Continuous Phase Research Articles

Emulsion Structural Remodeling in Milk and Its Gelling Products: A Review.

The fat covered by fat globule membrane is scattered in a water phase rich in lactose and milky protein, forming the original emulsion structure of milk. In order to develop low-fat milk products with good performance or dairy products with nutritional reinforcement, the original emulsion structure of milk can be restructured. According to the type of lipid and emulsion structure in milk, the remolded emulsion structure can be divided into three types: restructured single emulsion structure, mixed emulsion structure, and double emulsion structure. The restructured single emulsion structure refers to the introduction of another kind of lipid to skim milk, and the mixed emulsion structure refers to adding another type of oil or oil-in-water (O/W) emulsion to milk containing certain levels of milk fat, whose final emulsion structure is still O/W emulsion. In contrast, the double emulsion structure of milk is a more complicated structural remodeling method, which is usually performed by introducing W/O emulsion into skim milk (W2) to obtain milk containing (water-in-oil-in-water) W1/O/W2 emulsion structure in order to encapsulate more diverse nutrients. Causal statistical analysis was used in this review, based on previous studies on remodeling the emulsion structures in milk and its gelling products. In addition, some common processing technologies (including heat treatment, high-pressure treatment, homogenization, ultrasonic treatment, micro-fluidization, freezing and membrane emulsification) may also have a certain impact on the microstructure and properties of milk and its gelling products with four different emulsion structures. These processing technologies can change the size of the dispersed phase of milk, the composition and structure of the interfacial layer, and the composition and morphology of the aqueous phase substance, so as to regulate the shelf-life, stability, and sensory properties of the final milk products. This research on the restructuring of the emulsion structure of milk is not only a cutting-edge topic in the field of food science, but also a powerful driving force in promoting the transformation and upgrading of the dairy industry to achieve high-quality and multi-functional dairy products, in order to meet the diversified needs of consumers for health and taste.

Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization.

Precise size and shape control in nanocrystal synthesis is essential for utilizing nanocrystals in various industrial applications, such as catalysis, sensing, and energy conversion. However, traditional ensemble measurements often overlook the subtle size and shape distributions of individual nanocrystals, hindering the establishment of robust structure-property relationships. In this study, we uncover intricate shape evolutions and growth mechanisms in Co3O4 nanocrystal synthesis at a subnanometer scale, enabled by deep-learning-assisted statistical characterization. By first controlling synthetic parameters such as cobalt precursor concentration and water amount then using high resolution electron microscopy imaging to identify the geometric features of individual nanocrystals, this study provides insights into the interplay between synthesis conditions and the size-dependent shape evolution in colloidal nanocrystals. Utilizing population-wide imaging data encompassing over 441,067 nanocrystals, we analyze their characteristics and elucidate previously unobserved size-resolved shape evolution. This high-throughput statistical analysis is essential for representing the entire population accurately and enables the study of the size dependency of growth regimes in shaping nanocrystals. Our findings provide experimental quantification of the growth regime transition based on the size of the crystals, specifically (i) for faceting and (ii) from thermodynamic to kinetic, as evidenced by transitions from convex to concave polyhedral crystals. Additionally, we introduce the concept of an "onset radius," which describes the critical size thresholds at which these transitions occur. This discovery has implications beyond achieving nanocrystals with desired morphology; it enables finely tuned correlation between geometry and material properties, advancing the field of colloidal nanocrystal synthesis and its applications.

Determining the optimum number of cycles for calculating joint coordination and its variability during running at different speeds: A timeseries analysis

Understanding the intricacies of human movement coordination and variability during running is crucial to unraveling the dynamics of locomotion, identifying potential injury mechanisms and understanding skill development. Identification of minimum number of cycles for calculation of reliable coordination and its variability could help with better test organization and efficient assessment time. By adopting a cross-sectional study design, this study investigated the minimum required cycles for calculating hip-knee, hip-ankle and knee-ankle coordination and their variability using a continuous relative phase (CRP) method. Twenty-nine healthy adults ran on a treadmill at speeds of 9, 12.5, and 16 km.h−1 while 3D kinematic data of their lower limbs were recorded using 6 optoelectronic cameras. Using Intraclass Correlation Coefficient (ICC) analysis, reliability between CRP and its variability (CRPv) in different gait cycles (3, 5, 10, 20, 30) was assessed for each speed. A minimum of 10 cycles was required for CRP calculation across all speeds, whereas CRPv necessitated a minimum of 30 cycles for moderate to good reliability. While increasing the number of cycles improved ICC values for inter-joint CRP, the same trend was not consistently observed for CRPv, emphasizing the importance of separately assessing CRP and its variability metrics.

