This study benchmarks multiple data-driven methodologies for predicting relative density (RD) of 316 L stainless steel fabricated via Powder Bed Fusion–Laser Beam (PBF-LB), as part of the ESAFORM Benchmark 2025 AMDmodel initiative. Two datasets (DS-01 and DS-02), each with 256 specimens from a 4-factor, 4-level design of experiments, were produced on different PBF-LB systems equipped with equivalent in-situ infrared (IR) melt-pool pyrometry. Failed builds (RD = 60

As industries such as aerospace, automotive, and marine adopt new materials and designs, the need arises for advanced processing techniques which can shape this material while achieving required part properties. Aluminum alloys, widely used for their low weight, high strength, and corrosion resistance, still face limitations in hardness, wear resistance, and surface fouling. Surface laser processing offers a method to overcome these limitations. Specifically, femtosecond laser ablation offers a high-precision, low-defect method for surface texturing, capable of producing nano- and microscale features. This study investigates the femtosecond laser ablation threshold and material removal behavior of four aluminum alloys—99% pure Al, AA6061, AA7075, and Scalmalloy®—using a 4 W, 400 fs pulse laser at repetition rates up to 1 MHz. The results show significant variability in feature sizes, with AA6061 exhibiting the largest crater diameters depth for and pure Al displaying the greatest ablation depth (up to 4.1 μm) for the same process parameters. Increasing laser power resulted in a linear increase in ablation depth, while pulse repetition rate exhibited an inverse linear trend with depth, contrary to what would be expected from conventional laser processing. X-ray photoelectron spectroscopy (XPS) revealed that laser processing had minimal impact on surface chemistry, with aluminum oxide remaining the dominant component. Differences in physical properties, such as conductivity, reflectivity, and melting point, were identified as the key factors influencing ablation behaviour. These findings underscore the need for material-specific optimization when developing femtosecond laser-based processing techniques for aluminum alloys.

Laser Surface Texturing (LST) has emerged as a critical surface engineering technique for fabricating micro- and nanoscale features that enhance functional properties such as tribological performance, wettability, and thermal management. Ultrafast lasers, particularly femtosecond systems, have significantly advanced LST by enabling high-precision, non-thermal material modification with minimal heat-affected zones. This review provides a comprehensive and critical analysis of physics-based and data-driven modeling approaches used to predict and optimize ultrafast laser texturing processes. Multiphysics simulation tools, including COMSOL, ANSYS, ABAQUS, OpenFOAM, and Zemax, are evaluated for their capability to model heat transfer, phase transitions, stress evolution, and fluid dynamics, while their computational limitations and industrial applicability are critically compared. The integration of machine learning (ML), including Artificial Neural Networks and Random Forest models, is examined for rapid prediction of surface roughness and morphology using both laser parameters and image-derived features. Explainable AI techniques are also discussed for improving model transparency and enabling real-time quality control using camera-based monitoring systems. The review highlights key applications in tribology, wettability control, thermal management, and advanced manufacturing, and identifies hybrid physics-informed ML models as the most promising approach for achieving accurate, scalable, and real-time process prediction. By bridging multiphysics simulation, machine learning, and industrial implementation, this review provides a unified framework for advancing predictive and intelligent ultrafast laser surface texturing.

