Thermal Dynamics Research Articles

Learning reaction-transport coupling from thermal waves.

Although thermal waves are ubiquitous in nature and engineering, the development of diagnostic tools capable of elucidating the roles of reaction and transport remains an unmet need. This limits our comprehension of the physics and ability to predict wave dynamics. Here we demonstrate that thermal properties and chemical kinetics can be learned directly from observing thermal wave dynamics, using partial differential equation-constrained optimization. This enables the determination of unobserved reaction rates without the need for a comprehensive measurement of all state variables, given the model space constrained by governing equations. Examples include steady planar waves and unsteady pulsating waves of which dynamics are commonly observed in nature. We show successful learning of thermal properties and chemical kinetics and reconstruction of wave dynamics with the inferred properties, which enables the comprehension of the intricate reaction-transport coupling from thermal data.

Three-Dimensional CFD Analysis of a Hot Water Storage Tank with Various Inlet/Outlet Configurations

This study presents a comprehensive 3D numerical analysis of thermal stratification, fluid dynamics, and heat transfer efficiency across six hot water storage tank configurations, identified as Tank-1 through Tank-6. The objective is to determine the most effective design for achieving uniform temperature distribution, stable stratification, and efficient heat retention in sensible heat storage systems, with potential for integration with phase change materials (PCMs). Using COMSOL Multiphysics 5.6, simulations were conducted to evaluate key performance indicators, including the Richardson number, capacity ratio, and exergy efficiency. Among the tanks, Tank-1 demonstrated the highest efficiency, with a capacity ratio of 84.6% and an exergy efficiency of 72.5%, while Tank-3, which achieved a capacity ratio of 70.2% and exergy efficiency of 50.5%, was identified as the most practical for real-world applications due to its balanced heat distribution and feasibility for PCM integration. Calculated dimensionless numbers (Reynolds number: 635, Prandtl number: 4.5, and Peclet number: 2858) indicated laminar flow and dominant convective heat transfer across all the configurations. These findings provide valuable insights into the design of efficient thermal storage systems, with Tank-3’s configuration offering a practical balance of thermal performance and operational feasibility. Future work will explore the inclusion of PCM containers within Tank-3, as well as applications for heat pump and solar water heaters, and high-temperature heat storage with various working fluids.

Thermal and flow dynamics of an inclined air heat exchanger equipped with spring turbulators in the transition flow regime

AbstractThe research involves an experimental investigation into the performance of a flow assisting air heat exchanger under varying angular orientation and uniform external heat fluxes without and with spring turbulators. The investigation was performed for Reynolds numbers ranging from 511 to 9676 and inclination angle 15° and 30°. Three heat fluxes (2, 3, and 4 kW/m2) were applied to the test section to investigate the effect of external surface heating on the range of transition flow regime and thermohydraulic performance. Transition from laminar to turbulent flow for plain channel at different heat fluxes and inclinations occurs within specific Reynolds number ranges: 2436–4446 for 15° inclination at 4 kW/m2, 2574–4289 at 3 kW/m2, and 2850–4152 at 2 kW/m2; for 30° inclination, the ranges are 2518–4151, 2712–4361, and 2992–4346 at the respective heat fluxes. When it comes to the effect of inclination on Nusselt number, the transition occurs sooner at lower angles, but is delayed as the angle increases. Additionally, the Nusselt number decreases as the angle of inclination increases. When comparing the Nusselt numbers of plain tubes to those with spring turbulators, the latter shows a significantly greater enhancement. In laminar flow, a maximum 100% deviation exists between highest and lowest friction factors, decreasing to 75% with increasing Reynolds number; all insert configurations exhibit highest friction factor at 15° due to stronger buoyancy forces.

