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At least 1,099 records · Page 61

High-Performance Thermoelectric Generators for Field Deployments

Thermoelectric power generation is a reliable energy harvesting technique for directly converting heat into electricity. Recent studies have reported the thermal-to-electrical energy conversion efficiency of thermoelectric generators (TEGs) up to 11% under laboratory settings. However, the practical effectiveness of TEGs deployed under real environments is still not more than a few percent. In this study, we provide fundamental insight on the operation of TEGs in realistic environments by illustrating the combinatory effect of thermoelectric material properties, device boundary conditions, and environmental thermal resistivity on TEG performance in conjunction with the module parameters. Using numerical and experimental studies, we demonstrate the existence of a critical heat transfer coefficient that dramatically affects the design and performance of TEGs. Results provide a set of concrete design criteria for developing efficient TEGs that meet the metrics for field deployments. High-performance TEGs demonstrated in this study generated up to 28% higher power and 162% higher power per unit mass of thermoelectric materials as compared to the commercial module deployed for low-grade waste heat recovery. This advancement in understanding the TEG operation will have a transformative impact on the development of scalable thermal energy harvesters and in realizing their practical targets for efficiency, power density, and total output power.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Joint Experimental and Computational Characterization of Sum-Frequency Generation between a Continuous Wave Laser and an Ultrafast Frequency Comb Laser for Tunable Laser Development

Ultrafast optical frequency combs allow for both high spectral and temporal resolution in molecular spectroscopy and have become a powerful tool in many areas of chemistry and physics. Ultrafast lasers and frequency combs generated from ultrafast mode-locked lasers often need to be converted to other wavelengths. Commonly used wavelength conversions are optical parametric oscillators, which require an external optical cavity, and supercontinuum generation combined with optical parametric amplifiers. Whether commercial or home-built, these systems are complex and costly. Here, we investigate an alternative, simple, and easy-to-implement approach to tunable frequency comb ultrafast lasers enabled by new continuous-wave laser technology. Sum-frequency generation between an Nd:YAG continuous-wave laser and a Yb:fiber femtosecond frequency comb in a beta-barium borate (BBO) crystal is explored. The resulting sum-frequency beam is a pulsed frequency comb with the same repetition rate as the Yb:fiber source. SNLO simulation software is used to simulate the results and provide benchmarks for designing future systems to achieve wavelength conversion and tunability in otherwise difficult-to-reach spectral regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of an autothermal formate-based hydrogen generator: From optimization of formate dehydrogenation conditions to thermal integration with Fuel Cells

Formate received significant attention for storing H2 in chemical bonds using the concept of H2 carriers. In this report, hydrogen generation from formate was optimized systematically by varying reaction variables. Initial mass activity with a turnover frequency of 3200 molH2 molPd–1 h–1 and 92% H2 yield were obtained in sodium formate (7 M 2.0 mL) dehydrogenation over Pd(3 wt %)/C at 80 °C. Influence of formate cations (Na, K, and NH4) on dehydrogenation was also elucidated, presenting that the fastest initial reaction kinetics was achieved with ammonium formate, whereas the highest H2 yield was obtained with potassium formate (PF) in multiple catalyst recycle tests. Finally, an on-site power generation system was integrated, where a proton exchange membrane fuel cell (PEMFC) was operated in conjunction with H2 produced from the custom developed semibatch dehydrogenation reactors. The system operation was demonstrated with continuous feeding of PF to generate H2 and power on demand without an external heat source by utilizing waste heat produced from the PEMFC in a highly efficient manner.

formate dehydrogenation, optimization of reaction ↗

Optimization of echo-enabled harmonic generation toward coherent EUV and soft X-ray free-electron laser at NSLS-II

Prebunching via echo-enabled harmonic generation (EEHG) is an efficient way to reduce the radiator length and improve the longitudinal coherence as well as output stability in storage-ring-based free-electron lasers. We propose a conceptual design, which uses two straight sections to seed coherent extreme-ultraviolet (EUV) and soft X-ray emission with nearly MHz repetition rate. To take the large energy spread (10 –3 ) of a storage ring into account and utilize the existing bending magnets between the two straight sections as the first chicane, we implement a special modeling tool, named EEHG optimizer. This tool has been successfully applied to maximize the prebunching with a reasonably low energy modulation, thereby generating intense coherent X-ray pulses within a short undulator length (a few meters) limited by the available space of a storage ring. Numerical simulations confirm that the optimized EEHG parameters can be directly applied to generate a 10 MW scale peak power with fully coherent ultrafast EUV to soft X-ray pulses based on the NSLS-II parameters. This method can be easily extended to other types of diffraction-limited storage rings.

