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Restraining the rapid growth of operational carbon emissions from residential buildings is critical to achieve carbon neutrality. To illustrate the future decarbonization roadmap, this study builds an end-use emissions model to analyze past decarbonization efforts and projected emission change in China's residential building operations by mid-century. From 2001 to 2018, residential building operations reduced emissions by 2.77 (±1.61) giga tons of carbon dioxide (GtCO2). Dynamic simulation results of the emission model reveal that residential building operations will peak in 2031 (±3) with 0.95 (±0.06) GtCO2. Energy-related carbon intensity (∼44%) and energy intensity (∼36%) are identified as the primary factors affecting carbon peak status, with heating (∼87%) playing a crucial role in energy intensity. A feasible emission path towards carbon neutrality suggests limiting urban and rural residential building emissions to 0.38 and 0.27 GtCO2 in 2030, respectively, and offsetting only 0.03 and 0.01 GtCO2 in urban and rural regions by 2060, to become carbon free. Overall, the study proposes a stepwise data analysis benchmark to decarbonize the residential building operations of top emitters, contributing to global building decarbonization in the era of carbon neutrality.

Preparing halide perovskite films by solvent-free, powder-based processing approaches currently attracts more and more attention. However, working solar cells employing dry, powder-based halide perovskite thin films, have not been demonstrated so far. Herein, perovskite solar cells are presented where the absorber layer is prepared by transferring readily synthesized perovskite powders into a compact thin film using a fully dry-powder-processing concept. Compact thin films are deposited via an optimized powder aerosol deposition (PAD) process. Pressing at 120 °C further improves the morphology and the optoelectronic film properties. Integrating the perovskite films in a solar cell configuration results in fully working devices, with champion power conversion efficiencies of >6%. While the (optoelectronic) properties of the PAD-processed films are found to be comparable with their solution-processed counterparts, investigations of the solar cell stack suggest deterioration of the electron-transport layer properties due to the PAD process, and the presence of hydrates at the perovskite surface to be important factors that contribute to the limited solar cell efficiency. Herein, perspectives to overcome the identified limitations are outlined, emphasizing the high potential and realizability of efficient perovskite solar cells based on dry-powder-processing approaches in the future.

Building and microgrid designs with highly-distributed electrical storage have potential advantages over today's conventional topologies with centralized storage. This paper studies the capital cost benefits of several residential behind-the-meter distributed-storage topologies, including AC and DC versions of systems with load-packaged batteries and resilient sub-networks. The study begins by defining the block configuration of each topology. This work then develops a model for the cost of the power electronics necessary to interface with the storage elements. Finally, the analysis develops a model for the total cost of each storage topology, incorporating the installation and soft costs. The results suggest that while the cost of power electronics is lower in centralized topologies, the total cost is lower for distributed storage due to the avoided costs of installation and permitting. This paper also explores the benefits of load-packaged batteries for savings in electrical infrastructure.

Reducing the thickness of separation membranes without compromising their selectivity and robustness is the most effective way of maximizing the areal conductivity. This is especially important for the integration of visible light-driven water oxidation and carbon dioxide (or proton) reduction into a complete artificial photosystem on the shortest possible length scale - the nanoscale - because of the efficiency advantages over macroscale photosystems. In addition to their excellent separation property, ultrathin membranes of 10 nm thickness or less need to exhibit sufficient electrical and proton conductivity in order for the photocatalytic rates to keep up with the photon flux at maximum solar intensity. Two materials, graphene and amorphous silica with embedded molecular wires, have emerged as promising ultrathin membranes for the development of nanoscale integrated solar-fuel systems. Moreover, electrically conducting metal-organic or covalent-organic frameworks can be used to fabricate high surface area-supports that enable the use of molecular catalysts and/or light absorbers at an adequate areal density for nanoscale integration with graphene membranes. Following an overview of the electron and proton conductivity of these ultrathin materials and recent examples of photoelectrocatalytic applications that take advantage of some but not all the properties that constitute a complete functional membrane, the status and future opportunities for complete nanoscale integrated photosystems featuring an ultrathin membrane are discussed.

Proton exchange membrane fuel cells (PEMFCs) are leading candidates to decarbonize the transport sector, but widespread deployment will require improvements in lifetime, fuel economy and cost. Here we present the grooved electrode, an alternative electrode structure that enhances PEMFC performance and durability by coupling high ionomer (ion-conducting binder) content for improved H+ transport with grooves for rapid O2 transport. Grooved electrodes provide up to 50% higher performance than state-of-the-art conventional electrodes under standard operating conditions. Fuel cell diagnostics combined with multiphysics modelling demonstrate that grooved electrodes provide facile O2 transport despite their high ionomer content, enabling improved reaction rate uniformity. Grooved electrodes also provide improved durability, with less performance loss after carbon corrosion compared with baseline electrodes. Machine learning analysis demonstrates the potential to further optimize grooved structures for next-generation PEMFCs with enhanced performance and durability, enabling smaller and cheaper fuel cell stacks with higher fuel efficiency.