Characterizing non-Markovian and coherent errors in quantum simulation

Quantum simulation of many-body systems, particularly using ultracold atoms and trapped ions, presents a unique form of quantum control—it is a direct implementation of a multi-qubit gate generated by the Hamiltonian. As a consequence, it also faces a unique challenge in terms of benchmarking, because the well-established gate benchmarking techniques are unsuitable for this form of quantum control. Here we show that the symmetries of the target many-body Hamiltonian can be used not only to benchmark but to characterize experimental errors in the quantum simulation. We use our results to develop protocols to characterize these errors, which can be implemented using state-of-the-art technology. We consider two forms of errors: (i) unitary errors arising out of systematic errors in the applied Hamiltonian and (ii) canonical non-Markovian errors arising out of random shot-to-shot fluctuations in the applied Hamiltonian. We show that the dynamics of the expectation value of the target Hamiltonian itself, which is ideally constant in time, can be used to characterize these errors. In the presence of errors, the expectation value of the target Hamiltonian shows a characteristic thermalization dynamics, when it satisfies the operator thermalization hypothesis (OTH). That is, an oscillation in the short time followed by relaxation to a steady-state value in the long time limit. We show that while the steady-state value can be used to characterize the coherent errors, the amplitude of the oscillations can be used to estimate the non-Markovian errors. We prove a sandwich theorem to establish a linear relation between the amplitude of the oscillations and the magnitude of the non-Markovian errors. Moreover, by varying the initial state, we show that the steady state values can be used to completely construct the generator of the coherent errors. Using these results, we develop two experimental protocols to characterize the unitary errors based on these results, one of which requires single-qubit addressing and the other one doesn't. We also develop a protocol to characterize non-Markovian errors. Published by the American Physical Society 2024

Ultrafast thermal modulation dynamics during ripple formation induced by a femtosecond laser multi-pulse vortex beam

Abstract This work theoretically investigated the ultrafast thermal modulation dynamics during early formation of ripples on an Au film induced by femtosecond laser multi-pulse vortex beam irradiation. An extended two-temperature dynamics model that comprehensively considers optical interference modulation for the formation of seed ripples, transient reflectivity and non-equilibrium thermal transfer was self-consistently built to predict high-contrast ripple formation. The two-dimensional evolution of electron and phonon temperature modulations during ripple formation in a high non-equilibrium state of Au film were obtained via femtosecond laser multi-pulse vortex beam irradiation. It was revealed that ripple contrast can be significantly amplified by shortening the laser wavelength, increasing the pulse number, or enlarging the laser fluence of the vortex beam. Moreover, the electron–phonon coupling time during ripple formation is fully explored in detail. This study provides valuable insights into optimizing laser parameters for controlled high-contrast ripple formation on Au films.

Freezing-in cannibal dark sectors

Self-Interacting Dark Matter models can successfully explain dark matter (DM) production through interactions confined within the dark sector. However, they often lack measurable experimental signals due to their secluded nature. Including a feeble interaction with the visible sector through a Higgs portal leads not only to potential detection avenues and richer thermal production dynamics, but also to a possible explanation of the initial dark sector population through the freeze-in mechanism. In this work we study, by solving the full system of coupled Boltzmann equations for the number densities and temperatures of all the involved states, three scenarios of this type where the DM is: a real scalar with broken ℤ2, a complex scalar with unbroken ℤ3, and a ℤ3 scalar with an additional scalar mediator. All of these models have viable dark matter candidates in a cannibal phase while having different detection profiles. We show that cosmological bounds can be either exacerbated or evaded by changing the dark sector interactions, leading to potential signatures in long-lived particle and indirect detection experiments.

Parametric influences on flow, heat transfer, and nutrient transport in the knee joint cavity, a numerical approach

A novel aspect of this study is the investigation of the impact of temperature-dependent Arrhenius reactions and metabolic heat generation on the overall heat transfer within a knee joint cavity. This is a unique contribution where the interaction between thermal effects and metabolic activity is shown to influence the transport of nutrients and the removal of waste products. For the first time, the study also aims to examine the influence of key non-dimensional numbers on the characteristics of mixed convection flow, providing new insights into the dominant physical mechanisms at play. An innovative feature of the model is the incorporation of a non-linear reaction term to address the balance between protein synthesis and degradation. By integrating both thermal and biochemical dynamics, this approach offers a comprehensive analysis of protein aggregation in the knee joint, with potential implications for understanding and treating joint diseases, particularly those related to the health of synovial fluid and cartilage, such as osteoarthritis. The findings have the potential to inform the development of improved therapeutic strategies for managing these conditions. In the context of knee joint cavity dynamics, a low Cauchy number Ca plays a crucial role in ensuring steady and laminar flow, which reduces inertia and ensures that the continuity equation is satisfied. This laminar nature of the flow is essential for maintaining stable synovial fluid movement within the cavity, which aids in the smooth transport of nutrients and waste products. Additionally, higher Peclet number Pe values indicate an increased dominance of convective transport over diffusion, thereby enhancing the supply of essential nutrients to cartilage and bone, while also facilitating the removal of waste products and inflammatory mediators. This efficient convective transport mechanism is vital for the overall health of the joint and for mitigating inflammation. Furthermore, the Zeldovich number β significantly influences the temperature sensitivity of the Arrhenius reaction term within the cavity, where higher values reflect increased reactivity to temperature changes. This temperature dependence impacts metabolic heat generation and protein dynamics, further influencing the biochemical processes that occur within the joint. Collectively, these non-dimensional parameters highlight key aspects of synovial fluid dynamics, nutrient transport, and biochemical reactions that are essential to the functioning and health of the knee joint.

