Nïkhil Gupta

Additive Manufacturing (AM), also known as 3D printing, offers several advantages, including on-site production, enhanced throughput, and efficient use of raw materials. However, the rise in its usage has also led to an increase in potential threats that aim to disrupt the printing process. These attacks can subtly alter the design (CAD or STL) files or machine instructions (g-code), which can cause significant economic and reputational harm to the victim company. Current detection techniques, based on acoustic, magnetic, and accelerationbased side-channel analysis, have proven to be ineffective. Although power side-channel analysis is more effective than other means, it is expensive and not scalable. This paper proposes a novel detection method, SCREAM, that assumes the user has access to a trusted STL source and an untrusted g-code. SCREAM leverages the pulse trains sent to the motors to reconstruct the executing g-code. To ensure the safe and accurate execution of g-code, a three-level comparison is performed between recovered and untrusted g-code, as well as trusted STL ensuring successful detection of any anomalies present in the executing g-code. Our testing has shown that this method can detect a range of existing attacks on AM, including malicious firmware manipulation, FLAW3D, and Needle in a Haystack.

This work features a dataset intended to aid in the development of processing parameters for particulate composite materials for additive manufacturing (AM) using digital light processing (DLP) method. Hollow glass microspheres (HGMs) are used as particulate fillers to manufacture syntactic foam composites. The standard thermosetting resins have a recommended set of 3D printing parameters. However, when the particles are mixed to 3D print composites, the mixture properties change, and the processing parameters need to be adjusted according to the particle volume fraction, size and other parameters. This dataset provides rheological measurements on the neat resin and resin-HGM composite mixtures intended for vat photopolymerization (VP) based DLP method. Three HGM density grades (0.13, 0.23, and 0.31 g/cm³ true particle densities) were examined at 10, 20, and 40 vol.% to capture the effects of particle density and volume fraction on resin flow behavior. Viscosity was measured using an Anton Paar MCR702 analyzer at a range of shear rates (1-50 s⁻¹) and temperatures (35-125 °C), generating 50 independent data files for 5 trials repeated for each of the 10 compositions. The dataset records the coupled influence of temperature and shear rate for each composition, providing a foundation for modeling viscosity-shear rate-temperature-composition relationships. Interpolations of various parameters at a benchmark viscosity of 0.40 Pa·s enable extraction of processing windows relevant to VP of the composite mixtures and significantly reduce the trial and error involved in processing parameter optimization for composite mixtures. The dataset also includes µCT image stacks for representative specimens, supporting qualitative assessment of particle dispersion and internal structure.

Official release of micro-computed tomography (µCT) For syntactic foam for public use.

Official release of micro-computed tomography (µCT) For syntactic foam for public use.

Official release of micro-computed tomography (µCT) For syntactic foam for public use.

Official release of micro-computed tomography (µCT) For syntactic foam for public use.

Official release of rheological data for syntactic foam for public use.

Official release of micro-computed tomography (µCT) For syntactic foam for public use.

Official release of rheological data for syntactic foam for public use.

Official release of micro-computed tomography (µCT) For syntactic foam for public use.