The temperature dynamics during laser-powder bed fusion (L-PBF) plays a pivotal in governing the microstructure features and mechanical properties of printed NiTi parts. In this study, the influence of nickel concentration on the infrared emission characteristics of four NiTi powder compositions: Ni-50.1 at.% (pre-alloyed), Ni-50.6 at.% (pre-alloyed), Ni-52.1 at.% (pre-alloyed), and Ni-52 at.% (elementally blended) were investigated. A high-speed infrared (IR) pyrometer integrated into an optical microscope was employed for ex-situ acquisitions of voltage signals during controlled heating up to 1450 degrees C under inert atmosphere. Calibration curves were constructed for each NiTi chemical composition, enabling the estimation of spectral emissivity in the short-wave infrared range (SWIR) of 1580 nm to 1800 nm. Experimental results revealed moderate variations in the calibration curves between the pre-alloyed NiTi powders. In contrast, the curves for the blended Ni-52 at.% revealed significant shift towards right, highlight different thermal behavior. Spectral emissivity results showed a steep rise to similar to 1200 degrees C, followed by a steady-state regime for pre-alloyed powders. Overall, a higher emissivity of around 0.52 was observed in the temperature range of 1100 degrees C to 1450 degrees C for the Ni-52.1 at.%, whereas the Ni-50.6 at.% and Ni-50.1 at.% powders exhibited a slightly lower range (0.45-0.48) values. The real-time microstructure visual imaging revealed powder oxidation started approximately after 700 degrees C for all the pre-alloyed powders, followed by powder coalescence beyond 1100 degrees C, which are in consistent with the spectral emissivity variations. X-ray photoelectron spectroscopy (XPS) analysis revealed temperature-dependent surface oxidation behavior in NiTi powder, characterized by the progressive emergence of Ti4+/Ti3+ states, dynamic evolution of lattice and adsorbed oxygen species, and the absence of distinct Ni 2p features across annealed conditions (i.e., 650 degrees C to 1450 degrees C). These findings provide valuable insights into the thermal-dependent spectral emissivity of NiTi powders and supports the development of optimized process parameters for high-quality LPBF of NiTi components.

Nanofluids, suspensions of nanoparticles (NPs) in base fluids, enhance heat transfer in heating and cooling applications. Carbon and aluminium based nanofluids are the most promising materials owing to high stability, excellent thermal properties, low cost and high sustainability. This review critically examines the use of aluminium and carbon-based nanofluids, focusing on their synthesis, stability, thermal properties, and practical applications. Incorporating Al2O3, AlN, graphene, or C NPs into base fluids like water, methanol and ethylene glycol significantly enhances thermal conductivity and heat transfer performance. Carbon-based NPs added to water can result in up to 5000 W/m.K in thermal conductivity from 0.607 W/m.K. The two main synthesis methods namely one-step and two-step processes are discussed. The review also addresses challenges such as sedimentation, agglomeration, and channel blockage, providing insights into strategies for enhancing nanofluid stability and performance. Another limiting factor is the increased viscosity with increasing NP loading, with studies reporting up to a 138 % rise in fluid viscosity, which substantially raises the pumping power required. Future prospects such as using elastocaloric Ni-Ti alloys together with nanofluids for enhanced and sustainable heat transfer are reviewed.

With the development of inkjet-printed electrodes, artificial intelligence-based quality control is essential for classifying inkjet-printed electrodes in a quality control environment. The quality of printed structures can be significantly affected by defects such as cracks, smudging, and misaligned deposits, which can degrade electrical performance and overall device reliability. Traditional quality control methods, including manual inspection and electrical testing, are time-consuming, subjective, and invasive, and they are unsuitable for high-throughput manufacturing environments. This work explores the application of computer vision and deep learning, specifically Convolutional Neural Networks (CNNs) and Feedforward Neural Networks, to automate defect detection and quality classification of inkjet-printed electrodes. To demonstrate the accessibility of deep learning techniques, Neural Architecture Search was implemented, showing the importance of automated model design in achieving high performance without extensive manual tuning or the need for expertise. The CNN models proved to be the most suitable approach for this image classification task, achieving a testing accuracy of 90.9% and a precision of 88.9% for a dataset of 2,406 electrode images containing both high-quality (1,020) and low-quality (1,386) prints.