Wearable devices and fitness trackers have gained popularity in healthcare and telemedicine as tools to reduce hospitalization costs, improve personalized health management, and monitor patients in remote areas. Smartwatches, particularly, offer continuous monitoring capabilities through step counting, heart rate tracking, and activity monitoring. However, despite being recognized as an emerging technology, the adoption of smartwatches in patient monitoring systems is still at an early stage, with limited studies delving beyond their feasibility. Developing healthcare applications for smartwatches faces challenges such as short battery life, wearable comfort, patient compliance, termination of non-native applications, user interaction difficulties, small touch screens, personalized sensor configuration, and connectivity with other devices. This paper presents a case study on designing an Android smartwatch application for remote monitoring of geriatric patients. It highlights obstacles encountered during app development and offers insights into design decisions and implementation details. The aim is to assist programmers in developing more efficient healthcare applications for wearable systems.

Maintaining reliability is increasingly challenging for electric grids as they endure more frequent extreme weather events and utilize more intermittent generation. Exploration of alternative reliability approaches is needed to effectively address these emerging issues. Here we examine the potential to use the US rail system as a nationwide backup transmission grid over which containerized batteries, or rail-based mobile energy storage (RMES), are shared among regions to meet demand peaks, relieve transmission congestion and increase resilience. We find that RMES is a feasible reliability solution for low-frequency, high-impact events and quantify its cost effectiveness relative to reliability-driven investments in transmission infrastructure and stationary capacity. Compared to new transmission lines and stationary battery capacity, deploying RMES for such events could save the power sector upwards of US$300 per kW-year and US$85 per kW-year, respectively. While no known technical barriers exclude RMES from grid participation, addressing interconnection challenges and revising regulatory frameworks is necessary for deployment at scale.

Electromagnetics has been shown to be a viable tool to monitor CO2 plumes embedded in saline reservoirs. However, the majority of studies focus on measuring the electric field, which requires cumbersome equipment in the field and it is difficult to install permanent measurement stations. Magnetic field receivers offer an opportunity to reduce the form factor of the survey and increase the mobility by utilizing upcoming technologies, such as drones. We explore the use of frequency-domain electric dipole sources, and time-domain loops with a focus on measuring the secondary magnetic field at the surface for a conceptual injection scenario based on the Kemper CarbonSAFE site. We find that electric dipole sources give a response above the sensitivity of current sensor technology and, therefore, be a viable tool for CO2 monitoring. The time-domain loop source does provide fields that are useful for determining the location of the CO2 plume, however the field magnitude is below the sensitivity of the current generation of instruments. To explore the use of a potential borehole receiver we generate a map of the magnetic field at depth to explore potential borehole placement for monitoring efforts. Finally, we limit the spatial extent of the electric dipole survey to a single parcel of land to help understand how the fields change with survey geometry. We find that the shape of the secondary fields change slightly with the small transmitter, but are still measurable provided that the cultural noise at the site is low. Thus, we conclude that at the Kemper site a frequency-domain cross-dipole source with magnetometer receivers is suitable to monitor the expansion of the CO2 plume in the saline reservoir, even with a limited transmitter footprint on the surface.

Ammonia is a promising energy and hydrogen carrier due to its ease of liquification, high hydrogen content, and potential to be synthesized without carbon feedstocks. Despite its widespread use in agriculture, the utilization of ammonia to deliver hydrogen or for direct power generation is still under development. Sometimes referred to as “cracking”, the standard approach for recovering hydrogen from ammonia relies on harsh reaction conditions that limit its suitability for low-carbon transitions. This work investigates the technology development status and potential cost of plasma and electrolysis-based ammonia decomposition, benchmarks them with thermal-chemical decomposition, and further compares them with direct ammonia-to-power solid oxide fuel cell systems. Results suggest that in order to reach cost parity with cracking technologies, plasma-based decomposition must achieve one order of magnitude improvement in energy efficiency (to 10 kWh/kg or lower), while electrolysis decomposition must achieve enhanced durability using cheap electrolytes.

