Machining complex internal structures in high-hardness materials poses significant challenges, as conventional cutting methods often suffer from excessive tool wear and extended production cycles. This study introduces a hybrid approach that combines rough electrochemical machining (ECM) with precision slotting to efficiently shape involute internal splines in intricate high-hardness components. To enhance electrolyte distribution and stabilize the spline ECM process, the electrolyte flow direction was first evaluated to identify the most effective orientation. Based on this preliminary assessment, three flow field optimisation methods—guided flow head, cathode working teeth, and circular rectifier—were developed and validated through simulation. Experimental setups featured two distinct cathode designs and a dedicated ECM fixture and system. Key process parameters, including electrolyte concentration and composition, machining voltage, and cathode feed rate, were experimentally evaluated to determine optimal conditions for spline ECM. The results demonstrated that an electrolyte concentration of 8

Twinning, where adjacent microstructural grains share a common crystallographic plane, is an important accommodation of plastic deformation within many crystalline materials. Although twins are readily visible using optical microscopy, their crystallographic classification typically requires vacuum-based techniques such as electron backscatter diffraction (EBSD). Here, we demonstrate for the first time that an accessible, non-vacuum approach combining polarized light microscopy (PLM) with an open-source panoptic segmentation model (YOLO) can identify and classify deformation twins in Ti alloys. This work provides the first evidence that PLM integrated with machine learning can be used for twin identification and classification while operating entirely outside a vacuum environment. Because PLM + YOLO detects twins based on morphological and optical features, rather than the precise pixel-level misorientations required by EBSD, the approach captures twins that are poorly developed, blurred, or below EBSD's angular resolution. As a result, the YOLO models achieve up to twice the twin detection rate of EBSD at low strain levels (epsilon <= 1.0%). Regarding twin classification, the work demonstrates that PLM provides sufficient crystallographic information to distinguish tension from compression twins in a subset of cases. However, classification is subject to both theoretical limitations and engineering limitations. In the present implementation, approximately 5% of unclassified twins are attributable to theoretical constraints, while the majority of unclassified cases reflect current engineering limitations that are addressable through improved calibration, segmentation models, and parent-twin identification algorithms. This work therefore establishes PLM integrated with machine learning as a promising foundation for real-time monitoring of microstructural evolution during manufacturing, offering a low-cost solution for materials characterisation.

The advancement of manufacturing processes demands the deployment of new innovative solutions to control polycrystalline material microstructures in cheap, safe and rapid manner. Analysing polycrystalline microstructures requires grain segmentation, which is typically performed on image data or spatially resolved diffraction data collected from carefully prepared specimens. Recently, machine learning (ML) models have been developed to identify grain boundaries and defects from acquired image data. Despite existing ML-based methods showing an improvement over classical computational methods, there is still a significant structure error due to the necessity to have a high accuracy in detected boundaries to avoid grain misidentification. This investigation deploys a simple and open panoptic model, YOLO (You only look once), to directly identify grains from etched surfaces. The model performance was evaluated after appropriate data preparation and training. Even with a limited number of samples, the model outperformed computational methods like the Canny edge algorithm with an intersection-over-union (IoU) score 45 % higher and an aggregated Jaccard index score three times higher. Additionally, an index to measure segmentation quality was introduced, particularly suited for objects with a wide range of sizes, such as microstructural grains. By detecting grains directly instead of relying on boundary detection, common issues-such as failed grains reconstruction due to missing grain boundaries-are avoided, resulting in more accurate grain structures with reduced sensitivity to surface defects. The proposed approach offers significant potential for application to various materials and grain sizes, facilitating the detection of grains, defects, and microstructural artefacts.

Active interactions at liquid-to-solid interfaces can significantly impact the mechanical response of solid substrates. Traditionally, these have been regulated through surface-active media, such as ionic liquids, used in a static (time-invariant) manner that relies on chemical tuning to induce specific mechanochemical responses. This study introduces a novel and sustainable class of Deep Eutectic Solvents (DESs) to demonstrate a dynamic (time-variant) mechanochemical effect, achieved through molecular electro-actuation at the fluid-to-solid interface. The dynamic micro-mechanochemical effect was demonstrated using a DES mixture consisting of citric acid and choline chloride in a 1:1 M ratio, applied to a nickel single-crystal micro-cantilever substrate. The findings show how the DES coating alone induced compressive surface stress, resulting in a 34 % increase in principal stress. More notably, when the substrate surface was polarized with a +/- 5 V potential, electro-actuation amplified this mechanochemical effect by up to 51 %, confirming a clear dynamic response. Further validation was presented at the macroscale in a polycrystalline material setting, where a similar response was observed. These findings give insight into the possible development of smart surfaces coated with DESs, where a single chemical system can dynamically alter materials' mechanical response through simple electro-actuation, offering versatile applications across micro and macro scales.