Semi-Lagrangian simulation of particle laden flows using an SPH framework

Particle–laden flows occur in many natural and industrial systems and simulating them can be particularly challenging. The coupling of smoothed particle hydrodynamics (SPH) with the discrete element method (DEM) can effectively simulate particle-laden multiphase fluid dynamical systems, due to the shared Lagrangian nature of both methods. However, this approach has some inherent shortcomings, including a prohibitively small time step when dealing with small particles. An alternative approach is to use an Eulerian-Eulerian reference frame, usually using finite element or finite volume discretisations. In this approach, momentum and continuity equations are solved for each discrete phase as well as the continuous phase, and particles are modelled by means of concentration and velocity fields. This approach can suffer from strong numerical diffusion in the advection of the concentrations when absolute velocities of the phases are high, whilst their relative velocities are small. This numerical diffusion can obscure important aspects of the behaviour as it can smooth out details, especially in the particle concentration fields. In order to mitigate the shortcomings of these existing techniques, we present a new SPH-based semi-Lagrangian framework for solving the momentum and continuity equations for all phases in particle-laden flows. In this framework, the discrete and continuous phases move relative to a reference frame that moves at a momentum-averaged velocity. By focusing on velocities relative to the reference frame our method substantially reduces numerical diffusion compared to traditional Eulerian-Eulerian approaches, at a lower computational cost compared to Lagrangian-Lagrangian approaches. The simulation approach is validated by means of comparisons to both computational and experimental results for a number of relevant systems including particle-liquid separation in an inclined channel, particle sedimentation in a liquid, and gas-particle fluidised beds. This new method is shown to compare very favourably in terms of both the accuracy of the results and the computational cost required to achieve them.

Using Rheology and Image Processing to Study the Effects of Cellulose Nanocrystal Sedimentation.

The effect of sedimentation on lyotropic liquid crystalline dispersions is both an interesting subject in colloidal science and is of practical importance for understanding changes that can occur during dispersion storage. This research explored how the seemingly subtle changes in average length resulting from a single sedimentation step affected the rheological properties and self-assembly of aqueous dispersions of sulfated cellulose nanocrystals. Sedimentation of a primarily isotropic aqueous cellulose nanocrystal dispersion for 1 month at ambient conditions resulted in an isotropic top phase and a biphasic bottom phase, which were separated for further study. Both atomic force microscopy measurements and intrinsic viscosities determined via Fedor's equation showed preferential fractionation of longer cellulose nanocrystals (CNCs) to the bottom phase. The effects of this fractionation on dispersion rheology and phase behavior were studied by preparing a range of concentrations from each phase. As expected, the concentration for the isotropic-biphasic phase transition was significantly lower for the bottom phase than for the top phase or parent dispersion. Rheological changes were generally subtle, but significant differences were seen in the storage modulus at concentrations approaching rheological gelation. Most notably, quantitative image processing showed that even this simple, single-step fractionation process had a significant impact on the relative proportion of tactoids and chiral helices with planar and homeotropic anchoring in self-assembled cellulose nanocrystal films. These results highlight the impact that changes in polydispersity due to sedimentation can have on the self-assembly of nanomaterial mesogens.

Revealing the Role of Organic Ligands in Deep-Blue-Emitting Colloidal Europium Bromide Perovskite Nanocrystals.

