Inspire

Ultrashort pulsed (USP) laser machining is a promising approach for processing binderless nanopolycrystalline diamond (NPD), which combines isotropic ultra-high hardness and high thermal stability. This study systematically investigates USP laser ablation to identify suitable conditions for advanced microtool fabrication. The influence of pulse duration ( τ ), wavelength ( λ ), fluence ( F ), pulse frequency ( f ) and pulse and track overlaps ( O x , O y ) on orthogonal and quasi-tangential ablation of NPD was evaluated. The single-pulse ablation threshold ranged from 1.56 J / cm 2 for green fs irradiation to 8.82 J / cm 2 for IR ns irradiation. In orthogonal ablation, increasing f improved ablation efficiency under high-fluence conditions, with IR fs giving the highest material removal, while green fs at low frequency provided the best compromise between low roughness and high efficiency. In the overlap study, O x = 0.6 and O y = 0.8 yielded the lowest surface roughness. For quasi-tangential machining, an optimum parameter window was identified with R a = 13 nm and S a = 51 nm . Finally, NPD micro milling tools with sharp cutting edges ( r ϵ = 1.03 ± 0.13 μ m ) and low surface roughness were successfully fabricated. • Binderless nanopolycrystalline diamond showed the lowest ablation threshold under green femtosecond laser irradiation and the highest threshold under infrared nanosecond irradiation. • In orthogonal machining, green femtosecond irradiation at low frequency provided the best balance between smooth surfaces and efficient material removal, while infrared femtosecond irradiation at high frequency produced the highest removal rates. • A narrow optimum process window was identified for quasi-tangential machining, yielding very low surface roughness and high surface quality on cylindrical binderless nanopolycrystalline diamond. • Micro milling tools were successfully fabricated by combining orthogonal ablation for flute generation with quasi-tangential ablation for tool shaping, producing sharp cutting edges and low surface roughness in binderless nanopolycrystalline diamond.

Determining material properties for machining simulations is challenging because direct measurement methods cannot reproduce the conditions of machining. Instead, an inverse parameter identification is used in this work to determine the material parameters for the Johnson-Cook model for Ti6Al4V (3.7165, Grade 5). A numerical simulation model using the smoothed particle hydrodynamics code mfree_iwf is used to recalculate an orthogonal cutting experiment. Due to GPU-acceleration the computational time is less than 5 min per simulation. Three different optimization algorithms (Simplex, Bayes, Differential Evolution) are used for the identification of the material parameters by minimizing the process force errors between experiment and simulation. Best results are obtained with the Differential Evolution algorithm. The sensitivity of material model parameters to the computed process force errors are shown and reveal for some of the material parameters adverse effects on these errors. Recomputations of experiments at different process conditions with the identified material parameters show good agreements in terms of process forces and the chip segmentation behaviour can be reproduced in high resolution simulations.

Abstract Thermally induced errors critically limit precision in machine tools (MT), affecting dimensional accuracy in high-precision manufacturing. Physics-based models offer a sustainable solution and can do without training measurements, unlike data-driven models, but are often unsuitable for real-time thermal error compensation due to computational demands and boundary condition uncertainties. This paper presents an enhanced ensemble Kalman filter approach to accurately and efficiently reconstruct the thermal state from limited sensor data. Utilizing a reduced finite element model generated via Krylov modal subspace techniques, the proposed method integrates real-time sensor measurements with an ensemble of perturbed models to robustly estimate thermal states and mechanical deformations. Validation experiments on a thermal test bench with 10 out of 40 temperature sensors observed demonstrate significant improvements in accuracy achieving an RMSE of $$1.5\,^{\circ }$$ 1.5 ∘ C. The computational speed is over 45 $$\times $$ × faster than real-time allowing the implementation of the digital twin for any MT. The reduction of the volumetric thermal error by consistently more than 70% confirm the potential of this digital twin-based approach for real-time thermal error compensation in precision manufacturing.