Numerical Modelling and Experimental Validation of Selective Laser Melting Processes Using a Custom Argon Chamber Setup for 316L Stainless Steel and Ti6AI4V

Selective Laser Melting (SLM) is an advanced additive manufacturing technique that demands meticulous control over thermal dynamics to maintain the integrity and performance of manufactured parts. This study presents the development and validation of a thermal model designed to enhance the SLM process for 316L stainless steel (316L SS) and titanium alloy Ti6Al4V. A specially constructed Argon Chamber Setup, equipped with a 200 W continuous-wave (CW) fibre laser system, was used to create an SLM-representative environment for 316L SS, enabling precise experimental validation of the model. This validation serves as a robust baseline, facilitating the model’s extension to more complex materials like Ti6Al4V, thereby supporting a cost-efficient and safe approach to initial testing. The rigorously validated thermal model offers a comprehensive link between experimental data and numerical simulations in SLM. It supports process optimisation by accurately predicting thermal behaviours, contributing significantly to additive manufacturing advancements. By fine-tuning processing parameters, this model enhances material characteristics, thereby providing practical insights applicable to industrial production and improving the consistency and quality of SLM-manufactured parts.

Full 3D thermal-hydraulic and electric modelling of quench propagation in HTS conductors

Abstract A fully three-dimensional multi-physics model to simulate quench propagation in HTS conductors for fusion applications is presented. It accounts for thermal, electric and fluid dynamics throughout the entire transient. The need for high-fidelity models for quench simulations comes from the bulky layouts of many HTS conductors that are being proposed. The model is then validated against experimental data, showing a good agreement on all the relevant quentities (local voltage and temperatures). It is shown that the detailed model improves the quality of the agreement with the measured data with respect to more simplified models. It also allows an insight on the temperature distributions in the conductor cross-section, which can be relevant for the interpretation of experimental data as well as to support the design of quench detection strategies which rely on local temperature variations.

Unlocking Heat Transfer Potential in Multi-Sided Porous Geometries: A Study on Magnetothermal Effects and Entropy Generation

This study investigates heat transfer efficiency and irreversibility generation in multi-sided porous thermal systems filled with a Cu-Al2O3-water hybrid nanofluid. The research examines convective heat transfer across various polygonal geometries, ranging from four-sided to infinitely-sided (circular) structures, aiming to maximize thermal system performance intended for scientific and industrial applications. For a standardized comparison, the fluid volume and active heating and cooling lengths are kept constant for all the geometries considered. The analysis includes varying flow-controlling variables like the modified Rayleigh number (Ram), Hartmann number (Ha), and Darcy number (Da) to evaluate how they affect heat transfer efficiency and entropy generation, including total, magnetic, and viscous entropy. The numerical simulations, conducted using the finite element approach, explore Ram values ranging from 10 to 104, Ha from 0 to 70, and Da from 10-4 to 10-2. Streamline and isothermal contours analyze flow behavior, while heatline tools reveal thermal energy transport dynamics. Results show up to a 20% improvement in heat transfer efficiency in optimized configurations. Key findings indicate that hexagonal structures can be viable alternatives to circular tubes in space-constrained applications, offering comparable thermal performance. Interestingly, pentagonal cavities exhibit the highest irreversibility due to symmetry loss. The study offers insightful information for enhancing thermal system design in various industrial settings, particularly for applications requiring efficient heat transfer in limited spaces.