ABSTRACT Fused filament fabrication (FFF) three‐dimensional (3D) printing technologies offer new opportunities for fabricating customizable, low‐cost platforms for tissue engineering applications. Here, we developed and characterized 3D‐printed scaffolds using conductive thermoplastic polyurethane (cTPU) filaments and evaluated their mechanical, electrical, and biological performance in vitro. Dynamic mechanical analysis (DMA) across a range of temperatures and frequencies revealed that both TPU and cTPU exhibit temperature‐ and rate‐dependent elastic moduli, with cTPU showing enhanced mechanical stiffness due to the incorporation of conductive fillers. Electrical testing confirmed that cTPU exhibited a stable conductivity (∼1–2 mS/cm) resembling physiological conditions. Surface characterization showed that cTPU was significantly more hydrophilic and exhibited higher nanoscale roughness, both of which are favorable for cell‐material interactions. Mouse embryonic fibroblasts (MEFs) cultured on both scaffolds showed high viability (>85%) and significant proliferation. Notably, immunofluorescence analysis of cultured hippocampal neurons revealed significantly higher density of neuronal networks represented by higher microtubule‐associated protein 2 (MAP‐2)‐positive cell density, greater MAP‐2 area coverage, larger average MAP‐2 cell area, and enhanced postsynaptic density protein 95 (PSD‐95) expression on cTPU scaffolds. Together, these results demonstrate that FFF 3D‐printed cTPU platforms can support long‐term neuronal growth and synaptic maturation, offering promising applications in neural tissue modeling and bioelectronic interfaces. Practical Application: Characterizing soft viscoelastic materials whose properties strongly depend on temperature and strain rate is challenging and typically requires extensive testing across multiple conditions. Using a single‐specimen Dynamic Mechanical Analysis‐based mechanical testing method and a viscoelastic–elastic transformation that converts frequency‐domain viscoelastic measurements into elastic constants over a broad range of test conditions, validated by tensile tests, we efficiently generated reliable modulus data across a range of conditions, enhancing testing throughput without sacrificing accuracy. As a case study, we demonstrate the successful fabrication and comprehensive characterization of FDM 3D‐printed conductive TPU (cTPU) scaffolds for potential applications in neural tissue modeling and bioelectronic interfaces, with the results positioning cTPU composites as cost‐effective, tunable, cytocompatible, and electrically active platforms capable of supporting neuronal growth and function.

BACKGROUND Tumor organoids are 3D cell culture models derived from patient tumor tissues that replicate the complexity of the tumor microenvironment (TME). These models preserve the genetic and phenotypic features of the original tumor, making them superior to traditional 2D cultures and xenografts for cancer research. AIM To explore the role of tumor organoids in translational cancer research, with a focus on their applications in personalized therapy and drug testing. METHODS A comprehensive review of studies was conducted, including articles from PubMed, Scopus, and Web of Science, with a focus on tumor organoid models in cancer research, particularly in preclinical and clinical drug testing, personalized therapy, and biomarker identification. RESULTS Tumor organoids enable high-throughput drug screening, allowing the identification of effective therapies for individual patients. They provide insights into tumor behavior, metastasis, and resistance mechanisms. Additionally, organoids facilitate the evaluation of various therapeutic strategies, including chemotherapy, targeted therapies, and immunotherapies. Despite challenges like inconsistent success rates and ethical concerns with animal-derived matrices, advancements in organoid technology, including AI integration and multi-omics, promise to enhance their clinical applications. CONCLUSION Tumor organoids hold immense potential in precision oncology by providing more accurate, patient-specific models for studying cancer biology and predicting treatment responses. Their integration into clinical decision-making will enhance personalized treatment approaches and improve cancer therapy outcomes.

• Micro-computed tomography of Syntactic foams made from high-density polyethylene (HDPE) reinforced with hollow glass microspheres (HGM) • Automated K-means clustering algorithm for segmentation, was employed to characterize the internal microstructure of additively manufactured HDPE syntactic foams at various infill densities. • The automated segmentation method successfully differentiates the matrix material from the reinforcing particles and voids, allowing for a precise evaluation of the phases. Syntactic foams made from a high-density polyethylene (HDPE) matrix reinforced with hollow glass microspheres (HGMs) are used in weight-sensitive applications given their desirable mechanical performance and low density. However, accurately measuring the internal microstructure features, especially void and particle volume fractions, is compromised by the inadequacy in standard image segmentation methods. In this research, microcomputed tomography (µCT) imaging, in conjunction with a K-means clustering algorithm for segmentation, was employed to characterize the internal microstructure of additively manufactured HDPE syntactic foams at various infill densities, allowing for the quantification of void and particle volume fractions. The segmentation method successfully differentiates the matrix material from the reinforcing particles and voids, allowing for a precise evaluation of the phases. The results reveal a steady increase in Φ void from 3.28 % up to 20.98 % upon a reduction in infill density, with Composition A having 55.8 vol% HGMs of 0.14 g/cm 3 particle density, exhibiting lower void content compared to Composition B, which contains 37.6 vol% HGMs with a density of 0.32 g/cm 3 . Validation against manual segmentation using LabKit yielded an average F1 score of 0.926, demonstrating high segmentation accuracy for identifying voids. Additionally, the analysis distinguishes between internal HGM voids and raster-induced matrix voids, a crucial distinction in understanding porosity formation during additive manufacturing in syntactic foams. The resolution limitation of µCT imaging, 4.8 µm, poses challenges in accurately resolving the thin walls of HGMs of wall thickness 0.37 µm, leading to underestimation of the particle volume fraction. The results provide a quantitative framework for evaluating the microstructural characteristics, contributing to the optimization of syntactic foams for advanced engineering applications.

