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The morphological and mechanical characteristics of red blood cells (RBCs) largely vary depending on the occurrence of hematologic disorders. Variations in the rheological properties of RBCs affect the dynamic motions of RBCs, especially their rotational behavior. However, conventional techniques for measuring the orientation of biconcave-shaped RBCs still have some technical limitations, including complicated optical setups, complex post data processing, and low throughput. In this study, we propose a novel image-based technique for measuring 3D position and orientation of normal RBCs using digital in-line holographic microscopy (DIHM) and artificial intelligence (AI). Formaldehyde-fixed RBCs are immobilized in coagulated polydimethylsiloxane (PDMS). Holographic images of RBCs positioned at various out-of-plane angles are acquired by precisely manipulating the PDMS-trapped RBC sample attached to a 4-axis optical stage. With the aid of deep learning algorithms for data augmentation and regression analysis, the out-of-plane angle of RBCs is directly predicted from the captured holographic images. The 3D position and in-plane angle of RBCs are acquired by employing numerical reconstruction and ellipse detection methods. Combining these digital image processing techniques, the 3D positional and orientational information of each RBC recorded in a single holographic image is measured within 23.5 and 3.07 s, respectively. The proposed AI-based DIHM technique that can extract the 3D position, orientation, and morphology of individual RBCs would be utilized to analyze the dynamic translational and rotational motions of abnormal RBCs with hematologic disorders in shear flows through further research. • AI-based analysis of out-of-plane angles of RBCs was demonstrated. • 3D positions and in-plane angles of RBCs were measured using a DIHM technique. • 3D positions and orientations of RBCs recorded in a single hologram were measured. • This technique has a simpler optical setup and higher throughputs than others. • It would be utilized to analyze 3D dynamics of RBCs flowing in a microchannel. [ABSTRACT FROM AUTHOR]

Cobalt hexacyanoferrate (CoHCF) suffers from low rate capability and lifespan because of the dissolution and structural instability of Co during cycling. A smaller active material can relieve the stress caused by volume change during cycling and enable shorter transport pathways. Here, particle size reduction is performed by reducing the mixing time or citrate concentration in the coprecipitation reaction to improve the rate capability and lifespan of CoHCF. The reduced mixing time produces smaller particles with enlarged active sites, thus improving the capacity. Upon coprecipitation at a low citrate concentration, particle precipitation at reduced sizes is achieved by preferential nucleation versus growth. Although lowering the citrate concentration enlarges the external surface area, the reduced redox-active Fe degrades the capacity. All CoHCF samples with small sizes achieved enhance rate capability and stability. In particular, the sample synthesized with a short mixing time (0 h) achieve a specific capacity of 122 mAh g−1 with improved rate capability (79.4%) and stability (79.3%) over 500 cycles. Structural distortions are relaxed because of the shortened transport pathways and relieved distortion owing to particle size reduction. This study paves the approach for fast rechargeable and long-lasting aqueous Na-ion batteries using CoHCF electrodes. [Display omitted] • A decreased mixing time or citrate concentration yielded smaller CoHCF particles. • The capacity, rate capability, and lifespan were improved with shorter mixing times. • The low citrate ion concentration increased Fe vacancies and decreased the capacity. • Fe vacancies limited Na access in the lattice, thus improving structural stability. • The reduced CoHCF particle size improved rate capability and lifespan. [ABSTRACT FROM AUTHOR]