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Despite excruciating attempts by polymer physicists in last several decades, lamellar assembly in ring-banded spherulites (RBSs) is still an unsolved and highly debated puzzle. In an unprecedented manner, the banded rings, based on a model polymer, are mapped with advanced synchrotron microbeam X-ray diffraction. According to the diffraction map and microscopy-dissection morphology, the periodically banded structure is composed of lamellae self-assembled as structural gratings. The comparison of a real-time micrograph with this mapping shows the sequential arrangement and orientation of lamellae in gratings. Lamellar assembly in RBS is fully explained with experimental evidence. This methodology can be applied to a wide variety of polymers to analyze spherulites displaying periodic self-assembled patterns.

Although polymer physicists have conducted extensive research over the decades, the molecular assembly in lamellae of ring-banded spherulites (RBS) remains a puzzle that has yet to be solved. Nonetheless, a breakthrough has occurred in this field where long-pitch banded rings made of a model poly(ʟ-lactide) (PLLA) were examined using advanced synchrotron X-ray micro-focused diffraction techniques. Through the microbeam diffraction mapping and microscopy 3D dissection morphology, the periodic banded structure of RBS is composed of lamellae that self-assemble as structural gratings. Furthermore, a comparison of optical micrograph image with the mapping results revealed the sequential arrangement and orientation of lamellae in these gratings. These extensive experimental findings now provide a comprehensive and novel explanation for the formation of long-pitch lamellar assembly in RBS. This new methodology is adaptable to a wide variety of polymers and allows for the analysis of spherulites displaying periodically self-assembled patterns. The novel methodology employed here has a versatile applicability for a diverse range of polymers. This technique can be extended to analyze spherulites showcasing periodically self-assembled patterns. Such revelation provides valuable understanding into the complex structures and behaviors of polymers, and this discovery opens up new frontiers in materials science research and its practical applications.

In lap joint laser welding, a common practice is to conduct trial-and-error experiments using various parameter settings to determine processing conditions that enhance the quality of the weld. However, these experiments are both time-consuming and expensive. Therefore, in this study, we propose a more systematic approach for determining the optimal laser power and scanning speed in the lap joint of SS316 by using highly accurate simulations and artificial neural network models. The processing maps were obtained for three criteria: the melt pool depth, melt pool width, and cooling rate, respectively, which were screened using appropriate quality criteria to determine the laser power and scanning speed that could simultaneously minimize porosity, the size of the heat affected zone, and residual stress. The validity of the simulation model was confirmed by comparing the simulation results of the melt pool geometry with the experimental data. The mean deviations of the experimental and simulated results for melt pool depth and width were found to be only 5.34% and 10%, respectively. As a result, the joint welds produced using the optimal processing parameters exhibited minimal porosity, which was reduced from 1.22% in a non-penetration zone to 0.21% in an optimized zone. Additionally, these welds achieved an ultimate shear strength of up to 545.77 MPa, which is approximately 32% higher than that of the original base metal. Therefore, the effectiveness of the proposed framework for determining the optimal processing conditions for joint laser welding of SS316 has been confirmed.