Europium halide perovskites are promising candidates for environmentally benign blue-light emitters with their narrow emission line width. However, the development of high-photoluminescence quantum yield (PLQY) colloidal europium halide perovskite nanocrystals (PNCs) is hindered by limited synthetic methods and elusive reaction mechanisms. Here, we provide an effective synthetic route for achieving high-PLQY deep-blue-emitting colloidal CsEuBr3 PNCs. Using two Br-organic ligand precursors, oleylammonium bromide (OLAMHBr) and trioctylphosphine dibromide (TOPBr2), we identified distinct phase evolution routes involving Eu2+:CsBr, Cs4EuBr6, and CsEuBr3. The OLAMHBr precursor initially promotes the formation of the Eu2+:CsBr phase, which reorganizes into the CsEuBr3 perovskite phase via proton transfer. In contrast, the TOPBr2 precursor induces the formation of core/shell Cs4EuBr6/CsBr PNCs, which subsequently transform into CsEuBr3 through nucleophilic addition. The TOPBr2 route exhibited enhanced CsEuBr3 phase homogeneity, resulting in a significantly higher PLQY (40.5%; full width at half-maximum (fwhm) = 24 at 430 nm), compared to the OLAMHBr route (16.5% at 418 nm). Notably, the phase-pure CsEuBr3 PNCs demonstrated a world-record PLQY among the reported blue-emitting lead-free PNCs that exhibit a narrow emission line width (fwhm <25 nm). This work highlights the significant role of organic ligands in the colloidal synthesis of CsEuBr3 PNCs and their potential as nontoxic, solution-processable blue-light emitters.

Multi task deep learning phase unwrapping method based on semantic segmentation

Abstract Phase unwrapping is a key step to obtain continuous phase distribution in optical phase measurement. When the wrapped phase obtained from the interference pattern is unclear and noisy, estimating the unwrapped phase becomes more challenging. As deep learning advances in optical image processing, it will enhance processing efficiency and accuracy, bringing broader possibilities for various applications. This paper introduces an innovative phase unwrapping method based on multi-task learning, aiming to simultaneously enhancing denoised images and predicting wrap count. The proposed network, named ICER-Net, comprises an encoder and two decoders, transforming the input low-luminance, noisy wrapped phase into two intermediate outputs: enhanced wrapped phase and wrap count. Finally, these two intermediate results are fused to obtain the unwrapped phase. Experimental results demonstrate that ICER-Net not only enhances the accuracy of phase unwrapping, particularly when facing challenges of various noise levels and luminance sizes but also exhibits outstanding performance in actual collected speckle phase images. This indicates that ICER-Net holds significant superiority in addressing complex issues in optical image processing.

Quantum phases and transitions in spin chains with non-invertible symmetries

Generalized symmetries often appear in the form of emergent symmetries in low energy effective descriptions of quantum many-body systems. Non-invertible symmetries are a particularly exotic class of generalized symmetries, in that they are implemented by transformations that do not form a group. Such symmetries appear in large families of gapless states of quantum matter and constrain their low-energy dynamics. To provide a UV-complete description of such symmetries, it is useful to construct lattice models that respect these symmetries exactly. In this paper, we discuss two families of one-dimensional lattice Hamiltonians with finite on-site Hilbert spaces: one with (invertible) S_3S3 symmetry and the other with non-invertible \mathsf{Rep}(S_3)𝖱𝖾𝗉(S3) symmetry. Our models are largely analytically tractable and demonstrate all possible spontaneous symmetry breaking patterns of these symmetries. Moreover, we use numerical techniques to study the nature of continuous phase transitions between the different symmetry-breaking gapped phases associated with both symmetries. Both models have self-dual lines, where the models are enriched by so-called intrinsically non-invertible symmetries generated by Kramers-Wannier-like duality transformations. We provide explicit lattice operators that generate these non-invertible self-duality symmetries. We show that the enhanced symmetry at the self-dual lines is described by a 2+1d symmetry-topological-order (SymTO) of type JK_4\boxtimes \overline{JK}_4JK4⊠JK¯4. The condensable algebras of the SymTO determine the allowed gapped and gapless states of the self-dual S_3S3-symmetric and \mathsf{Rep}(S_3)𝖱𝖾𝗉(S3)-symmetric models.

Interaction of a Dense Layer of Solid Particles with a Shock Wave Propagating in a Tube

A numerical simulation of an unsteady gas flow containing inert solid particles in a shock tube is carried out using the interpenetrating continuum model. The gas and dispersed phases are characterized by governing equations that express the concepts of mass, momentum, and energy conservation as well as an equation that shows the change of the volume fraction of the dispersed phase. Using a Godunov-type approach, the hyperbolic governing equations are solved numerically with an increased order of accuracy. The working section of the shock tube containing air and solid particles of various sizes is considered. The shock wave structure is discussed and computational results provide the spatial and temporal dependencies of the particle concentration and other flow quantities. The numerical simulation results are compared with available experimental and computational data.

Colloidal Synthesis and Analysis of CNT-Cu2S for Stability and Capacity Increase Alleviation in Sodium-Ion Storage.