Thermal Characterization Methodologies for Experimental Minichannel Heat Sink Designs in Printed Circuit Board Assemblies

There has been a growing demand for novel, highly efficient, power-saving cooling solutions in recent years. In many cases, standard cooling techniques offer only limited opportunities to prevent the overheating of circuits. Such issues concern high-speed Printed Circuit Board Assemblies (PCBA) in data centers and telecommunication racks, where the flow of the cooling medium is obstructed due to the lack of space. Size limitations can also be a serious problem when cooling high-power devices because the devices consume a large space. Since the heat sink-based cooling solutions and the sophisticated IC packages only deal with one possible heat flow path, we were given the idea of enhancing the secondary heat flow path towards the Printed Circuit Board (PCB). Led by this intention, the idea of creating an embedded minichannel system inside the circuit board and circulating the cooling agent was realized. Through this method, we could decrease the board-to-ambient thermal resistance significantly. This paper presents the demonstration and feasibility study of this method. One of the main aims of this study is to demonstrate the applicability of the proposed concept in PCBAs, where the primary concerns are the low-cost manufacturability and available space. The other goal is to create an adaptation of the standard thermal characterization methodologies to deal with the specific dissipating components in the PCBA demonstrators. In the first part, the manufacturing technology is elaborated on, and its efficiency is characterized by thermal transient testing and Computational Fluid Dynamics (CFD) simulations. For these use cases, it was noted that the cumulative thermal resistance decreased by approximately 60% when a volumetric flow rate of 100 ccm was applied in the minichannels. In the second part, a more sophisticated technology demonstration is realized and characterized by adding the proposed embedded minichannel heat sink to an existing high-speed PCBA. A specific thermal transient testing was implemented specifically for this use case, and it was carried out on programmable logic devices by utilizing general-purpose programmable logic to construct the necessary measurement methods. In the future, this feature can be used in different logic circuit designs where it is not possible to determine the junction temperature directly.

On Assessing a Potential Reuse of the Indonesian Post-Operation Offshore Oil/Gas Pipelines as A Cold-Water Pipe for an Ocean Thermal Energy Conversion (OTEC) System: A Thermal and Fluid Dynamic Perspective

One of the main issues arising in offshore oil and gas decommissioning is associated with significant required costs. Research assessing the potential reuse of the post-operation offshore oil and gas pipeline (POGP) in Indonesia for the Ocean Thermal Energy Conversion (OTEC) system offer double the potential cost reductions in POGP decommissioning and OTEC development. In the context of OTEC development, research on increasing system efficiency makes a significant effort by modifying working fluids and usually by employing the assumption that the temperature of the cold seawater at the surface outlet of the Cold-Water Pipe (CWP) is practically the same as that at the inlet of the CWP at a depth of about 900 m. Unfortunately, this was not the case when the POGP was to be reused for the OTEC system because there was difficulty in applying additional insulation to the existing subsea pipelines. The temperature change in the cold seawater is even more critical considering that oil and gas operations at a depth of 900 m could be associated with more than 60 km of pipeline length to reach an onshore system for a typical seabed bathymetry. This paper assesses the potential reuse of the POGP as a CWP for the Ocean OTEC system. The temperature distribution within CWP is analyzed using a thermal and fluid dynamics approach. The results show that the reuse of POGP for the OTEC system could offer an excellent opportunity for capital cost reductions because the POGP has a remaining service life of over 20 years. However, the results of the analysis of heat and mass transfers show that the temperature change in cold seawater at CWP is about 3 to 6 oC, depending on the technical scenarios of the pipelines. The POGP used in the OTEC system could be suitable for a 20 kW OTEC system with practically no cost of pipelines, which usually accounts for a significant investment cost.

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation.

