In Situ Investigation of the Cytotoxic and Interfacial Characteristics of Titanium When Galvanically Coupled with Magnesium Using Scanning Electrochemical Microscopy

Characterizing effects of hydrogen ingress in Ti-Mg based hybrid implant materials

Hybrid implants consisting of a permanent Ti-based part combined with a degradable Mg part, are promising solutions to design superior implants by combining the advantages of both materials. In these implants Ti provides high strength while a degradable Mg part is used for temporary structural support, bone growth stimulation or drug delivery purpose. As Mg degrades hydrogen gas is released which can ingress into the Ti part, leading to changes in its properties. The profile of hydrogen distribution is a critical parameter for mechanical stability of Ti, especially in long-term applications. To investigate this in microscopic length scale, Ti6Al4V-Mg0.6Zn0.5Ca hybrid samples prepared using metal injection molding were subjected to saline degradation for a period of 0 to 120 hours. Neutron tomography, synchrotron X-ray tomography and diffraction, SEM and gas fusion technique were used to study the ingress of hydrogen in 3D after the degradation of MgZnCa. A uniform distribution of hydrogen was seen radially while the profile along height matched with macroscopic measurements. Synchrotron XRD confirmed that the room temperature diffusion of hydrogen led to lattice expansion of the BCC β-phase in Ti6Al4V, while no hydride phases were present.

How scanning probe microscopy can be supported by artificial intelligence and quantum computing?

The impact of Artificial Intelligence (AI) is rapidly expanding, revolutionizing both science and society. It is applied to practically all areas of life, science, and technology, including materials science, which continuously requires novel tools for effective materials characterization. One of the widely used techniques is scanning probe microscopy (SPM). SPM has fundamentally changed materials engineering, biology, and chemistry by providing tools for atomic-precision surface mapping. Despite its many advantages, it also has some drawbacks, such as long scanning times or the possibility of damaging soft-surface materials. In this paper, we focus on the potential for supporting SPM-based measurements, with an emphasis on the application of AI-based algorithms, especially Machine Learning-based algorithms, as well as quantum computing (QC). It has been found that AI can be helpful in automating experimental processes in routine operations, algorithmically searching for optimal sample regions, and elucidating structure-property relationships. Thus, it contributes to increasing the efficiency and accuracy of optical nanoscopy scanning probes. Moreover, the combination of AI-based algorithms and QC may have enormous potential to enhance the practical application of SPM. The limitations of the AI-QC-based approach were also discussed. Finally, we outline a research path for improving AI-QC-powered SPM. RESEARCH HIGHLIGHTS: Artificial intelligence and quantum computing as support for scanning probe microscopy. The analysis indicates a research gap in the field of scanning probe microscopy. The research aims to shed light into ai-qc-powered scanning probe microscopy.

Insight into oxygen reduction activity and pathway on pure titanium using scanning electrochemical microscopy and theoretical calculations

HYPOTHESIS

Unlike noble metals, the oxygen reduction reaction (ORR) behavior on Ti is more complicated due to its spontaneously formed oxide film. This film results in sluggish ORR kinetics and tends to be reduced within ORR potential region, causing the weak and multi-reaction coupled current. Though Ti is being used in chemical and biological fields, its ORR research is still underexplored.

EXPERIMENTS

We innovatively employed the modified reactive tip generation-substrate collection (RTG/SC) mode of scanning electrochemical microscopy (SECM) with high efficiency of 97.2 % to quantitatively study the effects of film characteristics, solution environment (pH, anion, dissolved oxygen), and applied potential on the ORR activity and selectivity of Ti. Then, density functional theory (DFT) and molecular dynamics (MD) analyses were employed to elucidate its ORR behavior.

FINDINGS

On highly reduced Ti, film properties dominate ORR behavior with promoted 4e^- selectivity. Rapid film regeneration in alkaline/O₂-saturated conditions inhibits ORR activity. Besides, ORR is sensitive to anion species in neutral solutions while showing enhanced 4e^- reduction in alkaline media. All the improved 4e^- selectivities originate from the hydrogen bond/electrostatic stabilization effect, while the decayed ORR activity by Cl^- arises from the suppressed O₂ adsorption. This work provides theoretical support and possible guidance for ORR research on oxide-covered metals.

Micro-Sized pH Sensors Based on Scanning Electrochemical Probe Microscopy

Monitoring pH changes at the micro/nano scale is essential to gain a fundamental understanding of surface processes. Detection of local pH changes at the electrode/electrolyte interface can be achieved through the use of micro-/nano-sized pH sensors. When combined with scanning electrochemical microscopy (SECM), these sensors can provide measurements with high spatial resolution. This article reviews the state-of-the-art design and fabrication of micro-/nano-sized pH sensors, as well as their applications based on SECM. Considerations for selecting sensing probes for use in biological studies, corrosion science, in energy applications, and for environmental research are examined. Different types of pH sensitive probes are summarized and compared. Finally, future trends and emerging applications of micro-/nano-sized pH sensors are discussed.