Search Results (21)

Additive manufacturing (AM) has emerged as a transformative technology in dentistry, enabling the production of patient-specific dental applications with reduced costs and fabrication times. Despite the growth of applications, a consolidated understanding of current 3D printing technologies, materials, and performance in dental settings remains fragmented. Here, we perform a Systematic Literature Review (SLR) using the PRISMA protocol, retrieving 19 closely related primary studies. The evidence is synthesized across three axes: application domain, AM technology, and critical quality parameters. Dental restorations, prosthetics, crowns, and implants are the most common applications, while fused deposition modeling, stereolithography, digital light processing, selective laser sintering, and laser-directed energy deposition are the most used technologies. AM materials include polymers, metals, and emerging biomaterials. Key quality determinants include dimensional accuracy, wear and corrosion resistance, and photosensitivity. Notably, biocompatibility and cytotoxicity remain underexplored yet critical factors for ensuring long-term clinical safety. The evidence also suggests a lack of in vivo studies, insufficient tribological and microbiological testing, including limited data degradation pathways of AM materials under oral conditions. Understanding that there are disconnects between the realization of the clinical and the economic benefits of 3D printing in dentistry, future research requires standardized testing frameworks and long-term biocompatibility validation. Full article

Additive Manufacturing (AM) techniques, such as Fused Deposition Modeling (FDM) and Stereolithography (SLA), are increasingly adopted in various high-demand sectors, including the aerospace, biomedical engineering, and automotive industries, due to their design flexibility and material adaptability. However, the tribological performance and surface integrity of parts manufactured by AM are the biggest functional deployment challenges, especially in wear susceptibility or load-carrying applications. The current review provides a comprehensive overview of the tribological challenges and surface engineering solutions inherent in FDM and SLA processes. The overview begins with a comparative overview of material systems, process mechanics, and failure modes, highlighting prevalent wear mechanisms, such as abrasion, adhesion, fatigue, and delamination. The effect of influential factors (layer thickness, raster direction, infill density, resin curing) on wear behavior and surface integrity is critically evaluated. Novel post-processing techniques, such as vapor smoothing, thermal annealing, laser polishing, and thin-film coating, are discussed for their potential to endow surface durability and reduce friction coefficients. Hybrid manufacturing potential, where subtractive operations (e.g., rolling, peening) are integrated with AM, is highlighted as a path to functionally graded, high-performance surfaces. Further, the review highlights the growing use of finite element modeling, digital twins, and machine learning algorithms for predictive control of tribological performance at AM parts. Through material-level innovations, process optimization, and surface treatment techniques integration, the article provides actionable guidelines for researchers and engineers aiming at performance improvement of FDM and SLA-manufactured parts. Future directions, such as smart tribological, sustainable materials, and AI-based process design, are highlighted to drive the transition of AM from prototyping to end-use applications in high-demand industries. Full article

Conventional lubricant testing methods focus on lab-scale constant contact conditions, which cannot represent the scenarios in actual hot-stamping processes. In recent studies, the concept of the ‘digital characteristics (DC)’ of metal forming has been proposed by unveiling the intrinsic nature of the specific forming, which presents a timely solution to address this challenge. In this work, the transient behaviours of three dedicated lubricants during the hot stamping of AA6111 material were investigated considering the effects of various contact conditions using an advanced friction testing system, and the interactive friction modelling was established accordingly. The lubricant limit diagram (LLD) of each lubricant was then generated to quantitatively evaluate the lubricant performance following the complex tool–workpiece interactions based on the tribological DCs, and a detailed investigation on the lubricant failure regions was conducted based on the interactive friction modelling. Finally, the industrial application index (IAI) was proposed and defined as a comprehensive evaluation of lubricant applications in the industry, and the most suitable lubricant was identified among the three candidates for mass production. Full article