36 MATERIALS SCIENCE↗

Thermomagnetic generators for ultra-low-grade marine thermal energy harvesting

Low-grade thermal gradients in marine environments represent an underexploited energy source for autonomous sensing and monitoring. Converting such small temperature differences into usable electrical power remains a key challenge for ocean-deployed systems. We present a deployable thermomagnetic generator thoroughly characterized for marine-relevant energy harvesting. The device powers an internet-connected sensor and harvests ultra-low temperature differences akin to those at the ocean surface. It draws heat from water and rejects it to ambient air, operating optimally at a temperature difference (ΔT) of ~7.5 °C. Laboratory prototypes generated up to 6.7 mW at ΔT ~ 10 °C with gentle airflow (~1 m s -1 ). A separate controlled wave-tank demonstration validated stable operation and sensor powering under marine-like boundary conditions. Given its voltage and power margins, the generator could sustain multiple sensor nodes. Scalability and material assessments identify modular deployment and non-rare-earth alternatives as pathways toward practical marine energy harvesting and low-grade waste-heat recovery.

16 TIDAL AND WAVE POWER↗

Preservation of kinetics parameters generated by Monte Carlo calculations in two-step deterministic calculations

The generation of accurate kinetic parameters such as mean generation time Λ and effective delayed neutron fraction β eff via Monte Carlo codes is established. Employing these in downstream deterministic codes warrants another step to ensure no additional error is introduced by the low-order transport operator when computing forward and adjoint fluxes for bilinear weighting of these parameters. Another complexity stems from applying superhomogenization (SPH) equivalence in non-fundamental mode approximations, where reference and low-order calculations rely on a 3D full core model. In these cases, SPH factors can optionally be computed for only part of the geometry while preserving reaction rates and K-effective, but the impact of such approximations on kinetics parameters has not been thoroughly studied. This paper aims at studying the preservation of bilinearly-weighted quantities in the Serpent–Griffin calculation procedure. Diffusion and transport evaluations of IPEN/MB-01, Godiva, and Flattop were carried out with the Griffin reactor physics code, testing available modeling options using Serpent-generated multigroup cross sections and equivalence data. Verifying Griffin against Serpent indicates sensitivities to multigroup energy grid selection and regional application of SPH equivalence, introducing significant errors; these were demonstrated to be reduced through the use of a transport method together with a finer energy grid.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High-speed tunable generation of random number distributions using actuated perpendicular magnetic tunnel junctions

Perpendicular magnetic tunnel junctions (pMTJs) actuated by nanosecond pulses are emerging as promising devices for true random number generation (TRNG) due to their intrinsic stochastic behavior and high throughput. In this work, we demonstrate the tunability and quality of random number distributions generated by pMTJs operating at a frequency of 104 MHz. First, changing the pulse amplitude is used to systematically vary the probability bias. The variance of the resulting bitstreams closely matches the expected binomial distribution, demonstrating consistency with an underlying sequence of Bernoulli trials. Second, the quality of uniform distributions of 8-bit random numbers generated with a probability bias of 0.5 is considered. A reduced chi-square analysis of these data shows that only two XOR operations are sufficient to achieve this distribution with p-values greater than 0.05. Finally, we show that there is a correlation between long-term probability bias variations and pMTJ resistance. These findings suggest that variations in the characteristics of the pMTJ underlie the observed variation of probability bias. In conclusion, our results highlight the potential of stochastically actuated pMTJs for high-speed, tunable TRNG applications, showing the importance of the stability of pMTJ device characteristics in achieving reliable, long-term performance.