Developing next-generation anode materials is crucial for advancing lithium-ion batteries, particularly in terms of capacity, safety, and cycling stability. While tin (II) selenide (SnSe) boasts a high theoretical capacity, its practical application is hindered by poor stability and volume expansion during cycling. To address these challenges, we combined commercially available SnSe with Ti3C2Tx MXene, which shows metallic conductivity and excellent binding properties. This study shows that a composite anode comprising SnSe and Ti3C2Tx needs no additional additives and has a minimal dead volume. Electrochemical evaluation demonstrated that our composite outperforms traditional anode materials due to the intrinsic MXene pseudo-capacitance and redox activity. The composite reached 918 mAh/g(total) (1148 mAh/g(SnSe)) at 0.2 C for 170 cycles and 720 mAh/g(total) (900 mAh/g(SnSe)) at 150 cycles at charge-discharge rates of 0.2 C and 0.5 C, respectively. This makes our hybrid structure a promising candidate for high-performance energy storage devices.

Inkjet printing of nanoparticle inks is rising method for fabricating energy storage electrodes and is driven by the demand for supercapacitors and flexible batteries for wearables. The process can be optimized on two fronts, the printing parameters and the ink fabrication. Researchers often lack control over ink formulation and must instead focus on optimizing printing parameters. This study demonstrates that both aspects can be optimized using Pulsed Laser Ablation in Liquid (PLAL) to tailor nanoparticle ink properties, coupled with real-time process monitoring and design of experiments for inkjet printing. Automated in-line monitoring of nanoparticle size and concentration via UV–Vis and DLS measurements every 5 min provided real-time data. The final ink had a mean particle size of 3 nm with a viscosity of 1.3 mPa.s. A design of experiments approach examined the effects of inkjet parameters on print quality on a polymer substrate with optimal printing conditions found to be 30 layers, 40 kHz jetting frequency, and 28 °C nozzle/bed temperature based on consistency in pixel values. The resulting Mn electrodes exhibited pseudocapacitive behavior with initial oxidation leading to stable manganese oxides. XPS analysis of printed electrodes revealed a chemical composition of MnO (64 %), MnO2 (26 %), and Mn2O3 (9 %).

In the realm of materials science and engineering, the pursuit of advanced materials with tailored properties has been a driving goal behind technological progress. Scientific interest in laser powder bed fusion (L-PBF) fabricated NiTi alloy has in recent times seen an upsurge of activity. In this study, we investigate the impact of varying volume energy density (VED) during L-PBF on the microstructure and corrosion behaviour of NiTi alloys in both scan (XY) and built (XZ) planes. The microstructural evolution in both planes was characterized by electron backscatter diffraction and phase change temperatures were characterized using differential scanning calorimeter measurements. Electrochemical experiments were carried out to compare the specimens produced at high laser energy density and low laser energy density. The results indicate that employing high laser energy density in the production of NiTi alloy induces discontinuous dynamic recrystallization, contributing to grain refinement. This in turn enhances the corrosion resistance of the specimen. X-ray photoelectron spectroscopy was employed to examine the type of oxide layer that developed on the samples. The increased resistance to corrosion in a high laser energy density sample can be associated with the formation of a stable and homogeneous passive layer with enriched TiO2 as opposed to Ti2O3. This exploration has unravelled the intricate relationship between VED, the microstructure, and the corrosion properties of L-PBF fabricated NiTi alloys, offering valuable insights into their performance for diverse applications.

Metalloid nanoparticles (MNPs) possess unique physicochemical properties but are challenging to create through biological or chemical routes. Using Pulsed Laser Ablation in Liquid (PLAL), Mg–C MNPs are fabricated from powders. The produced nanocolloids were ablated after the target was removed to tailor the particle size. MNPs with a mean size 300 nm could be reduced to 60 nm. Alternatively, MNPs with a mean size of 60 nm could be increased to 90 nm. The increase/decrease in size is controlled by the laser processing parameters and showcases the ability of PLAL for real-world applications that require meticulous control of size. The as-fabricated nanocolloids were successfully inkjet printed on paper, achieving a low resistivity of 75 Ω/square after 60 prints, highlighting their potential in printed electronics. To address a historical research gap, this article explored the impact of PLAL processing parameters, including fluence (1–2 J/cm2), pulse width (0.2–0.9 ns), repetition rate (10–20 kHz), and pH, factors often overlooked which is partly limiting applications. The influence of powder vs rod target on the PLAL process was addressed revealing that powders produce better size control and are easier to handle but they produce lower colloid concentrations.

