Yuebin Guo

Bio: Yuebin Guo is an academic researcher from University of Alabama. The author has contributed to research in topics: Surface integrity & Residual stress. The author has an hindex of 45, co-authored 157 publications receiving 6054 citations. Previous affiliations of Yuebin Guo include RWTH Aachen University & University of California, Berkeley.

Biodegradable Orthopedic Magnesium-Calcium (MgCa) Alloys, Processing, and Corrosion Performance

Abstract: Magnesium-Calcium (Mg-Ca) alloy has received considerable attention as an emerging biodegradable implant material in orthopedic fixation applications. The biodegradable Mg-Ca alloys avoid stress shielding and secondary surgery inherent with permanent metallic implant materials. They also provide sufficient mechanical strength in load carrying applications as opposed to biopolymers. However, the key issue facing a biodegradable Mg-Ca implant is the fast corrosion in the human body environment. The ability to adjust degradation rate of Mg-Ca alloys is critical for the successful development of biodegradable orthopedic implants. This paper focuses on the functions and requirements of bone implants and critical issues of current implant biomaterials. Microstructures and mechanical properties of Mg-Ca alloys, and the unique properties of novel magnesium-calcium implant materials have been reviewed. Various manufacturing techniques to process Mg-Ca based alloys have been analyzed regarding their impacts on implant performance. Corrosion performance of Mg-Ca alloys processed by different manufacturing techniques was compared. In addition, the societal and economical impacts of developing biodegradable orthopedic implants have been emphasized.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Introduction to the Finite Element Method

Abstract: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

Metallic implant biomaterials

Abstract: Human tissue is structured mainly of self-assembled polymers (proteins) and ceramics (bone minerals), with metals present as trace elements with molecular scale functions. However, metals and their alloys have played a predominant role as structural biomaterials in reconstructive surgery, especially orthopedics, with more recent uses in non-osseous tissues, such as blood vessels. With the successful routine use of a large variety of metal implants clinically, issues associated with long-term maintenance of implant integrity have also emerged. This review focuses on metallic implant biomaterials, identifying and discussing critical issues in their clinical applications, including the systemic toxicity of released metal ions due to corrosion, fatigue failure of structural components due to repeated loading, and wearing of joint replacements due to movement. This is followed by detailed reviews on specific metallic biomaterials made from stainless steels, alloys of cobalt, titanium and magnesium, as well as shape memory alloys of nickel–titanium, silver, tantalum and zirconium. For each, the properties that affect biocompatibility and mechanical integrity (especially corrosion fatigue) are discussed in detail. Finally, the most critical challenges for metallic implant biomaterials are summarized, with emphasis on the most promising approaches and strategies.

Metal Additive Manufacturing: A Review of Mechanical Properties

Abstract: This article reviews published data on the mechanical properties of additively manufactured metallic materials. The additive manufacturing techniques utilized to generate samples covered in this review include powder bed fusion (e.g., EBM, SLM, DMLS) and directed energy deposition (e.g., LENS, EBF3). Although only a limited number of metallic alloy systems are currently available for additive manufacturing (e.g., Ti-6Al-4V, TiAl, stainless steel, Inconel 625/718, and Al-Si-10Mg), the bulk of the published mechanical properties information has been generated on Ti-6Al-4V. However, summary tables for published mechanical properties and/or key figures are included for each of the alloys listed above, grouped by the additive technique used to generate the data. Published values for mechanical properties obtained from hardness, tension/compression, fracture toughness, fatigue crack growth, and high cycle fatigue are included for as-built, heat-treated, and/or HIP conditions, when available. The effects of test...