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At least 37 records · Page 2

Quantification of Load Flexibility in Residential Buildings Using Home Energy Management Systems

With increasing penetration of renewable energy resources, the flexibility of operating behind-the-meter (BTM) resources plays a key role in enhancing grid reliability and resilience. Residential buildings with home energy management systems (HEMS) can provide desired flexibility for the distribution system operator (DSO) while considering customer comfort and preferences. This paper discusses a methodology to quantify the flexibility of BTM resources of residential buildings using HEMS. First, we propose a model predictive control framework to formulate the flexibility band comprising nominal, upper, and lower demand profiles. Second, the paper proposes a dispatch method for HEMS to compute the control signals for each BTM resource (e.g., air conditioner, water heater, home battery system) upon receiving a flexibility service request from the DSO. The case study provides insight into the flexibility provided at the whole-home level with different user preferences and seasons. The results demonstrate that HEMS is capable of providing flexibility service at the request of the DSO while delivering primary services to the building occupants.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Stochastic Home Energy Management Systems with Varying Controllable Resources

This paper studies the performance of a model predictive control (MPC) algorithm in a home energy management system (HEMS) as the set of controllable resources varies and under both a constant and a time-of-use (TOU) electricity price structure. The set of controllable resources includes residentially-owned photovoltaic (PV) panels, a home battery system (HBS), an electric vehicle (EV), and a home heating, ventilation, and air conditioning (HVAC) system. The HEMS optimally schedules the set of controllable resources given user preferences such as indoor thermal comfort and electricity cost sensitivity. The home energy management system is built on a chance constrained, MPC-based algorithm, where the chance constraint ensures the indoor thermal comfort is satisfied with a high probability given uncertainty in the outdoor temperature and solar irradiance forecasts. Simulation results for varying sets of controllable resources under two different electricity price structures demonstrate the variation in the HEMS control with respect to HBS operation, electricity cost, and grid power usage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding Operando Water Management in Hydroxide‐Exchange‐Membrane Fuel Cells

The water balance in hydroxide-exchange-membrane fuel cells (HEMFCs) is a key challenge for improved performance and durability, intimately linked with the various interfaces and coupled phenomena. For every 4 electrons produced, 4 water molecules are generated in the anode and 2 consumed in the cathode, while electroosmosis transports water across the HEM from the cathode to the anode. Consequently, a concentration gradient drives water back, from anode to cathode. Ineffective water management could lead to cathode dry-out, limiting reaction rate and causing ionomer degradation, or to anode flooding. To address these concerns, it is critical to measure the water transport operando . Herein, a home-built water-flux station is used to measure total water flux during cell operation with different inlet relative humidities and back pressures. Increasing the HEM thickness fourfold decreases the water flux at high current density, and utilizing microporous layers on both the anode and cathode decreases the water flux from the anode to the cathode. However, the most significant variable in changing the water flux was found by increasing the anode back pressure. Furthermore, humidity cycling significantly changed electrochemical performance without affecting the overall water fluxes. These findings can be translated to other devices utilizing an HEM.

AEMFC↗

Across the Board: Sheng Dai on Catalyst Design by Entropic Factors

In this series of articles, the board members of ChemSusChem discuss recent research articles that they consider of exceptional quality and importance for sustainability. This entry features Dr. S. Dai, who discusses high-entropy materials (HEMs) as new materials in catalysis. In this viewpoint, two types of HEMs (alloy and non-alloy HEMs), their synthesis, and their application in various catalytic reactions are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Oxidative instability of ionomers in hydroxide-exchange-membrane water electrolyzers

Hydroxide-exchange membrane (HEM) electrolyzers can produce green H 2 with only earth-abundant catalysts and electrolyte-free (nominally pure) water feed, significantly decreasing system cost and complexity. However, HEM technology suffers from short lifetimes, attributed in part to poor stability of anion-exchange polymers used in the membrane and catalyst layers. We use electrochemical analysis and ex situ characterization techniques to study anion-exchange-polymer degradation in electrolyzers. Using multiple ionomers, catalyst-layer additives, and electrolyte feed, we show how anode-ionomer oxidation is the dominant degradation mechanism for all HEM-based electrolyzer cells tested. Here, we find improved device stability using oxidation-resistant catalyst-layer binders and propose new design strategies for advanced ionomer and catalyst-layer development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Beyond the four core effects: revisiting thermoelectrics with a high-entropy design