Hydrophobicity plays a pivotal role in mitigating surface fouling, corrosion, and icing in critical marine and aerospace environments. By employing ultrafast laser texturing, the characteristic properties of a material’s surface can be modified. This work investigates the potential of an advanced ultrafast laser texturing manufacturing process to enhance the hydrophobicity of aluminium alloy 7075. The surface properties were characterized using goniometry, 3D profilometry, SEM, and XPS analysis. The findings from this study show that the laser process parameters play a crucial role in the manufacturing of the required surface structures. Numerical optimization with response surface optimization was conducted to maximize the contact angle on these surfaces. The maximum water contact angle achieved was 142º, with an average height roughness (Sa) of 0.87 ± 0.075 µm, maximum height roughness (Sz) of 19.4 ± 2.12 µm, and texture aspect ratio of 0.042. This sample was manufactured with the process parameters of 3W laser power, 0.08 mm hatch distance, and a 3 mm/s scan speed. This study highlights the importance of laser process parameters in the manufacturing of the required surface structures and presents a parametric modeling approach that can be used to optimize the laser process parameters to obtain a specific surface morphology and hydrophobicity.

Abstract Surface biofouling, corrosion, and wettability are important parameters to understand and characterize aluminum alloys to prevent the failure in marine environments. Antifouling technologies predominantly encompass chemical and biocidal approaches with negative environmental consequences. Therefore, this study focuses on a new method of producing non‐toxic and effective antifouling and corrosion‐resistant surfaces. In this study, ultrafast laser texturing is used to modify the surface of an aluminum alloy using a femtosecond laser system. Five different unique texture patterns are designed and fabricated using 3 W laser power, 100 kHz pulse repetition rate, and 4 mm s−1 scanning speed in order to make the aluminum surface antifouling and corrosion resistant. The non‐textured sample has a contact angle of 85° while the textured samples have contact angles of up to 157°. The contact angle increased with time up to 90 days of aging. Biofouling assessment is conducted using marine algae Nitzschia ovalis as a marine fouling test organism. A reduction of biofilm coverage of 79% is recorded from the laser‐produced star pattern texture. This study demonstrates that laser‐textured surfaces have the potential to mitigate the formation of biofilms on the surfaces while also providing a mechanism to control the relative level of corrosion.

This study investigates the greater coefficient of Performance (COP) exhibited by the Ni-Ti lattice geometry (LS) over the solid geometry (SS) for solid-state heating and cooling. The LS's advantageous COP can be attributed to factors including variations in phase transformation behavior, a larger surface area facilitating enhanced heat transfer, and a greater volume of water heated per cycle owing to the cavities. Moreover, the LS demands lower compression forces due to its lower mass and geometry, which contribute to its heightened energy efficiency. Remarkably, the LS achieved a maximum temperature span of 11.2°C at 40 kN compression force, whereas the SS required 80 kN to attain a similar 12.9 °C span. Both the SS and LS showcased a non-linear correlation with compression force which was attributed to Lauder's transformation and pseudo-elastic behaviors. Additionally, the temperature span of the SS exhibited symmetrical behavior during heating-cooling cycles. Conversely, the LS displayed asymmetry, with a more substantial temperature change during the cooling phase than the heating phase.