The residual stress exhibited in post-machined metallic components fabricated by directed energy deposition (DED) determines their final mechanical performance and reliability in mission-critical applications. This study develops a numerical model to predict the final surface residual stress after the orthogonal cutting of DEDproduced IN718, which integrates two critical factors: DED-induced initial residual stress states and microstructure properties. Using the developed modeling procedure, the penetration depth of post-machining into the initial residual stress distribution can be effectively quantified, which aligns with residual stress measurements through X-ray diffraction. The developed model is further employed to quantify the cumulative effects of initial residual stress states and grain size on cutting forces and final surface residual stress profiles. The results suggest that, under the given orthogonal cutting conditions of DED parts, variations in the initial residual stress states of the chip formation region have negligible effects on cutting forces. However, magnitudes of surface compressive residual stress in the longitudinal direction reduce by 21.8 %-52.3 % as the initial residual stress states shift from compressive-dominant to tensile-dominant, and decrease by 23.8 %-54.0 % as the built-in grain size (dg_x) increases from 10 mu m to 100 mu m. With a comprehensive understanding of post-machining DED processes using this numerical modeling procedure, post-treatment techniques can now be tailored to achieve surface residual stress profiles on DED-generated or other additively manufactured metallic components to meet various industrial requirements.

In manufacturing, cutting tools and component integrity are subjected to high-performance thresholds. The role of cutting fluids is pivotal in mitigating heat generation and friction at the tool-workpiece interface. This study explores the application of specifically designed, unconventional, and eco-friendly media, Deep-Eutectic Fluids (DEFs), which provide optimized fluid delivery to the cutting zone, regulating lubrication and cooling, while maintaining the surface integrity of the machined parts. To benchmark DEFs against traditional material removal methods, including dry, and wet (emulsion-based, Hocut 3380) processes, grinding was selected due to its thermal and lubrication demands. The results indicate that DEFs reduce the formation of severely deformed layers by 47% in comparison to conventional water-based coolants exhibiting superior lubricity, yielding more consistent deformation profiles and lower surface roughness. The generated residual stresses are closely comparable to those achieved using water-based metalworking fluids. This was substantiated by micromechanical testing, revealing a coherent failure mechanism at the machined edges for both DEF and wet-cutting media, significantly mitigating the adverse effects of dry machining. These findings highlight DEFs’ potential for industrial-scale adoption as a sustainable alternative in material removal processes, underscoring their capability to enhance process efficiency and environmental sustainability, or as an in-field portable cutting fluid.

This study investigates the surface and electrochemical jet machining (EJM) characteristics of Ti CP1 and Ti-6Al-4V in a deep eutectic solvent-based electrolyte, with a focus on grain size effects, machining mechanisms, and material behaviour under tensile load. Surface roughness data, supported by images and surface reconstructions, highlights the impact of grain size on the surface finish of both materials. Data reveals no significant difference in material removal volumes between Ti CP1 and Ti-6Al-4V, although differences in profile width and are observed. These variations are attributed to the distinct machining mechanisms influenced by the oxide layer thickness in each material. The study also examines the application of EJM for material characterization under tensile load, with images of localized regions showing varying strain levels.

Understanding the effects of manufacturing methods upon materials has driven constant innovation for over 300 years. While our ability to fabricate metallurgical wonders extends into the annals of history our ability to understand the scientific principles where process meets material has been pivotal to improving our capabilities. In this letter we briefly consider this history, comment upon the current state-of-the-art and, most importantly, propose new technologies for future industrial application which have been devised and exploited by the authors. It is hoped that this letter will allow other researchers to engage in this topic and facilitate the emergence of new processcompatible technologies which do not require destructive evaluation. This is particularly timely given the ability to manipulate microstructures with increasing dexterity. This is perhaps best illustrated in additive manufacturing [1] but is also a key consideration when process planning for machining [2], grinding [3] and forming [4].