With the growing interest in energy storage, significant research has focused on finding suitable anode materials for sodium-ion batteries (SIBs). While developing high-capacity nanosized metal sulfides, issues like low stability and rapid initial capacity decline are common. Instead of maintaining steady capacity, they also tend to exhibit an increase in discharge capacity as cycling continues. We introduce CNT-Cu2S, featuring Cu2S nanoplates integrated onto the surface of MWCNTs, and assess its electrochemical properties for SIBs. Cu2S initially exhibited a rapid decrease in capacity and then showed increased capacity. In contrast, CNT-Cu2S demonstrated a stable capacity of 344.8 mAh g-1 at 2.0 A g-1 over 800 cycles, close to the theoretical capacity with capacitive behavior. This paper carried out analysis using data from in situ EIS and overpotential data from GITT to explain the different outcomes between the Cu2S and CNT-Cu2S experiments. These results show that CNT-Cu2S is a suitable anode material for SIBs.

Observing Quantum Measurement Collapse as a Learnability Phase Transition

During a quantum measurement, superpositions of states with different observable properties probabilistically collapse into one with a sharp value of the measured observable. In macroscopic quantum systems, this collapse arises via a continuous measurement-induced phase transition (MIPT) at a critical value of the strength of interaction with the measurement apparatus. MIPTs lie outside established paradigms for equilibrium or nonequilibrium critical phenomena and delineate distinct, stable dynamical and computational phases of matter. Quantum computers enable programmable simulation of the interaction of a measurement apparatus with a dynamical quantum system, to explore MIPT phenomena over a range of system sizes while retaining quantum coherence. Yet, existing experimental protocols rely on fundamentally nonscalable postselection techniques or direct classical simulation of quantum circuits. Here, we report the scalable observation of finite-size scaling evidence for an observable-sharpening MIPT in monitored quantum circuits in a chain of Yb+171 ions in Quantinuum’s H1-1 trapped-ion quantum processor. By leveraging an equivalent description as a statistical physics problem, we implement scalable classical algorithms to infer the value of the measured observable from a single experimental shot. This technique enables a truly scalable protocol to observe observable-sharpening MIPTs in generic classes of circuits that cannot be directly classically simulated and also provides enhanced means to detect and suppress errors in the quantum simulation. Published by the American Physical Society 2024

Poly(butylene succinate) Microparticles Prepared Through Green Suspension Polycondensations

AbstractThe demand for sustainable polymer particles production is growing, driven by the need for efficient, biocompatible, and biodegradable materials. In this context, the present study explores the production of poly(butylene succinate) (PBS) particles in a single step using a green heterogeneous suspension process, using vegetable oil as the suspending medium. Particularly, the effects of oil type (soybean, corn, sunflower), dispersed phase holdup (10–30 wt.%), stabilizers (Span 20, Span 80, Tween 80, Brij 52, Brij 93, Igepal‐co‐520, Polyglycerol polyricinoleate (PGPR)), reaction time (1–5 h), and temperature (100–160 °C) on the suspension polymerization are investigated. Results indicate that particle size and shape are influenced by the vegetable oil and stabilizer. Additionally, it is shown that the particle size distribution is affected by the use of a sonicator, allowing the manufacture of even smaller microsized particles. Based on the results, a 30 wt.% holdup in corn oil with a blend of surfactants can be recommended, producing spherical particles with an average diameter of 100 µm. Moreover, higher reaction temperatures (160 °C) and longer reaction times (5 h) positively impacted the molar mass of the obtained particles. Finally, cytotoxicity tests using Bone Marrow‐Derived Macrophages cells confirmed the safe use of PBS microparticles at concentrations up to 1000 µg mL⁻¹

The impact of receiver arrays on suppressing seismic speckle scattering noise caused by the meter-scale near-surface heterogeneity