Low-exergy waste heat, which constitutes the majority of industrial-scale thermal losses, remains largely unrecoverable with conventional technologies. Thermoelectrics offer a solid-state solution for converting this hard-to-access energy into electricity, making them attractive for decentralized power generation and sensor applications. High-entropy materials (HEMs) have gained traction as a strategy for better-performing thermoelectrics, but the mechanisms driving their benefits require further exploration. This article highlights key insights for heat and electronic transport in HEMs. For heat transport, we argue that reduced, and often ultralow, lattice thermal conductivity in HEMs—with respect to ordered counterparts—can be taken for granted, emerging naturally as a fifth core effect of high-entropy systems. While band convergence is often considered beneficial for electronic transport, its impact depends strongly on the electronic structure. We summarize the scenarios where it can be detrimental to thermoelectric performance. These insights motivate strategies that align seamlessly with advancements in artificial intelligence and data-driven approaches, helping accelerate the discovery of next-generation thermoelectric materials.

Oses, Corey [Johns Hopkins Univ., Baltimore, MD (U↗

Era of entropy: Synthesis, structure, properties, and applications of high-entropy materials

The field of high-entropy materials (HEMs) has emerged as a dynamic area of scientific exploration, driven by the exceptional properties arising from their compositional complexity. Encompassing both high-entropy alloys (HEAs) and high-entropy ceramics (HECs), these materials have garnered significant attention across diverse research domains. From investigations into phase evolution and mechanical characteristics to studies of ionic, electronic, and magnetic behaviors, HEMs demonstrate remarkable potential for a wide array of applications. These range from catalysis and tribology to energy storage and superconductivity. Fundamental research has shed light on crucial phenomena such as configurational entropy, lattice distortion, and sluggish diffusion. These discoveries are paving the way for materials design strategies that enable new functional tunability and resistance to application-specific harsh environments. This burgeoning field promises to revolutionize material design and performance across numerous technological sectors. Here, this special collection between Applied Physics Letters and the Journal of Applied Physics provides a timely overview of the latest research in this area. It highlights the growing interest in understanding the impact of high compositional complexity on conventional structure–process–property–performance relationships in HEMs.

36 MATERIALS SCIENCE↗

Optimizing Bendability and Hardness of Age-Hardenable Aluminum Sheets through Local Thermo-Mechanical Processing

This paper introduces a novel thermo-mechanical process to modify the local mechanical properties of 6xxx aluminum (Al-Mg-Si-Cu) alloy sheets. In this process, two pairs of rollers travel along the length of a sheet while locally bending and unbending it so that the final shape and thickness of the sheet remains unchanged. Room temperature bending/unbending (B/U) produces a deformation gradient through thickness and local hardening in both T4 and T6 sheets (with 41% and 18% greater Vickers hardness, respectively). High temperature bending/unbending performed at ~ 500°C via induction heating, produces significant improvements in local formability as measured by bend testing. Formability levels equivalent to the as-received T4 temper are achieved within the processed zones of T6 sheets with bend angles of ~ 150°, without disturbing the T6 temper in the remainder of the sheet. Finite element simulations and characterization explained the mechanical property improvements and the heterogenous microstructure with weakened Cube texture. Due to its similarity with the roller hemming process, and its compact dimensions, the apparatus developed for B/U has the potential for seamless integration with roller hemming robots to selectively process high strength aluminum sheet materials within mass-production settings.

Efe, Mert [BATTELLE (PACIFIC NW LAB)]↗

High-entropy materials: fundamentals and applications

Metallic high-entropy materials (HEMs), also known as high-entropy alloys (HEAs), are an exotic class of materials that possess desirable properties, such as exceptional strength and ductility, high wear resistance, and corrosion resistance. Due to these positive attributes, HEAs have been proposed for use in the automotive and aerospace industries, nuclear reactor technology, and the biomedical field. In terms of composition, HEAs contain five or more elements in amounts ranging from 5 to 35 atomic percent (at.%) each, resulting in a vast compositional space that is still mainly unexplored to this day. More recently, the field of HEMs has broadened to include materials such as polymers and ceramics.