Since launching in 2018, MLflow has been one of the major open-source tools in managing machine learning lifecycles. In the previous edition, we discussed the machine learning lifecycle and how to use MLflow to track experiments. Since MLflow 3.0, the community as well as Databricks has successfully evolved MLflow to support various GenAI use cases, from the basics like prompt versioning to agent tracing to custom judges.

Dynamic mechanical analysis (DMA) is commonly used to test the viscoelastic properties of materials. However, the frequency-dependent component of the measured properties in such techniques remains underutilized due to the lack of correlation between frequency, temperature, and strain rate. Recent studies have used a time-temperature superposition (TTS) based method to develop a frequency to time domain transformation and validated it for tensile loading conditions. This transform is very useful in reducing the experimental effort required to measure material modulus over a wide range of temperatures and strain rates. However, this transform is not yet validated on an important class of materials, closed-cell foams. The present work is focused on understanding the validity of such transforms on A polymethacrylimide based close-cell structural foam, Rohacell®. Torsional properties of these foams are important for underwater structural applications but neither these foams have been studied for such properties nor the transforms have been tested for their validity for such loading conditions. DMA was conducted under tension and torsion over 30-210°C and 0.1–10 Hz. The transformed results validated against tensile test results revealed an error &lt;6.63% in the strain rate range of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>5</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> s -1 . Moreover, the shear modulus is also transformed from frequency to time domain using the same scheme. Combining machine learning, the results yield an error &lt;4.71% in the shear strain rate of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>4</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>3</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> s -1 . These results show the validity of the transformation method as well as present valuable information about the mechanical properties of Rohacell.

Metamaterials (MMs) are engineered functional materials designed to manipulate waves of various frequencies. Advanced manufacturing has enabled the creation of novel micro- and macro-structured metamaterials with tuned properties. Many of the unique patterns created by metamaterials for specific applications require non-destructive testing (NDT) because the one part manufactured needs to be deployed in the application. Additive manufacturing has expanded the range of achievable metamaterial microstructures, sparking interest in using NDT for quality testing of specialized structures. This study evaluates vibration testing to estimate the elastic modulus of aperiodic metamaterial lattices made from PLA with varying densities, achieved by altering strut lengths. Lattices underwent sine sweeps from 5–300 Hz, with elastic modulus calculated and compared to the tensile tests conducted in accordance with the ASTM D638-14 standard.

The convergence of nanotechnology and bioprinting is redefining the landscape of tissue engineering, with nanocomposite gelatin methacryloyl (GelMA) bioinks emerging as a transformative platform for the biofabrication of multifunctional tissue-specific constructs. GelMA, a photocrosslinkable hydrogel, has rapidly gained attention due to its intrinsic bioactivity, tunable mechanical properties, and compatibility with living cells. However, despite its wide applicability regenerating muscle, cartilage, bone, vascular, cardiac, and neural tissues, native GelMA suffers from limited mechanical strength and insufficient biofunctionality to recapitulate the complexity of specialized tissues. To overcome these shortcomings, recent strategies have focused on the incorporation of nanomaterials into GelMA matrices, ranging from inorganic and carbon-based to metallic, polymeric, and lipidic nanomaterials. These nanocomposite bioprinted scaffolds impart critical enhancements, including improved mechanical robustness, electrical conductivity, stimuli-responsiveness, and bioactivity, while also enabling advanced functionalities such as controlled drug release and real-time responsiveness to the cellular microenvironment. This review examines the bioprinting parameters, material synergies, and design strategies governing the performance of nanocomposite GelMA bioinks. By integrating the tunability of photocrosslinkable bioinks with the multifunctionality of nanomaterials, nanocomposite GelMA bioinks represent a next-generation platform capable of addressing the complex demands of tissue repair and regeneration.