Managing seismic scattering noise in geophysical surveying, especially from near-surface heterogeneity, presents significant challenges. We revisit the role of receiver arrays in mitigating such noise in regions with near-surface meter-scale heterogeneity. Moving beyond traditional approaches that focus on suppressing coherent noise from near-surface arrivals and random ambient noise, our research highlights the substantial impact of speckle scattering noise. This noise, resulting from near-ballistic scattering on small-scale heterogeneities, introduces considerable trace-to-trace variability in phase and amplitude, complicating data processing. By integrating a novel model of random multiplicative noise with sophisticated statistical techniques, we determine the efficacy of array stacking in significantly reducing this type of noise and decreasing the dispersion of phase and amplitudes. Our analytical and numerical analyses reveal a notable trend: the reduction in phase and amplitude spread amplifies with the array size. A key finding of our study is the identification of a [Formula: see text] law for phase spread reduction, analogous yet distinct from the well-known [Formula: see text] law observed in amplitude attenuation of additive ambient noise. In our context, this law implies that the standard deviation of residual phase disturbances diminishes in proportion to [Formula: see text], where N denotes the array size. This insight holds particular significance for smaller arrays, such as those with nine receivers commonly used in desert environments.

Compatibilization of Poly(lactic acid)/Poly(propylene carbonate) blends by star-shaped multi-arm polymer with low molecular weight

Compatibilizing polymer blends via a facile and efficient manner is of great significance since polymer blends are practical in industrial applications but limit severely by poor compatibility. Herein, we propose a novel compatibilization strategy that star-shaped multi-arm polymer with low molecular weight can be an excellent compatibilizer for polymer blends. As an example of the concept, a modified tannic acid (mTA) with a star-shaped multi-arm structure is fabricated to compatibilize biodegradable poly(lactic acid)/poly(propylene carbonate) (PLA/PPC) blend. Compared to traditional compatibilization methods, mTA shows higher compatibilization efficiency and lower limitation in distribution as mTA can exert compatibilization at the interface and in PLA and PPC phases. Consequently, mTA compatibilizes the PLA/PPC blend efficiently, leading to strikingly reduced size of PPC dispersed phase and optimized interface. The mechanism is revealed to stem from the reduced interfacial tension and regulated viscosity ratio. With the improved compatibility, PLA70/PPC30/mTA4 shows an elongation at break of 307.5 ± 15.4 % and a toughness of 85.2 ± 4.5 MJ/m3, which is 680 % and 800 % of that of PLA70/PPC30 respectively. We envision that this work provides a novel and facile compatibilization strategy and will promote the fabrication of high-performance polymer blends.

Application of magnetic AlFu MOF nanocomposite for the extraction and preconcentration of some pesticides from different distillates

This research used a magnetic AlFu nano-metal-organic framework as an adsorbent for the first time. This approach extracts and preconcentrates eight pesticides from various distillates through a two-step process: magnetic dispersive micro solid phase extraction and dispersive liquid-liquid microextraction. Initially, the nanocomposite is dispersed into a sample solution containing the pesticides and Na2SO4. The target pesticides are then adsorbed onto the nanocomposite, which is subsequently isolated from the aqueous phase using an external magnetic field. Acetonitrile is used to elute the adsorbed analytes pesticides from the nanocomposite surface. The resulting acetonitrile extract, containing the concentrated pesticides, is then mixed with a tiny amount of another solvent and injected into a NaCl solution. Centrifugation allows the organic phase, enriched with the pesticides, to settle down. An aliquot of this organic layer is then analyzed using a gas chromatography-flame ionization detector. Optimization of the procedure led to favorable performance, including good extraction recovery of the pesticides (68–98 %), significant enrichment (enrichment factors of 340–489), a wide range of detectable concentrations (2.90–1400 µg L−1), and low detection (0.15–0.88 µg L−1) and quantification limits. (0.49–2.90 µg L−1)

Production of Monodisperse Large Drop Emulsions by Means of High Internal Phase Pickering Emulsions-Processing and Formulation.

High internal phase Pickering emulsions (HIPPE) have received significant research attention in the last two decades due to their potential for a wide range of applications. The appropriate processing of such high-viscosity emulsions, hundreds of times more viscous than that of the continuous phase, and the control of the final droplet size remain challenges to be tackled. Our research targeted this knowledge gap by examining the influence of the emulsion formulation and the processing conditions on the final droplet size. The dispersed phase fraction (100 cSt silicon oil) ranged between 75 and 80%. The emulsions were produced in a regular mixing tank equipped with a helical ribbon impeller rotating at a low speed (100-150 rpm). The effective viscosity of the continuous phase was obtained from the experimental torque measurements. The droplet size distributions were measured after emulsification and dilution in the continuous phases. It is shown that the capillary number obtained from the observed emulsification performance can help predict the final droplet size. Our approach provides a straightforward methodology to generate concentrated Pickering emulsions with controlled and predictable droplet size.

