VTT Technical Research Centre of Finland

Simultaneous obstacle avoidance and trajectory tracking for multi-robot systems via acceleration-level motion planning

Considerable attention has been directed toward collision-free trajectory tracking in multi-robot systems, for which CBFs have been widely adopted as a safety-critical tool. However, existing CBF methods are constrained by their dependence on maximum braking estimation. Moreover,...

Defining data-driven business models in the context of sustainability

Purpose Data have been identified as a potential next source of value creation and competitive advantage for companies, giving rise to data-driven business models that rely on data as a key resource. Despite the central role of data in today's business, there is conceptual ambigu...

Plasticizer compatibility with amorphous (low-ordered) cellulose and dialcohol cellulose

Abstract Biopolymers such as cellulose are promising candidates for replacing fossil-based plastics, but their processing is often limited by their high glass transition temperature ( T g ) and strong intermolecular hydrogen bonding. Plasticizers can improve processability, yet t...

Estimation of the Pitzer Parameters for 1-1, 2-1, 1-2, 3-1, and 1-3 Single Electrolytes at 25 °C

Abstract The Pitzer model is widely used in process models for determining the thermodynamic properties of concentrated aqueous electrolytes. The main drawback is the need for experimentally determined parameters for each ion pair in the system. The estimation of unknown Pitzer p...

Introducing citizen energy resilience: Evidence from Finland

This study examines citizen energy resilience (CER) as a sociotechnical construct. Responding to increasing disruptions driven by climate change, market volatility and geopolitical instability, this research conceptualizes CER as emerging from the dynamic interplay of technical s...

Beyond optimisation: Revisiting energy demand management

Energy demand reduction (EDR) in households has re-emerged as a central pillar of climate and energy transition strategies in Europe and beyond. While energy efficiency has long dominated policy frameworks, growing evidence shows that efficiency alone is insufficient to achieve a...

Thermodynamic Aspects of Mixed-Linkage Glucan and Nanocellulose Interactions

Abstract This study addresses knowledge gaps concerning interactions between barley mixed-linkage glucans (MLGs) and TEMPO-oxidized cellulose nanocrystals (TCNC), focusing on underlying physiochemical and thermodynamic principles. Combining dynamic light scattering (DLS), quartz...

Distributional implications of selection into heating-system retrofit subsidies

As the shift away from fossil fuel-based heating systems has become a political priority in many countries, subsidies for energy renovation measures have emerged as popular policy tools to support an equitable energy transition. In this paper, we use high-quality administrative d...

Comparison of Virgin LDPE and an Industrial Multilayer Plastic Film in a Continuous Pilot-Scale Fluidized-Bed Pyrolysis Reactor

Abstract Thermal pyrolysis of industrial multilayer plastic film was experimentally investigated in a pilot-scale fluidized-bed reactor with steam as the carrier gas. Experimental design was constructed by using two different feeds: virgin-quality LDPE and multilayer plastic (MLP...

Graphene Field-Effect Transistor Process and Analysis Optimization in 200 mm Pilot-Line Environment

Abstract The maturity of the chemical vapor deposition graphene-based device processing has increased from chip-level demonstrations to wafer-scale fabrication in the past few years. Due to this, wafer-scale electrical characterization and analysis of the fabricated devices have...

BB84 with ML-KEM Decapsulation-Failure-Based Security Parameters

With the advent of quantum computers, traditional key exchange mechanisms are under threat, necessitating the development of new methods. Recently, Module-Lattice-Based Key Encapsulation Mechanism (ML-KEM) has been standardized as a quantum-safe key exchange method. Another emerg...

Photonic Integrated Circuit Platform on 3 μm Thick Silicon‐on‐Insulator and Its Application Examples

ABSTRACT This paper gives an overview of the 3 μm SOI PIC platform and explains its unique characteristics, such as ultra‐high mode confinement, low losses, dense integration, polarization‐independent operation, small phase errors, ultra‐broadband operation, and ability to handle...

Physics‐Guided Monte Carlo Surrogate Modeling for Optical Properties Inference and Spectral Prediction From Limited Experimental Data

ABSTRACT We present a physics‐guided neural framework that combines Monte Carlo simulations with experimental measurements to characterize optical properties and predict spectral responses at unseen conditions. The hybrid model jointly learns from simulations with complete optica...

Predicting sales offer success of industrial configure-to-order equipment: evaluating explainable AI approach with B2B sales experts

Abstract This study investigates the use of explainable artificial intelligence (AI) for predicting sales offer success in the business-to-business (B2B) context of configure-to-order industrial equipment. Using real sales data from over 400 sales cases and extracted from custome...

Fast, unconditional reset and leakage reduction in fixed-frequency transmon qubits

Abstract On-demand qubit-state initialization is a prerequisite for quantum computation. We demonstrate such a protocol in a device consisting of fixed-frequency transmon qubits pair-wise coupled via tunable couplers — an architecture that is also compatible with the surface code...

Mechanical Properties of Natural Fibre-Reinforced Polymer Composites with Carbon Nanofillers: Experimental and Mesoscale Modelling

Abstract Incorporating carbon nanotubes (CNTs) or graphene nanoplatelets (GNPs) into thermoplastic composites enhances electrical and thermal conductivity, as well as fire resistance, but may impair mechanical performance. To address this challenge and develop multifunctional yet...

Deep learning-based surrogate model for generation of wood microstructures

A machine learning-based surrogate model for efficient wood microstructure generation compatible with a physics-based model is developed. The model is based on the U-Net neural network, a variant of convolutional neural network which, due to its architecture, is suitable for imag...