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Search results for: SURROGATE-BASED%20OPTIMIZATION
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Recent Advances in Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationDesign of high‐frequency structures, including microwave and antenna components, heavily relies on full‐wave electromagnetic (EM) simulation models. Their reliability comes at a price of a considerable computational cost. This may lead to practical issues whenever numerous EM analyses are to be executed, e.g., in the case of parametric optimization. The difficulties entailed by massive simulations may be mitigated by the use of...
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Expedited two-objective dimension scaling of compact microwave passives using surrogate models
PublicationGeometry scaling of compact microwave structures is a challenging problem because of complex relationships between the physical dimensions and electrical characteristics, mostly caused by considerable cross-couplings in densely arranged layouts. Here, a procedure for expedited dimension scaling of compact microwave couplers with respect to two independent criteria has been presented. Our approach involves inverse surrogate models...
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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublicationReflectarrays (RAs) have been attracting considerable interest in the recent years due to their appealing features, in particular, a possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublicationFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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Nested Kriging with Variable Domain Thickness for Rapid Surrogate Modeling and Design Optimization of Antennas
PublicationDesign of modern antennas faces numerous difficulties, partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities (circular polarization, pattern diversity, band-notch operation), but also constraints imposed upon the physical size of the radiators. Conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise...
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Surrogate modeling of impedance matching transformers by means of variable‐fidelity electromagnetic simulations and nested cokriging
PublicationAccurate performance evaluation of microwave components can be carried out using full‐wave electromagnetic (EM) simulation tools, routinely employed for circuit verification but also in the design process itself. Unfortunately, the computational cost of EM‐driven design may be high. This is especially pertinent to tasks entailing considerable number of simulations (eg, parametric optimization, statistical analysis). A possible...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublicationAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Global EM-Driven Optimization of Multi-Band Antennas Using Knowledge-Based Inverse Response-Feature Surrogates
PublicationElectromagnetic simulation tools have been playing an increasing role in the design of contemporary antenna structures. The employment of electromagnetic analysis ensures reliability of evaluating antenna characteristics but also incurs considerable computational expenses whenever massive simulations are involved (e.g., parametric optimization, uncertainty quantification). This high cost is the most serious bottleneck of simulation-driven...
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Reduced-Cost Two-Level Surrogate Antenna Modeling using Domain Confinement and Response Features
PublicationElectromagnetic (EM) simulation tools have become indispensable in the design of contemporary antennas. Still, the major setback of EM-driven design is the associated computational overhead. This is because a single full-wave simulation may take from dozens of seconds up to several hours, thus, the cost of solving design tasks that involve multiple EM analyses may turn unmanageable. This is where faster system representations (surrogates)...
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Rapid multi-objective antenna design using point-by-point Pareto set identification and local surrogate models
PublicationAntenna design is inherently a multicriterial problem.Determination of the best possible tradeoffs between conflicting objectives (a so-called Pareto front), such as reflection response, gain, and antenna size, is indispensable from the designer’s point of view, yet challenging when high-fidelity electromagnetic (EM) simulations are utilized for performance evaluation. Here, a novel and computationally...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Surrogate-assisted EM-driven miniaturization of wideband microwave couplers by means of co-simulation low-fidelity models
PublicationThis article proposes a methodology for rapid design optimization of miniaturized wideband couplers. More specifically, a class of circuits is considered, in which conventional transmission lines are replaced by their abbreviated counterparts referred to as slow-wave compact cells. Our focus is on explicit reduction of the structure size as well as on reducing the CPU cost of the design process. For the sake of computational feasibility,...
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Recent Advances in Accelerated Multi-Objective Design of High-Frequency Structures using Knowledge-Based Constrained Modeling Approach
PublicationDesign automation, including reliable optimization of engineering systems, is of paramount importance for both academia and industry. This includes the design of high-frequency structures (antennas, microwave circuits, integrated photonic components), where the appropriate adjustment of geometry and material parameters is crucial to meet stringent performance requirements dictated by practical applications. Realistic design has...
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Surrogate models and automated cad of passive microwave components
PublicationW pracy pokazane zostały techniki modelowania złożonych układów elektronicznych wysokiej częstotliwości. Modele zastępcze mają postać sparametryzowanych modeli matematycznych tworzonych za pomocą schematów interpolacyjnych lub skupionych, pasywnych układów zastępczych dedykowanych analizie w dziedzinie czasu. Do konstrukcji modeli wykorzystywane są wyniki symulacji elektromagnetycznych, co pozwala na osiągnięcie lepszej dokładności...
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Reliable low-cost surrogate modeling and design optimisation of antennas using implicit space mapping with substrate segmentation
PublicationAbstract: In this work, a reliable methodology for fast simulation-driven design optimisation of antenna structures is proposed. The authors’ approach exploits implicit space mapping (ISM) technology. To adopt it for handling antenna structures, they introduce substrate segmentation with separate dielectric permittivity value assigned for each segment as ISM preassigned parameters. At the same time, the coarse model for space mapping...
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Multimode, multiparametric surrogate models for fast design of waveguide components.