There is a general separation between the manufacturing processes that add value to materials on the factory floor and the techniques engineers use in the laboratory to evaluate the microstructures and the surface integrity that results. These techniques are often destructive or require a vacuum and are incompatible with production lines. However, this information has intrinsic value and could be exploited to inform production decisions during manufacture. In this study, a novel approach to acquire this information is presented that is underpinned by electrolyte jet machine tool coupled with optical microscopy, which can allow the extraction of both grain-wise partial orientation and morphological information, and crystallographic macro textures in three dimensions. Here, iterative sections are precisely machined into the near surface of a commercially pure titanium alloy using an electrochemical jet and subsequently imaged, allowing the reconstruction of high-fidelity microstructure models rapidly and under ambient conditions. In doing so, new insights into the specific orientation-dependent dissolution mechanisms are offered, and the acquisition of appropriate conditions that result in nanoscale roughness surfaces (avoiding the dominance of pitting and preferential grain removal) is firstly explored. Building on prior work, a piecewise approach is presented to analyse the acquired image stacks to map partial crystal orientations, while different approaches are proposed to account for jet-specific surface artefacts and waviness. This is repeated over 20 layers in an individual specimen and layer-wise orientation maps are used to construct volumetric models of the specimen. These data sets are then explored from the perspective of materials/manufacturing engineers, who may use to this information to effect advancements to materials processing technologies.

Atomically deposited Pt and Co on nano-grooves result in active and stable electrocatalysts for hydrogen evolution and oxygen evolution reactions.

Crystal orientation imaging is generally confined to the laboratory, typically following destructive sectioning, with most current techniques reliant on electron-material interactions that require a vacuum. This information is gathered in a manner that requires careful planning, however a more desirable approach would allow the manufacturer to acquire this data non-destructively at the point of manufacture, with little or no time penalty. We show that coupling a numerically controlled etching method to topographical data processing can be used to spatially map grain orientations over planar and non-planar surfaces. Our method allows the construction of large area orientation maps (approximate to 400 mm2) in agreement with electron backscatter diffraction datasets. We have characterized spatial and angular resolution limits for the technique, which are correlated to length scales of microscale etch surfaces and our ability to measure their geometries. This approach has the potential to augment materials processing technologies, where resultant microstructures require strict control in order to guarantee through-life integrity.

Electrochemical jet manufacturing methods exploit the localised interaction of an electrified jet with a conductive workpiece. This has been exploited by numerous researchers to deposit and remove material. In recent studies, the same approach has been used as an analysis tool to measure and evaluate engineering components. The capability of this manufacturing method is limited by the resolution, which is governed by the diameter of the jet. Although approaches have been taken to reduce the kerf or interaction volume in the process, it is the jet diameter still provides the fundamental limit. In this study, a new method is proposed which takes advantage of a constriction effect to reduce the jet diameter through flow focusing, which occurs in coaxial two-phase flows. A novel nozzle arrangement is presented which demonstrates jets can be constricted by 79% leading to 54% reduction in machined kerf width. The limitations of this method are investigated in the context of fluid dynamic constraints, identifying optimum operating regions to utilise the approach in a computer numerical control machine tool arrangement. This enables continuously varying tool size in-process, which is analogous to other energy beam processes where spot size can be adjusted with a corresponding response influence.

Processing of highly reflective and high thermally conductive materials (Cu, Ag, etc.) by laser powder bed fusion (LPBF) is of increasing interest to broaden the range of materials that can be additively manufactured. However, these alloys are challenged by high reflectivity resulting in unmelted particles and porosity. This is exacerbated for in-situ alloying techniques, where divergent optical properties of blended powders further narrow the stable processing window. One possible route to improved uniformity of initial melting is through coating powders with an optically absorptive layer. In-situ alloying of Ti-Ag was chosen as a model to assess this, given the potential of Ti-Ag as a novel antimicrobial biomedical alloy, facilitating an ideal model to assess this approach. High purity Ag powder was coated with Ti via physical vapour deposition. Barriers to reliable coating were investigated, with agglomeration of particles observed at a sputtering power of 100 W. In-situ laser micro calorimetry demonstrated a significant improvement in melting performance for coated Ag powder, with continuous tracks attained at 280 W vs. 320 W for uncoated powder, and absorptivity increasing from 27 % to 45 % at 320 W incident laser power. Subsequent in-situ alloying of the Ag powder when blended with commercially pure Ti powder demonstrated that improved absorptivity allowed for more uniform densification of the blended powder bed at lower energy density (0.7 & PLUSMN; 1.0 vs 7.1 & PLUSMN; 2.0 % porosity at 133 J.m-1). Ultimately, this offers a promising route to improved alloy development via LPBF, through application of a homogeneous, relevant coating.

