting of all the 2,436 HEA compositions. Cross validation (CV) was performed to optimize the ML models and the CV accuracies are found to be 91.4%, 93.1%, 90.2%, 89.1% for DT, KNN, SVM, and ANN respectively in predicting the formation of BCC/B2, BCC/B2 + FCC, and FCC; and 93.6%, 93.3%, 95.5%, 92.7% for DT, KNN, SVM, and ANN respectively in predicting SS, AM, SS + AM, and IM phases. Sixty-six experimental bulk alloys with SS structures are predicted with trained ANN model, and the accuracy reaches 81.8%. VEC is found to be most important parameter in phase prediction for BCC/B2, BCC/B2 + FCC, and FCC phases. Electronegativity difference and FCC-BCC-index (FBI) are the two additional dominating features in determining the formation of SS, AM, SS + AM, and IM. A separation line ΔH_mix=28.97×VEC-246.77 was found in the VEC-vs-ΔH_mix plot to predict the formation of single-phase BCC/B2 or FCC with a 96.2% accuracy (ΔH_mix = mixing enthalpy). These insights will be very valuable for designing HEAs with targeted crystal structures. 

Liquid–solid diffusion couples (LSDCs) are employed to generate a composition gradient in the single‐phase hexagonal closed‐packed (hcp) solid solution with compositions up to the solubility limit of various solutes in Mg. Nanoindentation scanning across the composition gradient in LSDCs allows effective evaluation of composition‐dependent hardness of eight alloying elements (Al, Ca, Ce, Gd, Li, Sn, Y, and Zn) in the hcp Mg phase. The hardening coefficients, an indicator of the potency of solid‐solution hardening, are evaluated from the measured composition‐hardness data and correlated with various materials properties such as atomic radius, shear modulus, and elastic modulus of the solutes. The rank of hardening potency of Al, Gd, Sn, Y, and Zn measured by nanoindentation is in good agreement with that measured by microindentation reported in the literature. The hardening coefficient (potency) from the strongest to the weakest is Ce > Ca > Y ≈ Gd > Zn > Al ≈ Sn > Li in Mg‐based hcp binary solid solutions. The hardening coefficient is found to be closely correlated with the strengthening potency.

 

With plenty of charges and rich functional groups, bovine serum albumin (BSA) protein provides effective transport for multiple metallic ions inside blood vessels. Inspired by the unique ionic transport function, we develop a BSA protein coating to stabilize Li anode, regulate Li+ transport, and resolve the Li dendrite growth for Li metal batteries (LMBs). The experimental and simulation studies demonstrate that the coating has strong interactions with Li metal, increases the wetting with electrolyte, reduces the electrolyte/Li side reactions, and significantly suppresses the Li dendrite formation. As a result, the BSA coating exhibits excellent stability in the electrolyte and improves the performance of Li|Cu and Li|Li cells as well as the LiFePO4|Li batteries. This work reveals that LMBs can benefit from the biological function of BSA, i.e., special transport capability of metallic ions, and lays an important foundation in design of protein-based materials for effectively enhancing the electrochemical performance of energy storage systems.