This study presents the transformation of acoustic emission (AE) waveforms from time domain to frequency domain using fast fourier transform (FFT) to understand the mechanisms underlying the fracture of cementitious composites.The motivation of the study is to introduce a real-time monitoring method based on frequency content of AE.The mode I fracture experiments are performed on plain concrete (PC) and steel fiber reinforced concrete (SFRC) in the laboratory.The fracture mechanisms of PC and SFRC are analyzed using the centroid of the frequency spectrum obtained from spectral analysis.The results indicate that there is no change in the frequency centroid spectrum (FCS) until the onset of microcracking in mode I crack deformation.After the microcracking begins, the slope of the FCS continuously decreases, indicating the rate of material damage over time.An accelerated crack growth denoted by slope of mean FCS is 2.7 times higher for PC when compared with SFRC.The slope of the mean FCS is nearly the same for both the initial and final regions of fracture mechanisms in PC.In SFRC, this rate is 29.2% lower due to fiber bridging mechanisms.A damage parameter, based on the FCS, is proposed to assess the damage and validated with the existing damage parameters.These observations suggests that FCS of AE waveforms may be used for real time damage monitoring of concrete structure.

Human tissues exhibit strain rate-dependent mechanical properties, adapting to various physical activities by altering their stiffness and elasticity. This dynamic behavior is critical for tissue functionality, influencing the design of biomaterials for tissue engineering. The current choice of tissue-specific biomaterials does not take into account the tissue dynamics nor the strain-dependent property variation. We propose a conceptual framework to overcome this challenge, considering soft tissues as a case in point and Thermoplastic polyurethanes (TPUs) as a suitable material, the chemistry of which can be controlled to develop them across a broad spectrum of mechanical properties to match those of the natural tissue. TPUs have attracted considerable interest in tissue engineering because of their versatility in biofabrication methods, tunable mechanical properties, and biocompatibility. However, characterizing such soft viscoelastic materials with a strong dependence of their properties on temperature and strain rate is a challenge and requires an elaborate test scheme over multiple strain rates and temperatures. The present study described a viscoelastic-elastic transform that can convert the frequency domain viscoelastic measurements to elastic constants over a wider range of test conditions using a single sample and substantially reduce the test regime. Tensile test measurements were used to validate the results of the transformation. The findings revealed that while some TPUs might be suitable for certain applications at specific strain rates, others are better suited when strain rates are varied to more accurately mimic human life conditions. Additionally, cytocompatibility tests, crucial for tissue engineering applications, confirmed that the TPU scaffolds support cell attachment and proliferation, with viability rates exceeding 80 % across all tested groups. Overall, this study highlights the versatility of the viscoelastic-elastic transform method in identifying suitable materials by characterizing their strain rate-dependent mechanical properties, thereby optimizing scaffold performance to more accurately replicate the dynamic conditions encountered in human tissues. • Human tissues exhibit strain rate-dependent mechanical properties. • Biomaterials selection do not consider strain-dependent property variation. • A viscoelastic-elastic transform converts frequency-domain measurements to elastic constants. • Substantially reduce the test regime with only a single sample. • Optimizing scaffold performance to better replicate dynamic conditions in human tissues.

Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation from natural language prompts, revolutionizing software development workflows. As we advance towards agent-based development paradigms, these models form the cornerstone of next-generation software development lifecycles. However, current benchmarks for evaluating multilingual code generation capabilities are predominantly English-centric, limiting their applicability across the global developer community. To address this limitation, we present IndicEval-XL, a comprehensive benchmark for code generation that incorporates 6 major Indic languages, collectively spoken by approximately 14\% of the world's population. Our benchmark bridges these languages with 12 programming languages, creating a robust evaluation framework. This work is particularly significant given India's representation of one-eighth of the global population and the crucial role Indic languages play in Indian society. IndicEval-XL represents a significant step toward expanding the linguistic diversity in code generation systems and evaluation frameworks. By developing resources that support multiple languages, we aim to make AI-powered development tools more inclusive and accessible to developers of various linguistic backgrounds. To facilitate further research and development in this direction, we make our dataset and evaluation benchmark publicly available at https://github.com/telekom/IndicEval-XL