In laser powder bed fusion, unconsolidated metal powder on the build plate tends to comprise a proportion of oxidised powder after repeated use. This is generally caused by the generation of oxidised spatter particles during processing which can contaminate the powder bed, and be incorporated into future builds, ultimately undermining part integrity. Oxidised metal powder often results in porosity, poor layer-layer bonding and detrimental oxides in the printed part. This work uses a new chemical etching approach to remove oxides from the surface of oxidised stainless steel spatter powder. It was shown that a ten-fold reduction in oxide area coverage on spatter powder was possible through submersion in a solution of heated Ralph's etchant for one hour. Oxide removal is thought to occur mostly via dissolution of the metal surrounding and underneath oxide islands on the powder, allowing more aggressive oxide removal. LPBF processing was performed using spatter, etched and virgin powder sieved to an identical powder size range. Etched spatter showed a reduced oxide slag layer on track surfaces compared to spatter. In addition, incorporation of powder into tracks appeared improved after chemical etching of the powder. This work demonstrates that chemical etching has the potential to be used to increase the re-usability and lifetime of spatter or heavily used powder from widely used and corrosion resistant stainless steel powder.

In laser powder bed fusion (LPBF), recovered unfused powder from the powder bed often degrades upon sequential processing through mechanisms like thermal oxidation and particle satelliting from ejected weld spatters and particle-laser interactions. Given the sensitivity of LPBF performance and build quality to powder properties, spent powder is generally discarded after a few build cycles, especially for materials that are sensitive towards surface oxidation. This increases feedstock material costs, as well as costs associated with machine downtime during powder replacement. Here, a new method to chemically reprocess spent LPBF metal powder is demonstrated under ambient conditions, using a heavily oxidised Cu powder feedstock recovered from prior LPBF processing as a model material. This is compared to an equivalent virgin Cu powder. The near-surface powder chemistry has been analysed, and it is shown that surface oxide layers present on spent Cu powder can be effectively reset after rapid reprocessing (from 5 to 20 min). Diffuse reflectance changes on etching, reducing for gas-atomised virgin Cu powder due to the formation of anisotropic etch facets, and increasing for heavily oxidised spent Cu as the highly absorptive oxide layers are removed. The mechanism of powder degradation for moisture sensitive materials like Cu has been correlated to the degradation of LPBF deposits, which manifests as widespread and extensive porosity. This extensive porosity is largely eliminated after reprocessing the spent Cu powder. Chemically etched spent powder is therefore demonstrated as a practical feedstock in LPBF in which track density produced is comparable to virgin powder.

Counterfeit parts result in significant losses per annum and are often dangerous, therefore they represent a serious concern for manufacturers and end users alike. Easily written but unclonable watermarks undermine the proposition of the counterfeiter. Here, a rapid electrochemical jet engraving routine is presented to encode robust materials with self‐organized dendritic structures at length scales that can be imaged with a smartphone. Surface defects act as stochastically distributed seeds from which discrete pitting events can be propagated by translating the electrochemical field. While the vascular pathways can be directly written at the macro scale, the formation and propagation of microscale dendritic arms is chaotic, caused by the implicit randomness of the defect seeds and the supply of ions to the surface. The latter is confounded by random perturbations in the flow condition. Each engraved dendrite is unique, stable at high temperature (>500 °C) and can be subjected to rapid image recognition to allow individual mark identification at any point during part production and delivery, or through part lifetime.