This work aims to explore the effect of side load and rotational speed on the tribological behavior of a novel ceramic–epoxy composite in Kevlar matrix casing lining that is in contact with a rotating drillpipe tool joint (DP-TJ) coated with the same composite. Three rotational speeds (65, 115, and 154 rpm) and three side loads (500, 700, and 1000 N) were considered under water-based mud (WBM) lubrication. Wear depths, volumes, and specific casing wear rates (K) were determined for each combination of speed and load. The wear depth and K were found to increase with an increasing applied side load. However, the specific casing wear rate at the rotational speed of 115 rpm was found to be the lowest among the three speeds. This is mainly due to a probable lubrication regime change from boundary lubrication at 65 rpm to hydrodynamic lubrication with a thick lubricant film at 115 rpm. The digital microscope images were used to determine the wear mechanism, showing that at low speeds, the main mechanism was abrasive wear, but the increase in the speed brought about more adhesive wear. In contrast, the change in the side load does not affect the wear mechanism of the casing. Scanning electron microscopy and energy-dispersive spectroscopy (EDS) were used to analyze the surface and composition of the novel material before and after the wear tests. Full article

In this study, copper(II) oxide, titanium dioxide and yttrium(III) oxide nanoparticles were added to Group III-type base oil formulated with overbased calcium sulfonate. The nanosized oxides were treated with ethyl oleate surface modification. The tribological properties of the homogenized oil samples were tested on a linear oscillating tribometer. Friction was continuously monitored during the tribological tests. A surface analysis was performed on the worn samples: the amount of wear was determined using a digital optical and confocal microscope. The type of wear was examined with a scanning electron microscope, while the additives adhered to the surface were examined with energy-dispersive X-ray spectroscopy. From the results of the measurements, it can be concluded that the surface-modified nanoparticles worked well with the overbased calcium sulfonate and significantly reduced both wear and friction. In the present tribology system, the optimal concentration of all three oxide ceramic nanoadditives is 0.4 wt%. By using oxide nanoparticles, friction can be reduced by up to 15% and the wear volume by up to 77%. Overbased calcium sulfonate and oxide ceramic nanoparticles together form a lower friction anti-wear boundary layer on the worn surfaces. The results of the tests represent another step toward the applicability of these nanoparticles in commercial engine lubricants. It is advisable to further investigate the possibility of formulating nanoparticles into the oil. Full article

This research addresses the development of a formalized approach to dental material selection (DMS) in manufacturing removable complete dentures (RDC). Three types of commercially available polymethyl methacrylate (PMMA) grades, processed by an identical Digital Light Processing (DLP) 3D printer, were compared. In this way, a combination of mechanical, tribological, technological, microbiological, and economic factors was assessed. The material indices were calculated to compare dental materials for a set of functional parameters related to feedstock cost. However, this did not solve the problem of simultaneous consideration of all the material indices, including their significance. The developed DMS procedure employs the extended VIKOR method, based on the analysis of interval quantitative estimations, which allowed the carrying out of a fully fledged analysis of alternatives. The proposed approach has the potential to enhance the efficiency of prosthetic treatment by optimizing the DMS procedure, taking into consideration the prosthesis design and its production route. Full article

The dispersion stability of carbon-based solid lubricants/lubricating oils remains a challenge to overcome. Recently, novel processing routes were developed to obtain 2D turbostratic graphite particles via solid-state reactions between B₄C and Cr₃C₂ (GBC) and between SiC and Fe (GSF) that present outstanding tribological properties in a dry scenario, as well as functionalized graphene (GNH). This work investigated the suspension stability of GBC and GSF particles (0.05 wt.%) dispersed in a low-viscosity polyol ester lubricating oil and their tribological performance. Ammonia-functionalized graphene (GNH) particles were also used as a reference. In order to evaluate the dispersion stability, in addition to the classical digital image technique, a much more assertive, reliable, quantitative and rarely reported in the literature technique was used, i.e., the STEP^TM (Space and Time-resolved Extinction Profiles) technology. Reciprocating sphere-on-flat tribological tests were carried out, in which before contact, 0.2 μL of pure oil and suspension (POE + 0.05 wt.% of solid lubricant) was applied on a flat surface. The results showed that the GBC particles remained remarkably stable and reduced the sphere wear rate by 61.8%. From the tribosystem point of view, the presence of GBC and GSF reduced the wear rate by 18.4% and 2.2%, respectively, with respect to the pure oil, while the GNH particles increased the wear rate by 4.2%. Furthermore, the wear rate was improved due to the highly disordered carbon tribolayer formation identified on both surfaces. Full article