PublicationPrzedstawiona została efektywna technika tworzenia wieloparametrycznych mo-deli zastępczych na podstawie wyników symulacji pełnofalowej przy wykorzy-staniu metody Cauchy`ego wielu zmiennych. Metoda pozwala na automatyczny wy-bór rzędu modelu i minimalizuje liczbę koniecznych analiz pełnofalowych. Te-chnika ta jest wykorzystana do tworzenia modeli uogólnionej macierzy rozpro-szenia.
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublicationThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Model Correction and Optimization Framework for Expedited EM-Driven Surrogate-Assisted Design of Compact Antennas
PublicationDesign of compact antennas is a numerically challenging process that heavily relies on electromagnetic (EM) simulations and numerical optimization algorithms. For reliability of simulation results, EM models of small radiators often include connectors which—despite being components with fixed dimensions—significantly contribute to evaluation cost. In this letter, a response correction method for antenna models without connector,...
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Fast multiplexer cad using surrogate models for channel filters synthesis
Publicationartykuł przedstawia metodę szybkiego projektowania multiplekserów mikrofalowych wykorzystującą dokładne modele zastępcze na etapie projektowania kanałów. przedstawiony został przykład trój-kanałowego multipleksera z filtrami dwurodzajowymi.
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Editorial for the special issue on advances in forward and inverse surrogate modeling for high-frequency design
PublicationThe design of modern‐day high‐frequency devices and circuits, including microwave/RF, antenna and photonic components, historically has relied on full‐wave electromagnetic (EM) simulation tools. Initially used for design verification, EM simulations are nowadays used in the design process itself, for example, for finding optimum values of geometry and/or material parameters of the structures of interest. In a growing number of...
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Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
PublicationFull-wave electromagnetic (EM) analysis has become one of the major design tools for contemporary antenna structures. Although reliable, it is computationally expensive which makes automated simulation-driven antenna design (e.g., parametric optimization) difficult. This difficulty can be alleviated by utilization of fast and accurate replacement models (surrogates). Unfortunately, conventional data-driven modeling of antennas...
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Expedited Geometry Scaling of Compact Microwave Passives by Means of Inverse Surrogate Modeling
PublicationIn this paper, the problem of geometry scaling of compact microwave structures is investigated. As opposed to conventional structures (i.e., constructed using uniform transmission lines), re-design of miniaturized circuits (e.g., implemented with artificial transmission lines, ATSs) for different operating frequencies is far from being straightforward due to considerable cross-couplings between the circuit components. Here, we...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Optimal shape design of multi-element trawl-doors using local surrogate models
PublicationTrawl-doors have a large influence on the fuel consumption of fishing vessels. Design and optimiza-tion of trawl-doors using computational models are a key factor in minimizing the fuel consump-tion. This paper presents an optimization algorithm for the shape design of trawl-door shapes using computational fluid dynamic (CFD) models. Accurate CFD models are computationally expensive. Therefore, the direct use of traditional optimization...
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Efficient knowledge-based optimization of expensive computational models using adaptive response correction
PublicationComputer simulation has become an indispensable tool in engineering design as they allow an accurate evaluation of the system performance. This is critical in order to carry out the design process in a reliable manner without costly prototyping and physical measurements. However, high-fidelity computer simulations are computationally expensive. This turns to be a fundamental bottleneck when it comes to design automation using numerical...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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An agent-based approach to ANN training
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Expedited Multi-Objective Design Optimization of Miniaturized Microwave Structures Using Physics-Based Surrogates
PublicationIn this paper, a methodology for fast multi-objective design optimization of compact microwave circuits is presented. Our approach exploits an equivalent circuit model of the structure under consideration, corrected through implicit and frequency space mapping, then optimized by a multi-objective evolutionary algorithm. The correction/optimization of the surrogate is iterated by design space confinement and segmentation based on...
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5-formylcytosine and 5-hydroxymethyluracil as surrogate markers of TET2 and SF3B1 mutations in myelodysplastic syndrome, respectively
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Inverse and forward surrogate models for expedited design optimization of unequal-power-split patch couplers
PublicationIn the paper, a procedure for precise and expedited design optimization of unequal power split patchcouplers is proposed. Our methodology aims at identifying the coupler dimensions that correspond to thecircuit operating at the requested frequency and featuring a required power split. At the same time, thedesign process is supposed to be computationally efficient. The proposed methodology involves two typesof auxiliary models (surrogates):...
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Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
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Low-Cost and Precise Automated Re-Design of Antenna Structures Using Interleaved Geometry Scaling and Gradient-Based Optimization
PublicationDesign of contemporary antennas is an intricate endeavor involving multiple stages, among others, tuning of geometry parameters. In particular, re-designing antennas to different operating frequencies, makes parametric optimization imperative to ensure the best achievable system performance. If the center frequency at the current design is distant from the target one, local tuning methods generally fail, whereas global algorithms...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublicationAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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RANS-based design optimization of dual-rotor wind turbines
PublicationPurpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine...