Abstract Regenerating damaged meniscal tissue remains a significant challenge due to the meniscus’ limited capacity for self-repair. Photocrosslinkable hydrogels, like gelatin methacryloyl (GelMA), offer a promising solution for meniscal regeneration by providing structural flexibility to accommodate the meniscus’ complex geometry while enabling the incorporation of bioactive molecules and cells. However, GelMA alone often lacks the mechanical robustness required for load-bearing applications. In this study, we introduce a dual-crosslinked GelMA scaffold, enhanced with tannic acid (TA), designed to replicate the mechanical properties of the native meniscus. By adjusting TA concentrations, we successfully fine-tuned the scaffold’s compressive modulus to match that of human meniscal tissue. This dual crosslinking not only improved mechanical strength but also resulted in a denser matrix with smaller pore sizes and reduced degradation and swelling rates. The optimized GelMA-TA formulation was 3D-printed into complex shapes, demonstrating its potential for producing patient-specific scaffolds. Beyond its mechanical benefits, the GelMA-TA scaffold exhibited excellent antioxidant and antibacterial properties. Human mesenchymal stem cells seeded onto the scaffold showed high viability, increased proliferation, and successful chondrogenic differentiation. Additionally, the GelMA-TA scaffold acted as an immunomodulatory biomaterial, suppressing pro-inflammatory responses in monocytes while promoting an anti-inflammatory, pro-regenerative M2a macrophage phenotype. These findings suggest that the GelMA-TA scaffold holds strong potential as a viable solution for meniscal tissue repair, offering both structural integrity and enhanced biological functionality. Graphical abstract

Abstract Characterizing materials under shock loading has been of interest in fields such as protective material development, biomechanics to study the injury mechanics and high-speed aerodynamic structures. However, shock loading of material is a very short duration phenomenon and it is extremely challenging to develop sensors for dynamic measurements under such loading conditions. Optical fiber sensors present the possibilities to allow high resolution measurement of displacement in such high strain rate loading conditions. This work studies the possibility of using a fiber-optic loop sensor (FOLS) based on the principle of power losses from the curved section for dynamic measurements under shock loading conditions. The displacement results obtained from the optical sensors are compared with the traditional strain gauge and digital image correlation (DIC) measurements. The result obtained by the FOLS closely matched the sensitivity and precision of the strain gauges and had higher precision than that of DIC.

BACKGROUND: Polylactic acid (PLA) has been extensively used in tissue engineering. However, poor mechanical properties and low cell affinity have limited its pertinence in load bearing bone tissue regeneration (BTR) devices. OBJECTIVE: Augmenting PLA with β-Tricalcium Phosphate (β-TCP), a calcium phosphate-based ceramic, could potentially improve its mechanical properties and enhance its osteogenic potential. METHODS: Gels of PLA and β-TCP were prepared of different % w/w ratios through polymer dissolution in acetone, after which polymer-ceramic membranes were synthesized using the gel casting workflow and subjected to characterization. RESULTS: Gel-cast polymer-ceramic constructs were associated with significantly higher osteogenic capacity and calcium deposition in differentiated osteoblasts compared to pure polymer counterparts. Immunocytochemistry revealed cell spreading over the gel-cast membrane surfaces, characterized by trapezoidal morphology, distinct rounded nuclei, and well-aligned actin filaments. However, groups with higher ceramic loading expressed significantly higher levels of osteogenic markers relative to pure PLA membranes. Rule of mixtures and finite element models indicated an increase in theoretical mechanical strength with an increase in β-TCP concentration. CONCLUSION: This study potentiates the use of PLA/β-TCP composites in load bearing BTR applications and the ability to be used as customized patient-specific shape memory membranes in guided bone regeneration.

Bone tissue regeneration is a rapidly evolving field aimed at the development of biocompatible materials and devices, such as scaffolds, to treat diseased and damaged osseous tissue. Functional scaffolds maintain structural integrity and provide mechanical support at the defect site during the healing process, while simultaneously enabling or improving regeneration through amplified cellular cues between the scaffold and native tissues. Ample research on functionalization has been conducted to improve scaffold-host tissue interaction, including fabrication techniques, biomaterial selection, scaffold surface modifications, integration of bioactive molecular additives, and post-processing modifications. Each of these methods plays a crucial role in enabling scaffolds to not only support but actively participate in the healing and regeneration process in bone and joint surgery. This review provides a state-of-the-art, comprehensive overview of the functionalization of scaffold-based strategies used in tissue engineering, specifically for bone regeneration. Critical issues and obstacles are highlighted, applications and advances are described, and future directions are identified.