In sustainable tribology, researchers are investigating methods to enhance tribological performance by incorporating nanoparticles into lubricants. However, one potential drawback of this strategy is increased lubricant viscosity. The current study aimed to assess the impact of these nanoparticles on the viscosity and coefficient of friction (COF) of the nanolubricants. Three different nanolubricants were synthesized through a two-step process, including mono-nanolubricants (Al₂O₃/DEC PAG and SiO₂/DEC PAG) and hybrid nanolubricants (Al₂O₃-SiO₂/DEC PAG), at volume concentrations between 0.01% and 0.05%. The viscosity and shear flow behavior of these nanolubricants were evaluated using a digital rheometer, while the COF was measured using a Koehler four-ball tribometer. All the nanolubricants showed Newtonian behavior during the experiments. The dynamic viscosity velocity increment of SiO₂/DEC PAG was found to be the lowest (1.88%), followed by Al₂O₃-SiO₂/DEC PAG (2.74%) and Al₂O₃/DEC PAG (3.56%). The viscosity indices of all the nanolubricants were improved only at higher concentrations. At a volume concentration of 0.03%, the Al₂O₃-SiO₂/DEC PAG nanolubricant reduced the COF by up to 8.1%. The results showed that the combination of nanoparticles, temperature, and volume concentration significantly influenced the viscosity and COF of nanolubricants. This study provides essential information for developing high-performance nanolubricants with improved viscosity and COF and advancing environmentally friendly tribology solutions. Full article

Zirconia-based materials are widely used in dentistry due to their biocompatibility and suitable mechanical and tribological behavior. Although commonly processed by subtractive manufacturing (SM), alternative techniques are being explored to reduce material waste, energy consumption and production time. 3D printing has received increasing interest for this purpose. This systematic review intends to gather information on the state of the art of additive manufacturing (AM) of zirconia-based materials for dental applications. As far as the authors know, this is the first time that a comparative analysis of these materials’ properties has been performed. It was performed following the PRISMA guidelines and using PubMed, Scopus and Web of Science databases to select studies that met the defined criteria without restrictions on publication year. Stereolithography (SLA) and digital light processing (DLP) were the techniques most focused on in the literature and the ones that led to most promising outcomes. However, other techniques, such as robocasting (RC) and material jetting (MJ), have also led to good results. In all cases, the main concerns are centered on dimensional accuracy, resolution, and insufficient mechanical strength of the pieces. Despite the struggles inherent to the different 3D printing techniques, the commitment to adapt materials, procedures and workflows to these digital technologies is remarkable. Overall, the research on this topic can be seen as a disruptive technological progress with a wide range of application possibilities. Full article

In the present work, Fe/Cu composite coatings were fabricated by electro-explosive spraying technology (EEST), with good lubrication performance and high wear resistance. The microstructure and morphology were characterized by an energy-dispersive spectrometer (EDS), 3D digital microscope, and scanning electron microscope (SEM) coupled with electron backscattered diffraction (EBSD). Mechanical properties and tribological performance were measured using a micro Vickers hardness tester, universal testing machine, and universal friction and wear testing machine. The composite coating had low porosity with a minimum value of 0.7%, high microhardness with a maximum value of 729.9 HV0.2, high bonding strength with a maximum average value of 55.25 MPa, and good wear resistance and self-lubrication, and the ratio of soft metal and hard metal in the coatings was controllable. Under dry friction conditions, the friction reduction mechanism was that there were both metallic oxide particles and soft metal attached in the friction pairs. When the ratio of soft metal in the composite coating was higher, the self-lubricating performance of the coating was better, with adhesive wear as the main wear mechanism; when the ratio of hard metal was higher, the wear resistance was better and the wear mechanism was mainly abrasive wear. Full article

Soft polymers such as the investigated polyurethane, characterized by low Young’s moduli and prone to high shear deflection, are frequently applied in pneumatic cylinders. Their performance and lifetime without external lubrication are highly determined by the friction between seal and shaft and the wear rate. FEM simulation has established itself as a tool in seal design processes but requires input values for friction and wear depending on material, load, and velocity. This paper presents a tribological test configuration for long stroke, reciprocating movement, allowing the generation of data which meet the requirements of input parameters for FEM simulations without the geometrical influences of specific seal profiles. A numerical parameter study, performed with an FEM model, revealed the most eligible sample geometry as a flat, disc-shaped sample of the polymer glued on a stiff sample holder. At the same time, the study illustrates that the sensitivity of the contact pressure distribution to Poisson’s ratio and CoF can be minimized by the developed and verified setup. It ensures robust, reliable, and repeatable experimental results with uniform contact pressures and constant contact areas to be used in databases and FEM simulations of seals, enabling upscaling from generically shaped samples to complex seal profiles. Full article