36 MATERIALS SCIENCE↗

Influence of Supporting Electrolyte on Hydroxide Exchange Membrane Water Electrolysis Performance: Anolyte

Hydroxide-exchange-membrane water electrolysis (HEMWE) is an emerging hydrogen-production pathway that combines many advantages of incumbent alkaline water electrolysis (AWE) and proton-exchange-membrane water electrolysis (PEMWE). Advancement in HEMWE has been accelerated with the development of stable and conductive hydroxide exchange membranes (HEMs) and a more comprehensive understanding of alkaline gas-evolving kinetics. However, performance and durability without supporting electrolytes (SELs) remain inferior to PEMWE and AWE and little is known about the role and impact of the SELs. This study investigates the effects of SELs used as anolyte solutions in HEMWEs including cation-type, anion-type, SEL conductivity and pH, presence of carbonates and increased cation/OH- ratios on cell voltage and stability. We report our findings that (i) cell potential and high-frequency resistance did not correlate with anolyte SEL conductivity, (ii) cation-type influences cell voltage at low current densities (<50 mA cm -2 ) as predicted by half-cell measurements, (iii) increased cation/OH- ratio causes increased overpotentials, and (iv) carbonates are exchanged in the HEM but removed via self-purging at high current density. Overall, this study concludes that concentrated KOH is still the best SEL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage

Buildings with solar photovoltaic (PV) generation and a stationary battery energy storage system (BESS) may self-sustain an uninterrupted full-level electricity supply during power outages. The duration of off-grid operation is dependent on the time of the power fault and the capabilities of the home energy management system (HEMS). In this paper, building resilience is quantified by analyzing the self-sustainment duration for all possible power outages throughout an entire year. An evaluation method is proposed and exercised on a reference house in California climate zone 9 for which the detailed electricity usage is simulated using the EnergyPlus software. The influence of factors such as energy use behavioral patterns, energy storage capacity from the BESS, and an electric vehicle (EV) battery on the building resilience is evaluated. Varying combinations of energy storage and controllable loads are studied for optimally improved resilience based on user preferences. It is shown that for the target home and region with a solar PV system of 7.2 kW, a BESS with a capacity of 11 kWh, and an EV with a battery of 80 kWh permanently connected to the home, off-grid self-sustained full operation is guaranteed for at least 72 h.

14 SOLAR ENERGY↗

High-Entropy Metal Sulfide Nanoparticles Promise High-Performance Oxygen Evolution Reaction

Transition metal sulfide with a multi-elemental nature represents a class of promising catalysts for oxygen evolution reaction (OER) owing to its good catalytic activity. However, its synthesis remains a grand challenge due to the thermodynamic immiscibility of the constituent multimetallic elements in a sulfide structure. Herein, we for the first time report a high-entropy metal sulfide (HEMS, i.e., (CrMnFeCoNi)Sx) solid solution nanoparticles. Computational and X-ray photoelectron spectroscopy analysis suggest that the (CrMnFeCoNi)S x exhibits a synergistic effect among metal atoms that leads to desired electronic states to enhance OER activity. The (CrMnFeCoNi)Sx nanoparticles showed one of the best activities (low overpotential 295 mV at 100 mA cm -2 in 1 M KOH solution) and good durability (only slight polarization after 10 hours by chronopotentiometry) compared with the unary, binary, ternary, and quaternary sulfide counterparts. This work opens up a new synthesis paradigm for high-entropy compound nanoparticles for highly efficient electrocatalysis applications.

25 ENERGY STORAGE↗

Review: Magnesium Sheet Alloy Development for Room Temperature Forming

Sheet metal forming operations in the automotive industry, including stamping, flanging, bending, hemming and trimming, are dominantly done at room temperature (RT). Unfortunately, the poor RT formability of magnesium due to its hexagonal close packed (HCP) structure and generally strong texture has limited the use of these processes in high-volume automotive production. However, the formability of magnesium can be improved via fine grain structure and random texture to enable some RT forming operations. Here, this paper presents the latest magnesium alloy development and evaluation by the United States Automotive Materials Partnership (USAMP) in collaboration with its university partners. A new sheet alloy developed in a recent USAMP project, ZAXME11100 (USAMP Alloy 2 Plus), offers excellent ductility (31% tensile elongation) and RT formability (7.8 mm Erichsen Index) in solution-treated condition (T4), and a high yield strength (270 MPa) upon post-forming aging treatment (T6), promising RT forming for automotive applications.

36 MATERIALS SCIENCE↗

The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

We report ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility's distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood's load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes' energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community's demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance estimation of resonance-enhanced dual-buoy wave energy converter using coupled time-domain simulation

This article presents the modeling methodology and performance evaluation of the resonance-enhanced dual-buoy WEC (Wave Energy Converter) by HEM (hydrodynamic & electro-magnetic) fully-coupled-dynamics time-domain-simulation program. The numerical results are systematically compared with the authors’ 1/6-scale experiment. With a direct-drive linear generator, the WEC consists of dual floating cylinders and a moon-pool between the cylinders, which can utilize three resonance phenomena from moon-pool dynamics as well as heave motions of inner and outer buoys. The contact and friction between the two buoys observed in the experiment are also properly modeled in the time-domain simulation by the Coulomb-friction model. Moon-pool resonance peaks significantly exaggerated in linear potential theory are empirically adjusted through comparisons with measured values. A systematic comparative study between the simulations and experiments with and without PTO (power-take-off) is conducted, and the relative heave displacements/velocities and power outputs are well matched. Then, parametric studies are carried out with the simulation program to determine optimum generator parameters. The performance with various wave conditions is also assessed.