Low-Frequency Electrical Heating for In Situ Conversion of Shale Oil: Modeling Thermal Dynamics and Decomposition

In situ conversion presents a viable strategy for exploiting low to moderate maturity shale oil. Traditional methods, however, require dense well patterns and substantial energy, which are major hurdles. This study introduces a novel approach employing low-frequency electrical heating via production wells to enhance heat transfer without necessitating additional heating wells. Utilizing a self-developed simulator, we developed a numerical model to evaluate the efficacy of this method in augmenting reservoir temperature and facilitating substance decomposition. Findings indicate that low-frequency electrical heating significantly elevates reservoir temperatures, accelerates hydrocarbon cracking, and boosts fluid production. A sensitivity analysis on various heating strategies and reservoir characteristics showed that elevated heating power can further pyrolyze the heavy oil in the product to light oil, while higher porosity formations favor increased oil and gas output. The study also explores the effect of thermal conductivity on heating efficiency, suggesting that while better conductivity improves heat distribution, it may increase the proportion of heavy oils in the output. Overall, this investigation offers a theoretical foundation for refining in situ conversion technologies in shale oil extraction, enhancing both energy efficiency and production quality.

Electro-thermal dynamics in superconducting generators: An In-Depth investigation of AC losses and cooling techniques for a 10 MW rotor coil system

In the pursuit of optimizing superconducting generator systems, a comprehensive understanding of their electro-thermal behaviors is crucial. This study builds upon previous research on an 8-pole, 10 MW superconducting generator by Inanir et al. (2022, Journal of Superconductivity and Novel Magnetism, 35(11), 3189) and focuses on an in-depth electro-thermal analysis of the rotor coil system. The emphasis is on assessing the AC losses experienced during transitory current changes. By simultaneously solving Ampere's equation and the heat conduction equation under specific boundary conditions, the research provides a detailed insight into the interaction between electrical and thermal dynamics within the rotor coils. The paper highlights the importance of temperature dynamics in various cooling and current conditions. The results demonstrate that achieving an optimal balance in cooling, particularly with the use of liquid nitrogen, is critical for efficient operation. This study not only advances the understanding of superconducting generators but also highlights potential strategies for improving their reliability and efficiency.

Breakdown of thermalization in spin chains with single-ion anisotropy

The principles of ergodicity and thermalization constitute the foundation of statistical mechanics, positing that a many-body system progressively loses its local information as it evolves. Nevertheless, these principles can be disrupted when thermalization dynamics lead to the conservation of local information, as observed in the phenomenon known as many-body localization. Quantum spin chains provide a fundamental platform for exploring the dynamics of closed interacting quantum many-body systems. This study explores the dynamics of a spin chain with S≥1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S\\ge 1/2$$\\end{document} within the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$J_1-J_2,$$\\end{document} incorporating a non-uniform magnetic field and single-ion anisotropy. Through the use of exact numerical diagonalization, we unveil that a nearly constant-gradient magnetic field suppresses thermalization, a phenomenon termed Stark many-body localization (SMBL), previously observed in S=1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S=1/2$$\\end{document} chains. Furthermore, our findings reveal that the sole presence of single-ion anisotropy is sufficient to prevent thermalization in the system. Interestingly, when the magnitudes of the magnetic field and anisotropy are comparable, they compete, favoring delocalization. Despite the potential hindrance of SMBL by single-ion anisotropy in this scenario, it introduces an alternative mechanism for localization. Our interpretation, considering local energetic constraints and resonances between degenerate eigenstates, not only provides insights into SMBL but also opens avenues for future experimental investigations into the enriched phenomenology of disordered free localized S≥1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S\\ge 1/2$$\\end{document} systems.

Optimal control of Hydrocarbon Reducer (HC) injection based on Trust-Region-Reflective Algorithm (TRRA) and physical models for Diesel Oxidation Catalyst (DOC)

The aim of this paper is to control the DOC outlet gas temperature between 600 ± 15 °C by optimizing the hydrocarbon (HC) injection into the Diesel Oxidation Catalyst (DOC) for active regeneration of the downstream Diesel Particulate Filter (DPF). First, based on the physical model of the DOC thermal dynamics, the energy conservation equation for the gas phase temperature is simplified by using variable substitution, and the energy conservation equation for the solid phase temperature is simplified by considering only the heat generated by the HC injection. By solving the simplified model using the Trapezoidal Rule-Backward Differentiation Formula 2 (TR-BDF2) method and optimizing the model parameters in combination with the Gauss-Newton method, the computational efficiency and accuracy were significantly improved. Next, the DOC downstream temperature observer is designed by combining the solution characteristics of the DOC model with the unscented Kalman filter (UKF) algorithm to ensure that the catalyst operates within the optimal temperature range. Then, this paper verifies the accuracy of the model and observer through bench tests covering four steady-state operation conditions and World Harmonized Transient Cycle (WHTC) test cycle, and the results show that the model and observer exhibit high accuracy in both steady-state and transient operation conditions. Finally, the DOC temperature was successfully maintained between 600 ± 15 °C by optimizing the control of the HC injection rate, thus achieving the expected temperature control target. These research results provide theoretical and practical support for diesel engine emission control and DPF active regeneration.