BackgroundThe therapeutic potential of non-invasive transcranial electric stimulation (tES) is growing, but challenges in tailoring treatments to individual patients persist. We demonstrated that personalized montages, informed by biophysical modeling, can reduce dose variability and improve target engagement. However, traditional setups are prone to electrode placement errors, leading to inconsistent dosage, localization and potential off-target engagement.MethodsWe developed a pipeline for creating patient-specific 3D-printed caps based on individual MRI scans to allow custom placement of up to 34 electrodes. Hybrid brush electrodes were incorporated to facilitate the use on with-hair regions of the head. The patient-specific caps are integrated within a Neurostimulator/EEG device, enabling precise electrode placement for recording of neural activity and optimized, personalised tES therapies based on individual biophysical brain models.ResultsA proof-of-concept in-silico study highlighted the importance of positional accuracy in electrode placement, particularly in minimizing off-target stimulation in case of the personalized montage configuration. To mitigate positional displacement, we introduced the pipeline for generating patient-specific 3D-printed caps, ensuring precise anatomical fit. The flexible design of these caps supports high-density electrode arrays tailored to various therapeutic montages. Integrated brush electrodes function in both dry and wet modes and are powered by electronics embedded in a neckpiece, enabling multi-step tES and EEG recording with minimal setup for at-home use. Electrical and mechanical evaluations confirmed the system’s feasibility, and a clinical trial with eight healthy subjects showed improved comfort and increased willingness for home use.ConclusionThis customized cap-electrode system provides a practical solution for self-administered, repeatable personalized tES and EEG session at home.Trial registration: The study is registered on the Swiss National Clinical Trials Portal (SNCTP), (SNCTP000005598) and Clinicaltrials.gov (NCT05999916). The study was approved by the Independent Competent Ethics Committee (Ethikkommission Nordwest-und Zentralschweiz (EKNZ)) at the 14 August 2023 and the Competent Regulatory Authority Swissmedic at the 20 December 2023.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12984-025-01769-8.

The Yld2000-2D yield locus is widely employed to model anisotropic plasticity in sheet metal forming. Its exponent, a, critically influences the shape of the yield surface and is typically assigned fixed values based on crystal structure–commonly a=6 for body-centered cubic (BCC) and a=8 for face-centered cubic (FCC) materials. However, no universally accepted value exists for hexagonal close-packed (HCP) metals such as commercially pure titanium, which exhibit pronounced anisotropy and complex hardening behavior. This study explores the influence of the value of a on accurately modeling the forming response of commercially pure titanium sheets. To examine the impact of the exponent value a comparison between finite element (FE) simulations and experimental draw-in profiles obtained from cup-drawing tests is performed. To account for evolving anisotropy during plastic deformation, the Yld2000-2D yield locus is further augmented with strain-dependent coefficients, while the loading asymmetry commonly present in HCP metals is neglected. The results show a clear preference for larger exponent values with a>9 giving the best results. This highlights the necessity of material-specific calibration for HCP alloys and provide actionable insights for improving the predictive fidelity of titanium sheet forming simulations.

Abstract Diverse subtypes of cortical projection neurons (PN) form long-range axonal projections that are responsible for distinct sensory, motor, cognitive, and behavioral functions. Translational control has been identified at multiple stages of PN development, but how translational regulation contributes to formation of distinct, subtype-specific long-range circuits is poorly understood. Ribosomal complexes (RCs) exhibit variations of their component proteins, with an increasing set of examples that confer specialized translational control. Here, we directly compare the protein compositions of RCs in vivo from two closely related cortical neuron subtypes–cortical output “subcerebral PN” (SCPN) and interhemispheric “callosal PN” (CPN)– during establishment of their distinct axonal connectivity. Using retrograde labeling of subtype-specific somata, purification by fluorescence-activated cell sorting, ribosome immunoprecipitation, and ultra-low-input mass spectrometry, we identify distinct protein compositions of RCs from these two subtypes. Strikingly, we identify 16 associated proteins reliably and exclusively detected only in RCs of SCPN. 11 of these proteins have known interaction with components of ribosomes; we further validated ribosome interaction with protein kinase C epsilon (PRKCE), a candidate with roles in synaptogenesis. PRKCE and a subset of SCPN-specific candidate ribosome-associated proteins also exhibit enriched gene expression by SCPN. Together, these results indicate that ribosomal complexes exhibit subtypespecific protein composition in distinct subtypes of cortical projection neurons during development, and identify potential candidates for further investigation of function in translational regulation involved in subtype-specific circuit formation.

Effective, rapid and functionally perfusable vascularization remains a major challenge in tissue engineering. Current approaches to generate vasculature in vitro require multipart fabrication methods or complex and costly media supplements, limiting their scalability. Here, we demonstrate that exogenous electrical stimulation (estim) offers a promising alternative by enhancing 3D vasculogenesis in engineered human tissues. Exposing 3D endothelial-fibroblast cocultures to pulsed estim promoted the formation of dense and branched vascular networks. In a microfluidic device model, we show that estim induces the formation of an interconnected vascular network that can be perfused, whereas unstimulated control networks remained less mature. Importantly, we demonstrate that upon implantation, estim-pretreated vascular grafts exhibit elevated anastomosis with host and perfusion with blood relative to the untreated grafts. In addition, we use estim to promote engraftment of a vascularized 3D liver construct. Mechanistically, we find that estim induces membrane hyperpolarization in endothelial cells via voltage-gated potassium (K V ) channels. Inhibiting K V channels abrogated estim's pro-vasculogenic effects in endothelial cells. Conversely, pharmacologically activating hyperpolarization induced endothelial responses even without estim, directly linking K V channel-mediated hyperpolarization as a key mechanism by which estim drives vascular assembly and function. Ultimately, our work establishes estim as a new orthogonal approach to promote formation of perfusable vasculature in engineered tissues.