Intermetallic alloys such as titanium aluminides (TiAl) are potential materials for aerospace applications at elevated temperatures. TiAl intermetallics have low weight and improved efficiency under aggressive environments. However, there is limited information about wear behavior of these alloys and their microstructure. The present work aims to study the influence of the microstructure in the tribological behavior of TiAl intermetallic alloy (45Al-2Mn-2Nb(at%)-0.8 vol%TiB₂). Wear tests were performed on samples manufactured by centrifugal casting (CC) and hot isostatic pressure (HIP). Reciprocating sliding wear test was carried out for TiAl, it was combined with different loads and frequencies. Wear tracks were analyzed through opto-digital microscopy and electron microscopy (SEM). The results obtained reveal that CC intermetallics present the lowest volume wear lost, approximately 20% less than HIP intermetallics. This good behavior could be related to the high hardness material, associated with the main microstructure where CC intermetallic has nearly lamellar microstructure and HIP intermetallics present duplex microstructure. Full article

The ever-increasing amount of data generated from experiments and simulations in engineering sciences is relying more and more on data science applications to generate new knowledge. Comprehensive metadata descriptions and a suitable research data infrastructure are essential prerequisites for these tasks. Experimental tribology, in particular, presents some unique challenges in this regard due to the interdisciplinary nature of the field and the lack of existing standards. In this work, we demonstrate the versatility of the open source research data infrastructure Kadi4Mat by managing and producing FAIR tribological data. As a showcase example, a tribological experiment is conducted by an experimental group with a focus on comprehensiveness. The result is a FAIR data package containing all produced data as well as machine- and user-readable metadata. The close collaboration between tribologists and software developers shows a practical bottom-up approach and how such infrastructures are an essential part of our FAIR digital future. Full article

Tribological performance of knee components are strongly related to the surface characteristics. Primarily, the roughness and its 3D distribution on the surfaces affect the joint performance. One of the main limitations related to the tribological study of knee prostheses is that most of the research studies report in vitro or in silico results, as knee retrievals are difficult to find or are too damaged to be analyzed. This paper is focused on the roughness characterization of retrieved metal femoral components of total knee replacements (TKR) by means of a rugosimeter and involving digital methods to reconstruct the 3D topography of the studied surfaces. The aim of this study is to investigate how changes and distribution of roughness are correlated between the medial vs. the lateral part and how the resulting digital topography can give insights about the wear behavior. Full article

The recent decline in crude oil prices due to global competition and COVID-19-related demand issues has highlighted the need for the efficient operation of an oil and gas plant. One such avenue is accurate predictions about the remaining useful life (RUL) of components used in oil and gas plants. A tribosystem is comprised of the surfaces in relative motion and the lubricant between them. Lubricant oils play a significant role in keeping any tribosystem such as bearings and gears working smoothly over the lifetime of the oil and gas plant. The lubricant oil needs replenishment from time to time to avoid component breakdown due to the increased presence of wear debris and friction between the sliding surfaces of bearings and gears. Traditionally, this oil change is carried out at pre-determined times. This paper explored the possibilities of employing machine learning to predict early failure behavior in sensor-instrumented tribosystems. Specifically, deep learning and tribological data obtained from sensors deployed on the components can provide more accurate predictions about the RUL of the tribosystem. This automated maintenance can improve the overall efficiency of the component. The present study aimed to develop a deep learning-based digital twin for accurately predicting the RUL of a tribosystem comprised of a ball bearing-like test apparatus, a four-ball tester, and lubricant oil. A commercial lubricant used in the offshore oil and gas components was tested for its extreme pressure performance, and its welding load was measured using a four-ball tester. Three accelerated deterioration tests was carried out on the four-ball tester at a load below the welding load. Based on the wear scar measurements obtained from the experimental tests, the RUL data were used to train a multivariate convolutional neural network (CNN). The training accuracy of the model was above 99%, and the testing accuracy was above 95%. This work involved the model-free learning prediction of the remaining useful lifetime of ball bearing-type contacts as a function of key sensor input data (i.e., load, friction, temperature). This model can be deployed for in-field tribological machine elements to trigger automated maintenance without explicitly measuring the wear phenomenon. Full article