Magnetic tunnel junctions↗

Soft x-ray high-harmonic generation in an anti-resonant hollow core fiber driven by a 3 μ m ultrafast laser

High-harmonic upconversion driven by a mid-infrared femtosecond laser can generate coherent soft x-ray beams in a tabletop-scale setup. Here, we report on a compact ytterbium-pumped optical parametric chirped pulse amplifier (OPCPA) laser system seeded by an all-fiber front-end and employing periodically poled lithium niobate (PPLN) nonlinear media operated near the pulse fluence limits of current commercially available PPLN crystals. The OPCPA delivers 3 µm wavelength pulses with 775 µJ energy at 1 kHz repetition rate, with transform-limited 120 fs pulse duration, diffraction-limited beam quality, and ultrahigh 0.33% rms energy stability over >18 h. Using this laser, we generate soft x-ray high harmonics (HHG) in argon gas by focusing into a low-loss, high-pressure gas-filled anti-resonant hollow core fiber (ARHCF), generating coherent light at photon energies up to the argon L-edge (250 eV) and carbon K-edge (284 eV), with high beam quality and ∼1% rms energy stability. This work demonstrates soft x-ray HHG in a high-efficiency guided-wave phase matched geometry, overcoming the high losses inherent to mid-IR propagation in unstructured waveguides, or the short interaction lengths of gas cells or jets. The ARHCF can operate in the long term without damage and with the repetition rate, stability, and robustness required for demanding applications in spectromicroscopy and imaging. Finally, we discuss routes for further optimizing the soft x-ray HHG flux by driving He at higher laser intensities using either the signal (1.5 μm) or idler wavelengths (3 μm).

Femtosecond lasers↗

Light-induced H 2 generation in a photosystem I-O 2 -tolerant [FeFe] hydrogenase nanoconstruct

The fusion of hydrogenases and photosynthetic reaction centers (RCs) has proven to be a promising strategy for the production of sustainable biofuels. Type I (iron-sulfur-containing) RCs, acting as photosensitizers, are capable of promoting electrons to a redox state that can be exploited by hydrogenases for the reduction of protons to dihydrogen (H 2 ). While both [FeFe] and [NiFe] hydrogenases have been used successfully, they tend to be limited due to either O 2 sensitivity, binding specificity, or H 2 production rates. In this study, we fuse a peripheral (stromal) subunit of Photosystem I (PS I), PsaE, to an O 2 -tolerant [FeFe] hydrogenase from Clostridium beijerinckii using a flexible [GGS] 4 linker group (CbHydA1-PsaE). We demonstrate that the CbHydA1 chimera can be synthetically activated in vitro to show bidirectional activity and that it can be quantitatively bound to a PS I variant lacking the PsaE subunit. When illuminated in an anaerobic environment, the nanoconstruct generates H 2 at a rate of 84.9 ± 3.1 µmol H 2 mg chl –1 h –1 . Further, when prepared and illuminated in the presence of O 2 , the nanoconstruct retains the ability to generate H 2 , though at a diminished rate of 2.2 ± 0.5 µmol H 2 mg chl –1 h –1 . This demonstrates not only that PsaE is a promising scaffold for PS I-based nanoconstructs, but the use of an O 2 -tolerant [FeFe] hydrogenase opens the possibility for an in vivo H 2 generating system that can function in the presence of O 2 .

Hydrogenase↗

Development of a metamodelling framework for building energy models with application to fifth-generation district heating and cooling networks

Fully defined physics-based building energy models can accurately represent building systems; however, generating models based on high-level parameters is time consuming and simulation time of complex models can be slow. This article discusses the development of a Metamodelling Framework to create metamodels from a building energy modelling dataset. The framework generates metamodels using either linear regression, random forests, or support vector regressions. A fifth-generation district heating and cooling system analysis use case was used to motivate the development of the framework. The use case required quick and accurate representations of annual building loads reported hourly. Typical annual building modelling approaches can result in a runtime of 10 min. The metamodels runtime was reduced to less than 10 s to load and run an annual simulation with user-defined covariates. The results of the metamodel performance and an abbreviated topology analysis based on the motivating use case will be presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding the electromagnetic topology during the ohmic breakdown in tokamaks considering self-generated electric fields

We report that the physical mechanisms of the ohmic breakdown in a tokamak have been understood based on the classical Townsend avalanche theory. However, a new systematic theory (Yoo et al 2018 Nat. Commun.9 3523) recently demonstrated that electron avalanches during the ohmic breakdown are completely different from the Townsend avalanche due to strong self-generated electric fields. In this study, we elucidate the multi-dimensional effects of the self-generated electric field on plasma dynamics during the ohmic breakdown. We also propose a novel electromagnetic topology analysis method that can easily predict the overall plasma behavior and where the main plasma is generated. The topology analysis method is validated by a state-of-art particle simulation for various magnetic configurations. New physical insights into the complex electromagnetic topology would facilitate designing more reliable and optimized ohmic breakdown scenarios in future tokamaks, such as ITER and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Metal oxide candidates for thermochemical water splitting obtained with a generative diffusion model

