Biomedical Alloys and Physical Surface Modifications: A Mini-Review

Biomedical alloys are essential parts of modern biomedical applications. However, they cannot satisfy the increasing requirements for large-scale production owing to the degradation of metals. Physical surface modification could be an effective way to enhance their biofunctionality. The main goal of this review is to emphasize the importance of the physical surface modification of biomedical alloys. In this review, we compare the properties of several common biomedical alloys, including stainless steel, Co–Cr, and Ti alloys. Then, we introduce the principle and applications of some popular physical surface modifications, such as thermal spraying, glow discharge plasma, ion implantation, ultrasonic nanocrystal surface modification, and physical vapor deposition. The importance of physical surface modifications in improving the biofunctionality of biomedical alloys is revealed. Future studies could focus on the development of novel coating materials and the integration of various approaches.

APAIC Report on the Holocode Crisis

The APAIC Report on the Holocode Crisis is a short story that imagines the future of machine-readable data encodings. In this story, I speculate about the next stage in the development of data encoding patterns: after barcodes and QR codes, the invention of “holocodes” will make it possible to store unprecedented amounts of data in a minuscule physical surface. As a collage of nested fictional materials (including ethnographic fieldnotes, interview transcripts, OCR scans, and intelligence reports) this story builds on the historical role of barcodes in supporting consumer logistics and the ongoing deployment of QR codes as anchors for the platform economy, concluding that the geopolitical future of optical governance is tied to unassuming technical standards such as those formalizing machine-readable representations of data.

Studying the fractal properties of Ceres

Currently, the asteroid Ceres belongs to small celestial bodies with the most well-known physical parameters. The study of the structural and real properties of Ceres is an urgent and modern task, the solution of which will make it possible to develop the evolutionary theory of a minor planet. In this work, the fractal properties of the dwarf planet Ceres were analyzed using data from the Dawn space mission. Using the expansion in a harmonic series in spherical functions the height parameters of the structural model of Ceres, a 3D model of Ceres was constructed. The analysis showed that the resulting system has a complex multiparameter fractal configuration. The study of such objects requires the use of harmonic multiparameter methods. Multivariate fractal analysis allows to represent systems similar to the Ceres model in the form of a spectrum of fractal dimensions. The advantage of fractal analysis is the ability to explore local areas of the physical surface. In this work, the Minkowski algorithm was used for this purpose. At the final stage, an overdetermined system was solved for various local areas of topocentric information in order to postulate a model that takes into account external measures. Fractal dimensions D are determined for local regions and the entire model of the planet. Fractal dimensions vary from 1.37 to 1.92 depending on the longitude and latitude of Ceres. The main results are as follows: 1) the structure of the Ceres surface varies more strongly in longitude; 2) the structure of Ceres is smoother in latitude; 3) the coefficient of self-similarity changes rather quickly in longitude, which indicates that different local regions of the minor planet were formed under the influence of various physical processes. It is necessary to emphasize that the resulting fractal dimensions are significantly scattered both in longitude and latitude of Ceres. This fact confirms the presence of a complex structure in the spatial model of a minor planet. This also applies to the actual physical surface of Ceres. The results of the work allow us to conclude that fractal modeling can give independent values of the fractal dimension both for the entire model of Ceres and for its local macrostructural regions.

Slab-geometry surface waves on steep gradients and the origin of related numerical issues in a variety of ICRF codes

In the ion cyclotron range of frequencies, electromagnetic surface waves are physically relevant for wave–filament interactions, parasitic edge losses and sheath–plasma waves. They are also important numerically, where non-physical surface waves may occur as side effects of slab-geometry approximations. We give new, completely general, mathematical techniques to construct dispersion relations for electromagnetic surface waves between any two media, isotropic or anisotropic, and first-order corrections for when the material interface is steep but continuous. We discuss numerical issues (localized non-convergence, undesired power generation) that arise in numerical calculations due to the presence of surface waves.