Electrochemical jet processing encompasses a group of non-contact and 'tool-less' technologies, relying on localised electrolyte jets to affect changes to the workpiece in a sitespecific manner.This is achieved without thermally or mechanically modifying the underlying material giving rise to a unique class of manufacturing methods.Jet techniques have been applied to remove and deposit material selectively, for example to machine microscale pits and grooves, to process larger surface areas, and to selectively coat materials through a variety of accretion phenomena.The jet itself also has the potential to serve as analysis/metrology tool.The potential to unify a broad range of site-specific manufacturing methods under one platform presents a unique opportunity to enable bespoke programmable surface geometries, finishes and compositions, guided by design and independent of material precondition.This review seeks to enrich the literature by drawing together these interdisciplinary research avenues into a single extensive but critical literature survey, incorporating the process fundamentals and theory, recent developments, and applications of jet processing methods, including hybrid jet processes.Finally, this review attempts to provide new insight and propose the direction of future research with the view to enhancing the areas in which electrochemical jet processes can add value on the factory floor and become widely applied industrial practice.

Deep-eutectic fluids (DEFs) are a novel class of materials that, to date, have been generally used in a single-phase (liquid) for a growing number of applications (e.g., extraction, catalysis, synthesis, etc). In contrast, we present a novel approach to utilise the advantages associated with dual-phase control of DEFs. In this study, we exploit the compositional tunability of DEFs to adapt their functional response. Specifically, we demonstrate the synthesis and application of a crystalline DEF (SolBar) that melts in a controlled manner and under desired conditions. We show how the concept of dual-phase control of a DEF can reduce thermo-mechanical loads developed during shear-based machining operations and offer a substitute for conventional cooling/lubrication means. To this end, we formulated the chemistry of SolBar (a citric acid and choline chloride DEF) so that, as it transforms into liquid, it directly affects lubrication and cooling at the tool-workpiece interface. This was demonstrated by temperature and force measurements. The generation of a tribo-active layer was evidenced through X-ray photoelectron spectroscopy. This layer enhances the lubrication capabilities of the DEF. The concept is not limited to machining, which serves to demonstrate a useful application in this study but can be extended to multiple fields where surfaces are in contact and control of the physico-chemical response of the system is required. Here, we pave the way to new, environmentally friendly, and cost-effective alternatives to conventional tribological media.

The high optical reflectance of Cu at near-infrared wavelengths narrows the process window to fabricate Cu parts by laser powder bed fusion (LPBF). Coating powders with optically absorptive materials has been investigated to improve processability and enhance part properties. However, given the intense heat localization and thin coating layers relative to the powder, the mechanisms of thin film coating interaction in LPBF remain unclear, despite recent work showing the importance of the near-track environment in deposition behavior. In this study, optically absorptive Zn-coated Cu powders were prepared by physical vapor deposition and characterized. Single LPBF tracks were fabricated to elucidate material incorporation phenomena influenced by the volatile Zn coating. It is shown that Zn-coated powder enhances accretion at fastest effective scan speed tested (100 mm/s), where mean track volumes are increased from 0.72 ± 0.05 mm3 (as-received) to 0.91 ± 0.01 mm3 (Zn-coated). This has been correlated to the stronger vapor jet from the volatile Zn-coating, which denudes the surrounding powder bed. This exhausts the powder bed at slower effective scan speeds, causing instability and balling when compared to the as-received powder. It is shown that Zn is localized at the track surface and is undetectable in the track bulk, indicating Zn vaporization on interaction with the incident beam. Zn present mainly occurs through secondary deposition mechanisms like spatter and condensation, rather than in-process alloying. Coating powder feedstocks for use in LPBF therefore affects composition, laser beam absorptivity, and the near-track vapor environment that is known to influence material incorporation behavior.

Measurement of surface geometry is an essential activity in engineering, which is commonly performed by tracing the surface of interest with a mechanical or an optical probe. This is generally performed ex-situ in laboratories designed for metrology. However, inline measurement represents an opportunity to unlock significant efficiency gains throughout manufacturing. Here, a new approach is proposed for in-situ measurement of surface topography using an electrolyte jet as a scanning probe within a precision electrochemical jet machine tool. The electrical resistance of a cylindrical jet impinging on a metal surface is a direct measure of the distance between the surface and the electrified nozzle, allowing profiling of surface shape. This enables integrated on-machine measurement in the electrochemical jet apparatus with tuneable sensitivity and vertical resolution, achieving accuracy of 4.4% with the calibration proposed here. The developed measurement system provides an accurate and low-cost surface imaging approach that can be easily integrated with industrial manufacturing processes.