Generative diffusion models (DMs) for inorganic crystalline materials are being actively investigated for their potential to expand the chemical and structural design spaces for known functional materials. Generative candidates are particularly useful for applications where few functional, let alone commercially viable, materials currently exist, such as metal oxides for thermochemical water-splitting, which have strict requirements for defect thermodynamics and host stability. Here, we critically examine generated metal oxides from the M ATTER G EN DM conditioned on select chemical systems for thermochemical water splitting applications. Perhaps most notably, we find that M ATTER G EN predicts a novel, thermodynamically stable, quinary metal oxide, Ba 2 SrInFeO 6 , although this compound represents an ordered and layered substitution within the same A 3 B 2 O 6 structural prototype as its two ternary end members. Detailed density functional theory calculations and spin configuration sampling for this material and its possible decomposition products—beyond what existed in M ATTER G EN training data—are required to quantitatively validate hull energy predictions and conclusions of stability. Furthermore, the material exhibits oxygen defect formation energies appropriate for thermochemical water splitting, warranting targeted investigation in an experimental validation campaign, along with other future M ATTER G EN candidates in this application space.

36 MATERIALS SCIENCE↗

Searching for optimal THz generation through calculations of the asymmetry of photoelectron momentum distributions by an improved strong-field-approximation method

From the solution of the time-dependent Schrödinger equation (TDSE), it has been shown that in a two-color laser pulse the relative phase that optimizes terahertz (THz) radiation also optimizes the asymmetry of the angular distribution of photoelectrons. Here, in this work, we show that a second-order strong-field approximation can accurately calculate the asymmetry of photoelectrons and thus can locate the phase delay that optimizes THz generation, doing so four orders of magnitude faster than TDSE calculations. We further trace that this is possible because THz emission originates from a free-free radiative transition between the rescattered electron and the target ion, similar to other electron-ion collisions in the laser field, e.g., high-harmonic generation and nonsequential double ionization. Our results pave the way to locate the optimal phase delay for any typical laser pulses for maximal THz generation in the laboratory.

74 ATOMIC AND MOLECULAR PHYSICS↗

Multiple Carrier Generation at an Exceptionally Low Energy Threshold

Multiple carrier generation (MCG), a process wherein two or more carriers are generated from a single high-energy absorbed photon, holds immense promise for quantum sensing, metrology, low-threshold lasers, and photovoltaics. Despite its potential, MCG has faced obstacles such as low efficiency and a high threshold photon energy at least twice the band gap (2?Eg) of the semiconductor, limiting its application only to a class of materials with low Eg. Here, we present a new approach that overcomes this limitation by leveraging carrier-donor scattering to excite secondary electrons from donor states strategically positioned below the conduction band. Our method relies on strong Coulomb interaction, reduced dielectric screening, slow hot carrier cooling, and strictly follows the energy conservation rules. We experimentally demonstrated this idea in a model system of monolayer (1L) MoS2 by exploiting electron-donating chalcogen vacancy states. We observed an exceptionally low MCG threshold of ~1.12?Eg for the first time in 1L MoS2. Remarkably, the quantum yield can be further increased to >3 by increasing the photon energy to 1.65?Eg, representing a substantial advancement over existing methods. Our findings extend the horizon of MCG into next-generation high-performance optoelectronic devices with an on-demand operating spectral range spanning from infrared to ultraviolet.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

Scalable Wind Turbine Generator Bearing Fault Prediction Using Machine Learning: A Case Study

Operation and maintenance (O&M) costs for wind turbines pose a risk to competitiveness and asset owners. With machine-learning technologies and digitalization rapidly maturing, the wind industry is actively investigating these new technologies to optimize O&M practices and reduce costs. This paper reviews recent work on machine-learning approaches to generator bearing failure prediction and presents a relevant real-world case study through a collaboration between the National Renewable Energy Laboratory and Envision Digital Corporation. In the case study, we evaluate the performance of representative machine-learning algorithms for predicting wind turbine generator bearing failures. Operational supervisory control and data acquisition data from one wind power plant was used to train and test the machine-learning models. The investigated data channels are chosen based on whether physically they reflect the failed generator bearing conditions and the component historical usage, including both environmental and operational conditions. Benefits and drawbacks of different methods are identified.