In this study, CuCl2 nanoparticles (NPs) synthesised via pulsed laser ablation in liquid (PLAL) were successfully employed to simultaneously detect glutamine and ammonia, with a limit of detection of 20 nM and up to 1500 ppm, respectively. These NPs hold potential for non-invasive diagnosis and monitoring of various health conditions using urine and sweat samples. The sensing mechanism relied on the plasmon peaks of CuCl2 NPs in the UV range (at 300, 363, and 423 nm), which were used to correlate the levels of glutamine and ammonia concentration with the absorbance. Quasi-spherical CuO and pyramidal CuCl2 NPs were synthesised through laser ablation of Cu powder in liquid IPA and IPA-HCl, respectively. CuCl2 NPs displayed higher ablation efficiency, higher optical absorbance (20-fold), and an 8400-fold increase in colloidal conductivity (0.0005 vs 4.2 mS/cm) compared to CuO NPs. The NP size distribution ranged broadly from 10 nm to less than 100 nm. XPS analysis revealed that ablation in pure IPA resulted in oxidized Cu NPs, while ablation in IPA-HCl liquid medium (12 nM HCl) led to the formation of a combination of metallic copper and CuCl2 NPs that were more conductive and had higher optical absorbance than their oxidized counterparts.

PorosityPorosity in copper filters is sensitive to powder type and space holder material in addition to fabrication processing conditions. This study is focused on the use of two different copper powderCopper powder types (spherical and dendritic) to produce air flow filtersAir flow filtration. The hydraulic pressing method was used to produce copper filters under varying pressure with different spacer (polyvinyl alcohol (PVA)) concentrations. Following compaction, the samples were thermally sintered in two segments at 200 °C and 750 °C. The morphologyMorphology, porosityPorosity, and mechanical propertiesMechanical properties of the sintered samples were characterized. The morphological analysis demonstrated better consolidation and overlapping of copper powderCopper powder particles in samples with a higher weight percentage of the spacer material (PVA). The highest porosityPorosity was achieved in the sample produced using dendritic copper powderCopper powder mixed with the highest weight percentage of PVA (3

In the last few decades, Nitinol (NiTi) actuators have created a massive impact at the commercial level due to their application in various engineering and medical fields. In this paper, an experimental analysis study is presented on commercially manufactured nitinol tubes for performance enhancement. As received tubes were super-elastic at room temperature with Af temperature of 1.7 degrees C. The nitinol tubes were heat treated at 500 degrees C for different time ranging from 30 min to 60 min to raise the Af temperature. Metallography was performed on pristine and heat-treated samples to analyse the changes in the physical properties. XRD analysis revealed the crystalline structure present in the tubes (as received and heat treated) was nitinol cubic (110) while nitinol cubic (211) at room temperature. Moreover, dilatometry was performed which showed thermal expansion coefficients very close as noted in the literature as 11.4x10-6/degrees C. In the last section of this paper, the actuation force of the tubes was experimentally measured and analysed using different springs attached to the tubes connected to a conductive heating stage. A full factorial Design of Experiments (DoE) was used based on factors of time, tem-perature, and spring constant. For a surface temperature of 125 degrees C and a spring constant of 2.39 kN/m, 131 N force was attained from the tube. The maximum actuation force of 145 N was obeserved for surface temperature of 145 degrees C at an exposure time of 60 s with k = 2.39 kN/m.

Since last few decades, Nitinol (NiTi)Nitinol (NiTi)-based shape memory actuators have attained considerable attention due to high power to mass ratio, greater fatigue life, and lower cost. NiTiNitinol (NiTi) wires sheets and tube actuatorsActuators are a useful resource for harvesting heat energy. The present work aims to investigate the Rhombohedral (R-Phase) NiTi tube actuators. Heat treatment and shape setting is performed for setting the shape of the tube. A design test rig is used with the capability to provide conductive and convective heating for cyclic heating and cooling of material. The actuation force of the tubes is gauged by attaching springs of different stiffness. The effect of heat treatment is investigated by analysing the corresponding crystalline structure of tube using XRD technique. Further, the thermal expansion coefficient is investigated for the tubes heat treated at constant temperature as function of time. Moreover, evolution of microstructure as result of heat treatment is studied for visualization of different phases present in the NiTiNitinol (NiTi) tubes.