16 TIDAL AND WAVE POWER↗

Elucidating the reversible exsolution–dissolution behaviour of high-entropy oxides in crystalline and amorphous phases

High-entropy oxides (HEOs), as a subclass of high-entropy materials (HEMs), offer a versatile platform for catalysis by leveraging entropy-stabilized solid solutions with tunable compositions, lattice structures, and electronic properties. While exsolution–dissolution of metal species in crystalline HEOs has emerged as a promising strategy for reversible active sites regeneration, the dynamic behaviour of HEOs possessing amorphous nature remains under-explored, particularly the difference with crystalline counterparts. In this work, we systematically investigate the architecture-dependent exsolution–dissolution behavior of HEOs by comparing a crystalline-phase HEO (c-HEO) and an amorphous-phase HEO (a-HEO), both comprising Ni, Mg, Cu, Zn, and Co as principal metal elements. Using a combination of in situ variable-temperature X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), electron microscopy, and in situ CO diffuse reflectance infrared Fourier transform spectroscopy (CO-DRIFTS), the structural evolution of the two HEO phases under redox conditions was elucidated. Both materials exhibit reversible exsolution of metallic species or alloys in reducing environments, followed by re-incorporation into the host lattice upon oxidation. Remarkably, the a-HEO demonstrates more facile and dynamic self-healing behavior, with alloy exsolution and dissolution occurring under milder conditions because of its enhanced reducibility and structural disorder. This study provides critical insights into the design of next-generation regenerable catalysts based on amorphous HEOs, highlighting the role of phase structure in governing reversible metal-site formation dynamics and catalytic performance.

Wang, Qingju [Univ. of Tennessee, Knoxville, TN (U↗

Disentangling the confounding spectroscopy of C 1 molecules: Without symmetry as a guide, everything is allowed

The spectra of C 1 molecules are confounding in that each of the fundamental vibrational modes transform as the same irreducible representation (A) and hence each band consists of a seemingly random distribution of a-, b-, and c-type transitions. This is in contrast to higher symmetry molecules for which band types are readily deduced by simple symmetry rules. Herein, we present a method to simulate the convoluted rotational contours in the gas-phase spectra of C 1 molecules by combining existing ab initio calculations with Colin Western’s PGOPHER rotational contour program. Specifically, ab initio calculations in the NWC HEM suite of programs were employed to predict the components of the dipole moment derivatives along the principal axes of the moments of inertia. This information was then input into PGOPHER to model the fundamental band contours as a sum of a-, b-, and c-type transitions. This method was applied to simulate the rotational contour spectra of a series of representative C 1 molecules which were then compared against both ab initio stick spectra and experimentally measured broadband IR spectra from the Pacific Northwest National Laboratory infrared gas-phase database. In addition to providing further insight beyond what is revealed in a typical stick spectrum, the simulated contours showed good agreement with the measured spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unbundling Smart Meter Services Through Spatio-Temporal Decomposition Agents in DER-rich Environment

Smart meters and the advanced metering infrastructure (AMI) facilitate distribution system operators (DSOs) to gather information on energy consumption at the customer level. With the increasing penetration of building-level intermittent distributed energy resources (DERs) behind the meter, DER information is not available to DSOs. At the same time, smart meter enables users to participate in grid, with real-time information. Information for behind the meter is needed by user to coordinate building level assets for maximum benefits. The concept of unbundled smart meter (USM) needs agents to decompose smart meter measurements to provide service to DSO as well as customers. In this paper, we propose a Spatio-Temporal Decomposition Agent (STDA) for USM based on Artificial Intelligence (AI). STDA can help users optimize their energy usage, help DSO to utilize building assets for the grid operation. The energy usage strategy developed by STDA is suitable for different users, and can be customized by deep learning (DL) models according to the different energy consumption habits of each user. The power prediction performance results of various DL models and evaluation using a set of data from a Hawaii utility is presented. Furthermore, STDA integration with Home Energy management Systems (HEMS) to manage resources is presented and validated. STDA pre-processes the measurements before model training, and provides the spatio-temporal decomposed forecasting.

42 ENGINEERING↗