#mechanical properties

Pushing the frontiers of frozen water: Computer simulations examine effects of shear on medium-density amorphous ice

Water is ubiquitous and seemingly ordinary, possessing no distinct color or odor. Though we often take water for granted, it is by no means a simple substance. As a consequence of its chemical properties, H₂O is one of the most incredible substances, able to form into 20 known separate crystalline ice phases. Now researchers are seeking to expand that number even further. Ingrid De Almeida Ribeiro, a postdoctoral researcher in chemistry, and her lab partners in the Molinero Research Group at the University of Utah's department of chemistry have published a study in Proceedings of the National Academy of Sciences detailing their work advancing the science of amorphous ice using computer simulations.

What is the forging process?

Forging is the working of metal into a useful shape by using localized compressive forces. These forces are applied through various tools such as hammers or presses. This process is integral to producing high-strength components for various industries, including automotive, aerospace, and construction.

Carburizing, also known as a case-hardening process, is a heat treatment process used to harden the surface of low carbon steel parts by infusing carbon into the surface layer of the steel. This process enhances the surface hardness and wear resistance while maintaining a tough and ductile interior. The process is crucial in applications where the wear resistance of the material is critical, such as gears, camshafts, and other high-stress components.

Machine learning uses X-ray diffraction data from polymers to predict the behavior of new materials

Polymers such as polypropylene are fundamental materials in the modern world, found in everything from computers to cars. Because of their ubiquity, it's vital that materials scientists know exactly how each newly developed polymer will perform under different preparation conditions. As described in a new study, which was published in Science and Technology of Advanced Materials, scientists can now use machine learning to determine what to expect from a new polymer. Predicting the mechanical properties of new polymers, such as their tensile strength or flexibility, usually involves putting them through destructive and costly physical tests. However, a team of researchers from Japan, led by Dr. Ryo Tamura, Dr. Kenji Nagata, and Dr. Takashi Nakanishi from the National Institute for Materials Science in Tsukuba, showed that machine learning can predict the material properties of polymers. They developed the method on a group of polymers called homo-polypropylenes, using X-ray diffraction patterns of the polymers under different preparation conditions to provide detailed information about their complex structure and features.

What is age hardening?

Age hardening, also known as precipitation hardening, is a heat treatment process used to increase the strength and hardness materials, particularly metals and alloys. This process increases the yield strength of the material, making it harder and more durable. 

Researchers reveal new method for calculating mechanical properties of solids using machine learning

A research team from Skoltech introduced a new method that takes advantage of machine learning for studying the properties of polycrystals, composites, and multiphase systems. It attained high accuracy, nearly as good as that of quantum-mechanical methods, which are only applicable to materials with less than a few hundred atoms. The new method also benefits from active learning on local atomic environments. The paper is published in the Advanced Theory and Simulations journal. "Many industrial materials are synthesized as polycrystals or multiphase systems. They contain both a single crystal and amorphous components between single crystal grains. The large number of atoms makes it hard to calculate the properties of these systems using modern quantum-mechanical methods. Density functional theory can only be applied to materials with a few hundred atoms."

Strain hardening, also known as work hardening or cold working, is an important industrial process that increases the strength and hardness of a material that do not respond to heat treatment through plastic deformation. This deformation occurs when a material is subjected to mechanical stress, such as compression, tension, or torsion, causing its shape to change permanently.

Read more for the mechanism and applications

Examining how fiber content affects mechanical properties in flax and pineapple leaf fiber-reinforced plastic composites

A new study has compared the reinforcing efficiency of pineapple leaf fiber (PALF) and cultivated flax fiber in poly(butylene succinate) composites. PALF, a less explored but potentially sustainable alternative, outperformed flax at 20 wt.%, showcasing its potential in high-performance bio-composites and aligning with environmental goals. The focus of this research revolves around a comprehensive exploration of the reinforcing capabilities of two distinct natural fibers, namely pineapple leaf fiber (PALF) and cultivated flax fiber, within the context of unidirectional poly(butylene succinate) (PBS) composites. The primary objective is to discern and compare the mechanical efficiency of these fibers as potential reinforcements in polymer composites. Flax, renowned for its robust mechanical properties, is a benchmark for comparison against PALF, which represents a less investigated yet potentially sustainable alternative. To systematically assess their performance, short fibers with a length of 6 mm were incorporated into the composites at varying weight percentages, specifically at 10% and 20% levels.