Densely distributed sensor networks can revolutionize environmental observations by providing real-time data with an unprecedented spatiotemporal resolution. However, field deployments often pose unique challenges in terms of power provisions and wireless connectivity. We present a framework for wirelessly connected distributed sensor arrays for near-surface temperature and/or deformation monitoring. Our research focuses on a novel time division duplex implementation of the LoRa protocol, enabling battery powered base stations and avoiding collisions within the network. In order to minimize transmissions and improve battery life throughout the network, we propose a dedicated delta encoding algorithm that utilizes the spatial and temporal similarity in the acquired data sets. We implemented the developed technologies in a AA battery powered hardware platform that can be used as a wireless data logger or base station, and we conducted an assessment of the power consumption. Without data compression, the projected battery life for a data logger is 4.74 years, and a wireless base stations can last several weeks or months depending on the amount of network traffic. The delta encoding algorithm can further improve this battery life with a factor of up to 3.50. Our results demonstrate the viability of the proposed methods for low-power environmental wireless sensor networks.

Customer concerns over electric system resilience could drive early adoption of behind-the-meter solar-plus-storage (BTM PVESS), especially as wildfire, hurricane, and other climate-driven risks to electric grids become more pronounced. However, the resilience benefits of BTM PVESS are poorly understood, especially for residential customers, owing to lack of data and methodological challenges, making it difficult to forecast adoption trends. In this paper, we develop a methodology to model the performance of BTM PVESS in providing backup power across a wide range of customer types, geography / climate conditions, and long duration power interruption scenarios, considering both whole-building backup and backup of specific critical loads. We combine novel, disaggregated end-use load profiles across the continental United States with temporally and geospatially aligned solar generation estimates. We then implement a PVESS dispatch algorithm to calculate the amount of load served during interruptions. We find that PVESS with 10 kWh of storage can meet a limited set of critical loads in most United States counties during any month of the year, though this capability drops to meeting only 86% of critical load, averaged across all counties and months, when heating and cooling are considered critical. Backup performance is lowest in winter months where electric heat is common (southeast and northwest U.S.) and in summer months in places with large cooling loads (southwest and southeast U.S.). Winter backup performance varies by roughly 20% depending on infiltration rates, while summer performance varies by close to 15% depending on the efficiency of the central air-conditioning system. Differences in temperature set-points in Harris County correspond to a 40% range in winter backup performance and a 20% range in summer performance. Economic calculations show that a customer's resilience value of PVESS must be high to motivate adoption of these systems.

This paper investigates the energy performance and sizing criteria of 5th generation district heating and cooling (5GDHC) networks as a function of the heat distribution temperature in the building systems connected to the district network. An energy simulation model of a 5GDHC network was developed in Modelica for a case study located in Denmark. Calculations were carried out for four different building heating systems. Simulation results show that reducing the heat distribution temperatures from 70 °C to 23 °C leads to around 40% annual electric energy savings (from 10.4 kWh/m2 to 6.2 kWh/m2) for the operation of the heat pumps. Heat distribution temperatures of 23 °C cause higher water mass flow rates through the network, leading to annual electric energy consumption for the circulation pumps that are almost doubled (from 0.16 kWh/m2 to 0.3 kWh/m2) compared to the reference case at 70 °C. Furthermore, the paper discusses how the results obtained from the Danish case study can be generalized and applied to other cases using a simplified mathematical approach. It is found that about 1.5% of electric energy savings can be achieved for each temperature degree reduction in the heat distribution system.

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By operating resonant switched-capacitor converters at resonance, zero current switching (ZCS) can be achieved to eliminate voltage-current overlap losses. Previous literature has shown that zero voltage switching (ZVS) can also be achieved to further reduce switching losses and attain a higher peak efficiency by recovering the charge stored in the parasitic output capacitance of the switches. Contrary to ZCS operation, ZVS timing is highly dependent on load current even with ideal primary passive components. This paper proposes a novel digital control technique that can dynamically track the optimum ZVS timing across a wide range of load current, through passive component and voltage variations. The proposed concept is validated in a 48-V-to-24-V resonant switched-capacitor (ReSC) converter prototype, demonstrating over 10% power loss reduction compared with the conventional open-loop ZVS, and approximately 30% power loss reduction compared with ZCS.

Hybrid switched-capacitor (SC) converters have gained popularity due to their efficient switch utilization and use of energy-dense capacitors, which allows them to achieve high efficiency and power density even at large conversion ratios. The Dickson converter is one such popular hybrid SC converter, as it can achieve the theoretical minimum switch stress rating for a given operating condition. However, unlike other hybrid SC topologies that can automatically achieve full soft-charging through the addition of one or more augmenting inductors, certain Dickson variants also require the use of special switching schemes to fully soft-charge all flying capacitors. This technique, denoted as split-phase switching, inserts extra sub-phases into the control scheme so that flying capacitors are disconnected or connected at staggered times. Traditionally, split-phase timing has been calculated analytically, sometimes using imprecise models. This paper instead proposes an active control technique for detecting hard-charging events on the flying capacitors, such that the split-phase timing automatically converges on soft-charging operation. The technique is validated on an 8-to-1 resonant single-inductor Dickson hardware prototype. While this method is demonstrated on a resonant fixed-ratio converter in this work, the technique can also be applied to regulating split-phase applications, as well as used to detect hard-charging events in general.