Integrating forecasting methods to support finite element analysis and explore heat transfer complexities

Purpose This paper aims to reduce the cost of experiments required to test the efficiency of materials suitable for artificial tissue ablation by increasing efficiency and accurately forecasting heating properties. Design/methodology/approach A two-step numerical analysis is used to develop and simulate a bioheat model using improved finite element method and deep learning algorithms, systematically regulating temperature distributions within the hydrogel artificial tissue during radiofrequency ablation (RFA). The model connects supervised learning and finite element analysis data to optimize electrode configurations, ensuring precise heat application while protecting surrounding hydrogel integrity. Findings The model accurately predicts a range of thermal changes critical for optimizing RFA, thereby enhancing treatment precision and minimizing impact on surrounding hydrogel materials. This computational approach not only advances the understanding of thermal dynamics but also provides a robust framework for improving therapeutic outcomes. Originality/value A computational predictive bioheat model, incorporating deep learning to optimize electrode configurations and minimize collateral tissue damage, represents a pioneering approach in interventional research. This method offers efficient evaluation of thermal strategies with reduced computational overhead compared to traditional numerical methods.

Model Predictive Control and Service Life Monitoring for Molten Salt Solar Power Towers

A two-component system for control and monitoring of solar power towers with molten salt receivers is proposed. The control component consists of a model predictive control application (MPC) with a flexible objective function and on-line tunable weights, which runs on a Industrial PC and uses a reduced order dynamic model of the receiver’s thermal and flow dynamics. The second component consists of a service-life monitoring unit, which estimates the service-life consumption of the absorber tubes depending on the current mode of operation based on thermal stresses and creep fatigue in the high temperature regime. The calculation of stresses is done based on a detailed finite element study, in which a digital twin of the receiver was developed. By parallelising the model solver, the estimation of service-life consumption became capable of real-time operation. The system has been implemented at a test facility in Jülich, Germany, and awaits field experiments. In this paper, the modeling and architecture are presented along simulation results, which were validated on a hardware-in-the-loop test bench. The MPC showed good disturbance rejection while respecting process variable constraints during the simulation studies.

Understanding AFM-IR Signal Dependence on Sample Thickness and Laser Excitation: Experimental and Theoretical Insights.

Photothermal induced resonance (PTIR), also known as atomic force microscopy-infrared (AFM-IR), enables nanoscale IR absorption spectroscopy by transducing the local photothermal expansion and contraction of a sample with the tip of an atomic force microscope. PTIR spectra enable material identification at the nanoscale and can measure sample composition at depths >1 μm. However, implementation of quantitative, multivariate, nanoscale IR analysis requires an improved understanding of PTIR signal transduction and of the intensity dependence on sample characteristics and measurement parameters. Here, PTIR spectra measured on three-dimensional printed conical structures up to 2.5 μm tall elucidate the signal dependence on sample thickness for different IR laser repetition rates and pulse lengths. Additionally, we develop a model linking sample thermal expansion dynamics to cantilever excitation amplitudes that includes samples that do not fully thermalize between consecutive pulses. Remarkable qualitative agreement between experiments and theory demonstrates a monotonic increase in the PTIR signal intensity with thickness, with decreasing sensitivities at higher repetition rates, while signal intensity is nearly unaffected by laser pulse length. Although we observe slight deviations from linearity over the entire 2.5 μm thickness range, the signal's approximate linearity for bands of sample thicknesses up to ≈500 nm suggests that samples with comparably low topographic variations are most amenable to quantitative analysis. Importantly, we measure absorptive undistorted profiles in PTIR spectra for strongly absorbing modes, up to ≈1650 nm, and >2500 nm for other modes. These insights are foundational toward quantitative nanoscale PTIR analyses and material identification, furthering their impact across many applications.