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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublicationFast data-driven surrogate models can be employed as replacements of computationally demanding full-wave electromagnetic simulations to facilitate the microwave design procedures. Unfortunately, practical application of surrogate modelling is often hindered by the curse of dimensionality and/or considerable nonlinearity of the component characteristics. This paper proposes a simple yet reliable approach to cost-efficient modelling...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Globalized Parametric Optimization of Microwave Passive Components Using Simplex-Based Surrogates
PublicationOptimization-based parameter adjustment involving full-wave electromagnetic (EM) simulation models is a crucial stage of present-day microwave design process. In fact, rigorous optimization is the only reliable mean permitting to simultaneously handle multiple geometry/material parameters, objectives, and constraints. Unfortunately, EM-driven design is a computationally intensive endeavor. While local tuning is usually manageable,...
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Fast Design Closure of Compact Microwave Components by Means of Feature-Based Metamodels
PublicationPrecise tuning of geometry parameters is an important consideration in the design of modern microwave passive components. It is mandatory due to limitations of theoretical design methods unable to quantify certain phenomena that are important for the operation and performance of the devices (e.g., strong cross-coupling effects in miniaturized layouts). Consequently, the initial designs obtained using analytical or equivalent network...
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Accelerated Gradient-Based Optimization of Antenna Structures Using Multi-Fidelity Simulations and Convergence-Based Model Management Scheme
PublicationThe importance of numerical optimization has been steadily growing in the design of contemporary antenna structures. The primary reason is the increasing complexity of antenna topologies, [ a typically large number of adjustable parameters that have to be simultaneously tuned. Design closure is no longer possible using traditional methods, including theoretical models or supervised parameter sweeping. To ensure reliability, optimization...
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Accelerated Re-Design of Antenna Structures Using Sensitivity-Based Inverse Surrogates
PublicationThe paper proposes a novel framework for accelerated re-design (dimension scaling) of antenna structures using inverse surrogates. The major contribution of the work is a sensitivity-based model identification procedure, which permits a significant reduction of the number of reference designs required to render the surrogate. Rigorous formulation of the approach is supplemented by its comprehensive numerical validation using a...
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A novel version of simulated annealing based on linguistic patterns for solving facility layout problems
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On Accelerated Metaheuristic-Based Electromagnetic-Driven Design Optimization of Antenna Structures Using Response Features
PublicationDevelopment of present-day antenna systems is an intricate and multi-step process requiring, among others, meticulous tuning of designable (mainly geometry) parameters. Concerning the latter, the most reliable approach is rigorous numerical optimization, which tends to be re-source-intensive in terms of computing due to involving full-wave electromagnetic (EM) simu-lations. The cost-related issues are particularly pronounced whenever...
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Expression of epithelial to mesenchymal transition-related markers in lymph node metastases as a surrogate for primary tumor metastatic potential in breast cancer
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Evaluation of Readiness of IT Organizations to Agile Transformation Based on Case-Based Reasoning
PublicationNowadays many of IT organization decides to change the way of delivering from classic, waterfall approach to agile. This transition is called “agile transformation” (AT). The problem of this process is that part of companies started AT without any analysis. This causes that many of transitions fails and organizations must return to old methods of delivering. Cost of return is significant and number of projects with violated project...
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Smart Cities System Design Method Based on Case Based Reasoning
PublicationThe objective of this paper is to present the results of research carried out to develop a design method for Smart Cities systems. The method is based on the analysis of design cases of Smart Cities systems in cities, the selection of the city appropriate to the requirements for implementation and application. The Case Based Reasoning method was used to develop the proposed design methodology, along with mechanisms of the conversion...
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Expedited Gradient-Based Design Closure of Antennas Using Variable-Resolution Simulations and Sparse Sensitivity Updates
PublicationNumerical optimization has been playing an increasingly important role in the design of contemporary antenna systems. Due to the shortage of design-ready theoretical models, optimization is mainly based on electromagnetic (EM) analysis, which tends to be costly. Numerous techniques have evolved to abate this cost, including surrogate-assisted frameworks for global optimization, or sparse sensitivity updates for speeding up local...
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Ladder-Based Synthesis and Design of Low-Frequency Buffer-Based CMOS Filters
PublicationBuffer-based CMOS filters are maximally simplified circuits containing as few transistors as possible. Their applications, among others, include nano to micro watt biomedical sensors that process physiological signals of frequencies from 0.01 Hz to about 3 kHz. The order of a buffer-based filter is not greater than two. Hence, to obtain higher-order filters, a cascade of second-order filters is constructed. In this paper, a more...
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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublicationNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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The Green Approach to the Synthesis of Bio-Based Thermoplastic Polyurethane Elastomers with Partially Bio-Based Hard Blocks
PublicationBio-based polymeric materials and green routes for their preparation are current issues of many research works. In this work, we used the diisocyanate mixture based on partially bio-based diisocyanate origin and typical petrochemical diisocyanate for the preparation of novel bio-based thermoplastic polyurethane elastomers (bio-TPUs). We studied the influence of the diisocyanate mixture composition on the chemical structure, thermal,...