VTT Research System
Not a member yet
161399 research outputs found
Sort by
Microbial metabolism in deep terrestrial subsurface communities - amino acids as biosignatures
Get PDFThe deep terrestrial subsurface (DTS) biosphere consists of a variety of distinct microbial taxa, mostly bacterial. The mechanisms by which microbes dynamically manage the uptake and concurrent utilization of nutrients within the DTS environments remain largely unexplored. Here, we examined the utilization patterns of amino acids and other polar metabolites in cultured DTS bacterial communities to investigate the adaptive responses and metabolic pathways employed under varying nutrient conditions to gain insight into how environmental shifts impact the metabolism of these communities. Previously, we found that changes in growth conditions affected the composition and size of the bacterial communities enriched from these oligotrophic, anoxic environments and induced changes in the production of primary and secondary metabolites. In the present study, metabolic fingerprinting was used to investigate the primary and secondary metabolite utilization and main metabolic pathways present in the enriched DTS bacterial consortium originating from the deep bedrock of the Fennoscandian Shield. We found that especially amino acids were predominantly degraded under different nutrient conditions. Notably, the degradation of phenylalanine and valine constituted a 'core' metabolic process that remained unaffected by variations in available nutrients within this community. Further, the most significant metabolic pathways employed were those connected to phenylalanine, cysteine and methionine.</p
Biosynthetic optical waveguide interface integration using biomimetic - <i>de novo</i> design ELP for optoelectronic applications
Get PDFThe integration of biologically inspired materials into photonic device fabrication offers a promising route toward sustainable and biocompatible alternative to conventional in inorganic or petroleum based synthetic materials used in optoelectronic systems. In this work, we present a biosynthetic approach for waveguide fabrication utilizing a biomimetic - de novo designed elastin-like polypeptide (ELP) formulated into an all-water-based photoresist compatible with two-photon polymerization (2PP). The ELP was genetically engineered and recombinantly produced in microbes for enhanced molecular stability, a critical feature for withstanding both localized and bulk temperature increases that occur during high-intensity laser exposure during printing. The resulting ELP formulation supported direct writing of waveguide architecture without the need for organic solvents, harsh processing steps, or post-functionalization. This aqueous resist formulation exhibits high stability during printing and retains its structural integrity upon curing, making it a promising candidate for environmentally friendly, soft-material photonics. This work establishes a foundation for using biosynthetic polypeptides in the fabrication of functional photonic elements and demonstrates a step toward greener, protein-based optoelectronic manufacturing technologies
Developing EU-CEM:A Common Evaluation Methodology for Evaluating Co-operative, Connected and Automated Mobility
No full textCo-operative, Connected and Automated Mobility (CCAM) is of increasing interest to the transport community across the world, though is still maturing. The Horizon Europe project FAME is developing a European framework for testing CCAM on public roads. As part of this, a common evaluation methodology (EU-CEM) is being developed, which provides guidance on how to set up and carry out an evaluation or assessment of direct and indirect impacts of CCAM solutions on different user groups and wider society. Objectives include ensuring that evaluations can be complementary planned with results that are easy to compare, as well as establishing a common vocabulary to support projects in the CCAM community. This paper sets out how the EU-CEM is being developed and embedded into CCAM research in Europe, with a particular emphasis on how the project has adopted an agile and iterative approach to the CEM development alongside meaningful and sustained engagement with stakeholders.</p
Enhancing Analytical Performance in Cyclic Voltammetry:An Open-Source Tool for Signal Deconvolution
No full textCyclic voltammetry (CV) is a cornerstone of electrochemical analysis, yet the accurate determination of Faradaic peak heights is often compromised by overlapping signals and complex background currents. Traditional analysis relying on linear baseline subtraction is highly inaccurate, particularly for systems with multiple redox processes or interfering species. This work introduces a powerful and accessible automated fitting algorithm that uses semiderivative analysis to deconvolve complex voltammograms, suitable for linear diffusion controlled experiments conducted with planar working electrodes. The method employs flexible Pearson IV distributions to model a wide range of Faradaic peak shapes and introduces a novel piecewise function to accurately fit and subtract both capacitive and background electrolysis currents. The algorithm’s efficacy is demonstrated on three challenging experimental systems: the reversible redox probe [Ru(NH3)6]Cl3 in the presence of interfering oxygen reduction, the sequential ligand reductions of [Ru(bpy)3](PF6)2 featuring heavily overlapping peaks, and the quantitative analysis of SO2 obscured by a large oxygen reduction signal. The results show a dramatic improvement in accuracy and signal deconvolution over the conventional methods. To promote broad adoption, a user-friendly program and its Python source code have been made freely available to the electrochemistry community.</p
Discrete acceleration-level pseudoinverse-free zeroing neurodynamics for robotic manipulator path tracking control
No full textPredicting the unknown next-instant state of the future nonlinear equation system (FNES) is critical for high-performance robotic manipulator path tracking control. While various algorithms have been developed to solve the FNES problem, many existing methods often focus on velocity-level solutions and rely on computationally expensive Jacobian matrix pseudoinverse operation, which impair both efficiency and accuracy. To bridge the gap, this paper proposes an innovative discrete acceleration-level pseudoinverse-free zeroing neurodynamics (DALPFZN) algorithm. By reformulating the FNES problem as a future nonlinear output-zeroing problem and operating at the acceleration level, the proposed algorithm effectively avoids the need for complicated pseudoinverse computation. Theoretical analyses show the convergence and stability of the DALPFZN algorithm. Numerical comparisons illustrate its superior efficiency and accuracy against existing methods. Furthermore, experimental results on MATLAB and CoppeliaSim platforms substantiate the effectiveness and outstanding performance of the DALPFZN algorithm. When the proposed DALPFZN algorithm is applied to the robotic manipulator path tracking control, the mean of the maximum steady-state output errors (MSSOEs) is 0.05 mm, and the mean of the average computing time per updating (ACTPUs) is 0.1 ms. Compared with the velocity-level pseudoinverse algorithm, the performance improvement rate of the ACTPU is 8.96%. Compared with the velocity-level pseudoinverse-free algorithm, the performance improvement rate of the MSSOE is 87.65%.</p
Mechanical characterisation of ITER-specification tungsten using tensile and small punch testing methods
No full textTungsten is widely recognised for its exceptional properties. The material exhibits a high melting point, excellent thermal conductivity, and strong resistance to radiation damage, making it a key material for fusion energy applications.In this work, two types of mechanical tests were conducted on ITER-specification tungsten (A.L.M.T, Japan): tensile and small punch testing (SPT). Tensile testing provides fundamental properties such as yield strength, and ultimate tensile strength in specific rolling directions. SPT on the other hand, which is biaxial in nature, offers comparable data using miniature specimens, thus enabling efficient characterisation with limited material. The study aims to characterise the mechanical properties of the material and explore a correlation factor between the two approaches.Re-evaluation of the SPT correlation factors of ITER-specification tungsten in this study revealed noticeable deviation from the commonly adopted value in the European standard, with the yield strength factor showing the largest discrepancy. Furthermore, all correlation factors exhibited a noticeable temperature and directional (anisotropy) dependence, highlighting the importance of using material-specific values for accurate properties estimation