Improving classification based on physical surface tension-neural net for the prediction of psychosocial-risk level in public school teachers

Background Psychosocial risks, also present in educational processes, are stress factors particularly critical in state-schools, affecting the efficacy, stress, and job satisfaction of the teachers. This study proposes an intelligent algorithm to improve the prediction of psychosocial risk, as a tool for the generation of health and risk prevention assistance programs. Methods The proposed approach, Physical Surface Tension-Neural Net (PST-NN), applied the theory of superficial tension in liquids to an artificial neural network (ANN), in order to model four risk levels (low, medium, high and very high psychosocial risk). The model was trained and tested using the results of tests for measurement of the psychosocial risk levels of 5,443 teachers. Psychosocial, and also physiological and musculoskeletal symptoms, factors were included as inputs of the model. The classification efficiency of the PST-NN approach was evaluated by using the sensitivity, specificity, accuracy and ROC curve metrics, and compared against other techniques as the Decision Tree model, Naïve Bayes, ANN, Support Vector Machines, Robust Linear Regression and the Logistic Regression Model. Results The modification of the ANN model, by the adaptation of a layer that includes concepts related to the theory of physical surface tension, improved the separation of the subjects according to the risk level group, as a function of the mass and perimeter outputs. Indeed, the PST-NN model showed better performance to classify psychosocial risk level on state-school teachers than the linear, probabilistic and logistic models included in this study, obtaining an average accuracy value of 97.31%. Conclusions The introduction of physical models, such as the physical surface tension, can improve the classification performance of ANN. Particularly, the PST-NN model can be used to predict and classify psychosocial risk levels among state-school teachers at work. This model could help to early identification of psychosocial risk and to the development of programs to prevent it.

Limited Accessibility to Surface Area Generated by Thermal Pretreatment of Electrodes Reduces Its Impact on Redox Flow Battery Performance

Thermal oxidation of carbon electrodes is a common approach to improving flow battery performance. Here, we investigate how thermal pretreatment increases electrode surface area and the effect this added surface area has on electrode performance. Specifically, we rigorously analyze the surface area of Freudenberg H23 carbon paper electrodes, a binder-free model material, by systematically varying pretreatment temperature (400, 450, and 500 °C) and time (0 to 24 h) and evaluating changes in the physical, chemical, and electrochemical properties of the electrodes. We compare physical surface area, measured by a combination of gas adsorption techniques, to surface area measured via electrochemical double layer capacitance. We find good agreement between the two at shorter treatment times (0-3 h); however, at longer treatment times (6-24 h), the surface area measured electrochemically is an underestimate of the physical surface area. Further, we use gas adsorption to measure a pore size distribution and find that the majority of pores are in the micropore range (< 2 nm), and ca. 60% of the added surface area are in the sub-nanometer (< 1 nm) pore size range. We postulate that the solvated radii and imperfect wetting of electrochemical species may hinder active species transport into these recessed regions, explaining the discrepancy between electrochemical and physical surface area. These results are supported with in situ flow cell testing, where single-electrolyte polarization measurements show little improvement with increasing surface area. Further, using a simple convection-reaction model to simulate electrode overpotential as a function of surface area, we find that increasing surface area improves the performance to a point, but the mass transport to and the catalytic activity of the reaction sites offer greater comparative impact. Ultimately, this work aims to inform the design of electrodes that offer maximal accessible surface area to redox species.

Limited Accessibility to Surface Area Generated by Thermal Pretreatment of Electrodes Reduces Its Impact on Redox Flow Battery Performance

Thermal oxidation of carbon electrodes is a common approach to improving flow battery performance. Here, we investigate how thermal pretreatment increases electrode surface area and the effect this added surface area has on electrode performance. Specifically, we rigorously analyze the surface area of Freudenberg H23 carbon paper electrodes, a binder-free model material, by systematically varying pretreatment temperature (400, 450, and 500 °C) and time (0 to 24 h) and evaluating changes in the physical, chemical, and electrochemical properties of the electrodes. We compare physical surface area, measured by a combination of gas adsorption techniques, to surface area measured via electrochemical double layer capacitance. We find good agreement between the two at shorter treatment times (0-3 h); however, at longer treatment times (6-24 h), the surface area measured electrochemically is an underestimate of the physical surface area. Further, we use gas adsorption to measure a pore size distribution and find that the majority of pores are in the micropore range (< 2 nm), and ca. 60% of the added surface area are in the sub-nanometer (< 1 nm) pore size range. We postulate that the solvated radii and imperfect wetting of electrochemical species may hinder active species transport into these recessed regions, explaining the discrepancy between electrochemical and physical surface area. These results are supported with in situ flow cell testing, where single-electrolyte polarization measurements show little improvement with increasing surface area. Further, using a simple convection-reaction model to simulate electrode overpotential as a function of surface area, we find that increasing surface area improves the performance to a point, but the mass transport to and the catalytic activity of the reaction sites offer greater comparative impact. Ultimately, this work aims to inform the design of electrodes that offer maximal accessible surface area to redox species.