Exceptional points in the microcavity with phonon pump enhance the transparency and slow light

We theoretically investigated optomechanically induced transparency (OMIT) and slow light in a microcavity optomechanical system containing three nanoparticles, where the pump-probe field drives the cavity and a weak phonon pump drives the mechanical resonator. When the phonon pump frequency matches the pump-probe field frequency difference, adjusting the phonon pump's amplitude and phase can result in the transparency window exceeding unity. Tuning the relative positions of nanoparticles can periodically steer the system to exceptional points (EPs), further enhancing and modulating the transparency window. Furthermore, the phonon pump causes the phase dispersion at the transparency window to become highly steep, resulting in a large value and tunable group delay. Notably, when the system is at EPs, the slow light can be enhanced by approximately two times compared to when the system is not at EPs. Our research demonstrates a way to control optical transmission with potential applications in quantum communications and optical buffers.

Covalent organic framework composite hydrogel sorbent beads for vortex-assisted dispersive miniaturized solid phase extraction of parabens and synthetic phenolic antioxidants in foodstuffs

A covalent organic framework composite hydrogel sorbent beads was fabricated for the vortex-assisted dispersive miniaturized-solid phase extraction and determination of parabens and synthetic phenolic antioxidants from food matrices. The covalent organic framework was entrapped into alginate hydrogel beads. This composite sorbent effectively adsorbs analytes through hydrophobic, π-π and hydrogen bonding interactions. Under optimal extraction conditions, the developed method demonstrated good linearity from 1.00 to 100 µg kg−1 for methyl paraben and 2.00 to 100 µg kg−1 for tertiary butylhydroquinone, propyl paraben, butyl paraben and butylated hydroxyanisole. Limits of detection ranged from 0.25 to 0.50 µg kg−1. The developed sorbent was applied to the extraction of parabens and synthetic phenolic antioxidants from tomato paste, mayonnaise, infant milk powder and coffee creamer samples. The analytes were separated and quantified by high-performance liquid chromatography, achieving recoveries ranging from 89 to 98 % with RSDs lower than 7 %. The vortex-assisted extraction approach was efficient, and the fabricated sorbent could be reused for up to eight cycles. The greenness of the methodology was also evaluated.

Colloidal Ag2SbBiSe4 nanocrystals as n‑type thermoelectric materials

Materials with low intrinsic thermal conductivity are essential for the development of high-performance thermoelectric devices. At the same time, the solution processing of these materials may enable the cost-effective production of the devices. Herein, we detail a high-yield and scalable colloidal synthesis route to produce Ag2SbBiSe4 nanocrystals (NCs) using amine-thiol-Se chemistry. The quaternary chalcogenide material is consolidated by a rapid hot-press maintaining the cubic crystalline structure. Transport measurements confirm that n-type Ag2SbBiSe4 exhibits an inherently ultralow lattice thermal conductivity of ca. 0.34 W m−1K−1 at 760 K. Moreover, a modulation doping strategy based on the blending of semiconductor Ag2SbBiSe4 and metallic Sn NCs is demonstrated to control the charge carrier concentration in the final composite material. The introduction of Sn nanodomains additionally blocks phonon propagation thus contributing to reducing the thermal conductivity of the final material. Ultimately, a peak thermoelectric figure of merit value of 0.64 at 760 K is achieved for n-type Ag2SbBiSe4-Sn nanocomposites that also demonstrate a notable Vickers hardness of 185 HV.

Micro-alloying of Sm with rolling for synergetic corrosion resistance and mechanical properties of Mg-Al-Sn-Ca-Mn alloys

Micro Sm alloying coupling with four-pass rotary rolling is conducted to synergize the corrosion resistance and mechanical properties of Mg-Al-Sn-Ca-Mn alloys. Micro Sm alloying weakens the galvanic corrosion. Rolling process refines the grains, intensifies the basal texture and promotes dispersed second phase particles, thereby contributing to forming a uniform and protective corrosion product film, and enhancing the mechanical strength and ductility. As a result, rolled Mg-Al-Sn-Ca-Mn-Sm alloy exhibits a synergy of mechanical properties and corrosion resistance, i.e., an UTS of 271 MPa, YS of 204 MPa, elongation to failure of 18 %, and a low corrosion rate of 0.85 mm y−1.