Abstract Introduction Prostate cancer diagnosis and treatment can have a significant impact on sexual quality of life for patients and their partners. We developed and validated a new instrument, the Sexual Concerns In Partners of Patients with Prostate cancer (SCIPPP-F), to measure sexual quality of life among female partners of patients with prostate cancer. Objective To examine scores on the SCIPPP-F questionnaire in 200 female partners from across the U.S. and factors associated with worse scores. Methods The SCIPPP-F survey includes 19 questions in 7 domains: 1) distress/satisfaction, 2) loss of connection as a couple, 3) active communication, 4) discomfort with communication, 5) frustration with sexual counseling, 6) expansion of sexual repertoire, and 7) non-penetrative sexual activity. All questions have 5 response choices (not at all, a little bit, somewhat, quite a bit, very much). Descriptive statistics were used to examine the distribution of survey responses, and the Mann–Whitney U test was used to compare median scores between subgroups of partners based on demographics and relationship characteristics. Results Results of the survey are shown in the table. More than half of partners (53%) felt their sex life is quite a bit or very much worse since the prostate cancer diagnosis and/or treatment, and 35% were not at all satisfied with their current sex life. Loss of intimacy was a common complaint. Additionally, approximately 1/3 of partners were at least somewhat uncomfortable talking to their partner about sexual problems and frustrated/angry about the lack of information they received about sexual health from clinicians, with 51 partners (26%) reporting that they were not at all prepared for sexual side effects. Notably, the majority of partners were at least somewhat comfortable trying new ways to achieve intercourse and at least somewhat satisfied with hugging, kissing, and other intimate activities rather than intercourse. There were no significant differences in median overall SCIPPP-F scores based on partners’ marital status, relationship length (&amp;gt;30 vs &amp;lt; =30 years), or menopausal status; however, there was a trend toward lower (better) SCIPPP-F scores among non-white partners (p = 0.07). Conclusions These results identify multiple actionable gaps in sexual quality of life for female partners of patients with prostate cancer, including a need for more comprehensive sexual counseling prior to treatment and interventions to improve sexual quality of life, such as individual/couples counseling and/or sex therapy. Funding acknowledgement: Department of Defense. Disclosure No.

The primary objective of this study is to clarify the fundamental question of whether, in principle, it is possible to dispense with a prior solution annealing process in favor of a direct aging heat treatment for specimens of maraging stainless steel grade X3NiCoMoTi18‐9‐5 (1.2709) produced by laser powder bed fusion (LPBF). The waiver of a solution annealing process would significantly increase the process efficiency and thus support a sustainable and resource‐friendly production of such components. Therefore, the hardness, microstructure, and the present phases of specimens in as‐built + aged condition (AB + A) and solution‐annealed + aged (SOL + A) are examined during this study. Initially, an extended parameter study is performed using a Renishaw AM 250 LPBF system equipped with a pulsed mode laser system to achieve the highest possible apparent density. As test specimens, small cubes are produced for parameter study and are analyzed for porosity by means of optical microscopy. To investigate the relationship between microstructure and hardness in different material states, one series of specimens is aged directly after LPBF processing in the as‐built state (AB + A). For comparison, the other series was solution annealed at 820 °C for 60 min, quenched in water and then aged (SOL + A). A maximum hardness value of 614 HV1.0 is achieved for specimen aged at 490 °C for 120 min in as built condition (AB + A), while 624 HV1.0 was measured for specimen aged at 490 °C for 180 min in conventionally solution annealed + aged (SOL + A) condition. Significant austenite reversion is not observed at aging temperature of 490 °C in both cases. Aging of specimens at temperatures of 540 and 600 °C resulted in reduction of specimen hardness due to higher percentage of austenite reversion. No significant difference between the hardness values of AB + A and SOL + A specimens is observed. It can therefore be concluded that, in principle, conventional solution annealing and ageing can be dispensed with in favor of direct aging. However, as the results are based on small sized specimens, further investigations into the scalability are needed.