generator bearing failures↗

Dynamic P-Q Capability and Abnormal Operation Analysis of a Wind Turbine with Doubly-Fed Induction Generator

After several accidents occurred in wind farms in the United States and around the world, the subsynchronous oscillation (SSO) issues in grid-connected wind farms have gained serious attention. Particularly, these issues have caused significant challenges to wind turbines with a doubly fed induction generator (DFIG) because it is connected to the grid via both its stator and rotor paths. Traditionally, a P-Q capability chart is utilized to assure the safe operation boundary for a synchronous generator. But the energy conversion characteristics of a DFIG wind turbine are completely different. A critical factor to affect the reliable operation of a DFIG wind turbine is the rated current and pulse-width modulation (PWM) saturation constraints of its power converters. These constraint conditions can be affected by the wind turbine rotating speed and grid conditions. However, a detailed study of DFIG P-Q capability from these perspectives has not been conducted, which has hindered adequate understanding of many abnormal wind turbine operations reported in the literature and the development of advanced control technologies to overcome the challenges. The proposed study in this paper considers vector control implementation to DFIG power electronic converters in the dq reference frame, and the models and algorithms developed for the P-Q capability study have addressed specific DFIG power converter constraints that are different from those of a traditional synchronous generator. The paper especially focuses on exploring the dynamic natures of DFIG P-Q capability under uncertain and variable conditions to explore the root causes of many abnormal operations of DFIG wind turbines reported in the literature. The proposed study is validated through an electromagnetic transient simulation model of a grid-connected DFIG wind turbine. The proposed study has the potential to lead to the development of new DFIG control technologies that can help overcome the challenges for many abnormal operations of DFIG wind turbines.

17 WIND ENERGY↗

Data-driven Minimum Entropy Control for Stochastic Nonlinear Systems using the Cumulant-Generating Function

Here, we present a novel minimum entropy control algorithm for a class of stochastic nonlinear systems subjected to non-Gaussian noises. The entropy control can be considered as an optimization problem for the system randomness attenuation, but the mean value has to be considered separately. To overcome this disadvantage, a new representation of the system stochastic properties was given using the cumulant-generating function based on the moment-generating function, in which the mean value and the entropy was reflected by the shape of the cumulant-generating function. Based on the samples of the system output and control input, a time-variant linear model was identified, and the minimum entropy optimization was transformed to system stabilization. Then, an optimal control strategy was developed to achieve the randomness attenuation, and the boundedness of the controlled system output was analyzed. The effectiveness of the presented control algorithm was demonstrated by a numerical example. In this paper, a data-driven minimum entropy design is presented without pre-knowledge of the system model; entropy optimization is achieved by the system stabilization approach in which the stochastic distribution control and minimum entropy are unified using the same identified structure; and a potential framework is obtained since all the existing system stabilization methods can be adopted to achieve the minimum entropy objective.

42 ENGINEERING↗

Robust Output Feedback Control Design for Inertia Emulation by Wind Turbine Generators

Wind generation has gained widespread use as a renewable energy source. Most wind turbines and other renewables connected to the grid through converters result in a reduction in the natural inertial response to grid frequency changes. The doubly-fed induction generator (DFIG) can be controlled to compensate for this reduction and, in fact, provide faster response than traditional synchronous machines. This paper proposes to design observer based output feedback linear quadratic regulator (LQR) and H control laws to realize the inertia emulation function and deliver fast frequency support. Furthermore, the aim is to track the reference speed by a diesel synchronous generator (DSG) in order to reach the desired inertia. The control signal is computed based on a reduced order model using the balanced truncation technique. A comparison with selective modal analysis (SMA) and balanced truncation model reduction techniques is presented. Comprehensive results show the effective emulation of synthetic inertia by implementing the control laws on a nonlinear three- phase diesel-wind system. The proposed technique is analyzed for different short circuit ratio (SCR) scenarios.

17 WIND ENERGY↗