The concentration of biomolecules such as trypsin and ammonia in bodily fluids are indicators of health conditions including pancreatic diseases and acute liver failure respectively. The maximum UV-Visible intensity and wavelength shifts of Mg-Cu bimetallic oxide nanoparticles (BNPs) were found to be proportional to changes in trypsin and ammonia concentration. The BNPs could selectively detect trypsin in tap water containing ions, ammonia, and glutamine at concentrations as low as 0.0003%v/v. The synthesis of Mg-Cu BNPs was accomplished by ablating a mixture of Mg and Cu powders and Mg and Cu colloids using a Nd:YAG 1064 nm laser in isopropanol alcohol and HCl. The BNPs demonstrated higher optical absorbance intensity in the UV-Visible range compared to their monometallic constituents, making them more suitable for use in biochemical sensing of trypsin and ammonia. The BNPs exhibited a massive 730-fold increase in electrical conductivity compared to monometallic Mg nanoparticles (0.001 mS/cm vs. 0.73 mS/cm). Field emission scanning electron microscopy was used to visualize the NP morphologies, revealing pyramidal and quasi-spherical BNPs with diameters as small as 5 nm.

This article provides an in-depth analysis of various fabrication methods of bimetallic nanoparticles (BNP), including chemical, biological, and physical techniques. The review explores BNP's diverse uses, from well-known applications such as sensing water treatment and biomedical uses to less-studied areas like breath sensing for diabetes monitoring and hydrogen storage. It cites results from over 1000 researchers worldwide and >300 peer-reviewed articles. Additionally, the article discusses current trends, actionable recommendations, and the importance of synthetic analysis for industry players looking to optimize manufacturing techniques for specific applications. The article also evaluates the pros and cons of various fabrication methods, highlighting the potential of plant extract synthesis for mass production of capped BNPs. However, it warns that this method may not be suitable for certain applications requiring ligand-free surfaces. In contrast, physical methods like laser ablation offer better control and reactivity, especially for applications where ligand-free surfaces are critical. The report underscores the environmental benefits of plant extract synthesis compared to chemical methods that use hazardous chemicals and pose risks to extraction, production, and disposal. The article emphasizes the need for life cycle assessment (LCA) articles in the literature, given the growing volume of research on nanotechnology materials. This article caters to researchers at all stages and applies to various fields applying nanomaterials.

Selective laser sintering (SLS) of copper components manufactured via powder metallurgy is widely studied due to minimal material wastage. However, copper has poor optical absorption when exposed to infrared (IR) lasers, such as in laser-based additive manufacturing or laser surface processing. To address this issue, an innovative approach to enhance the optical absorption of copper powders during infrared laser sintering is presented in this study. Carbon nanotubes (CNTs) have several unique properties, including their high surface area, plasmonic response, excellent conductivity, and optical absorption properties. CNTs were mixed with copper powders at different weight percentages using an acoustic method. The resulting Cu-CNT compositions were fabricated into pellets. The Box-Behnken Design of Experiments methodology was used to optimize the IR laser processing conditions for sintering. Spectroscopic analysis was conducted to evaluate the reflection and thermal absorption of the IR wavelengths by the Cu-CNT composites. Density and hardness measurements were taken for the laser-sintered Cu-CNT pellets. The coating of copper powders with CNTs demonstrated enhanced optical absorption and correspondingly reduced reflection. Due to the enhanced optical absorption, increased control and sensitivity of the laser sintering process was achieved, which enabled improvement in the mechanical properties of strength, hardness, and density, while also enabling control over the composite thermal expansion coefficient. A maximum average hardness of 66.5 HV was observed. Indentation test results of the samples revealed maximum tangential and radial stresses of 0.148 MPa and 0.058 Mpa, respectively.