The series-capacitor buck (SCB) converter is a compact and highly-efficient alternative to the multi-phase buck converter and has recently been demonstrated in data center applications. To achieve high power density, it is desirable to reduce the total flying capacitance in this topology. However, for sufficiently small flying capacitances, a discontinuous capacitor voltage mode (DCVM) manifests, leading to an imbalance in inductor currents. This work provides a detailed derivation of the relationship between the critical capacitance describing the onset of DCVM and converter operating parameters. Moreover, the inductor current imbalance is characterized through the development of a clamped steady-state model. To recover balancing when flying capacitance below the critical value is used, a technique to drive the branches with modified duty cycles in a constant power regime is proposed. Experimental validation of the steady-state model and recovery of inductor current balancing are demonstrated on a 4-branch SCB prototype.

With both data center power delivery and automotive powertrains tending towards a 48V distribution rail, high performance hybrid switched-capacitor (hybrid SC) converters have become an attractive power delivery solution in both spaces. However, automotive power systems present unique challenges in reliability and noise qualifications. This work investigates a regulating Dickson-based hybrid SC topology with low inherent electromagnetic interference (EMI) as well as mitigation techniques, such as an input filter and spread spectrum frequency modulation (SSFM). The proposed filter and modulation schemes enable this converter to meet automotive EMI standards. A hardware prototype combining a power stage and passive input filter is built to demonstrate the merit of hybrid SC topologies for use in 48V automotive systems.

Photovoltaic (PV) systems can operate off the maximum power point (MPP) for various reasons. Understanding when off- MPP behavior occurs is essential to the maintenance and operation (O&M) of PV systems. To detect off-MPP data, a reference power is usually needed, which can be obtained by system modeling that generally relies on physical model parameters. Traditional methods commonly obtain these parameters based on the initial condition of the PV system such as from the module datasheet. However, these parameters often do not reflect the current condition of the on-site PV system, which is likely to suffer from degradation and faults after years of operation with degraded parameters. Thus, we propose an off-MPP analysis algorithm based on the PV-Pro method, which can extract the model parameters (like series and shunt resistance) at the current operating condition only using the routine production data. In this way, the system power, current, and voltage can be accurately modeled. The off-MPP points are detected by comparing the measured power with the one modeled by PV-Pro. Points with large disagreement in power are further analyzed by deconvolving it into the error of the current and voltage at MPP, which allows tracing the error source of the off- MPP and provides valuable information for the O&M of PV systems. This off-MPP analysis is demonstrated on a 271kW PV field system, where it is shown that most of the off- MPP points are caused by the reduced DC current.

Alternative computing approaches that interface readily with physical systems are well suited for embedded control of those systems. We demonstrate finite state machines implemented as pneumatic circuits of microfluidic valves and use these controllers to direct microfluidic liquid handling procedures on the same chip. These monolithic integrated systems require only power to be supplied externally, in the form of a vacuum source. User input can be provided directly to the chip by covering pneumatic ports with a finger. State machines with up to four bits of state memory are demonstrated, and next-state combinational logic can be fully reprogrammed by changing the hole-punch pattern on a membrane in the chip. These pneumatic computers demonstrate a framework for the embedded control of physical systems and open a path to stand-alone lab-on-a-chip devices capable of highly complex functionality.

The fabrication of organic solar cells (OSCs) by a layer-by-layer (LBL) method has attracted growing attention in recent years. As already known, the pre-aggregates of conjugated polymers in solution have a profound impact on their microstructure morphology in films. Herein, by simply controlling the solution temperature and annealing processes, the pre-aggregation behavior of D18 polymer in solution can be fine-tuned and the microstructure of D18 bottom layer is well manipulated. The optimized D18 bottom layer can effectively regulate L8-BO upper-layer-forming suitable networks for efficient charge transportation. In addition, a vertical phase separation with a special D/D:A/A structure (P-i-N-type component distribution) is also formed. As a result, compared to the 16.43% power conversion efficiency (PCE) of the bulk heterojunction devices, such control enables bilayer OSC devices based on the polymer D18 and L8-BO to deliver an enhanced PCE of 18.02% with simultaneously improved short-circuit current density, open-circuit voltage, and fill factor. It is also demonstrated in these results that the LBL deposition process utilizing the pre-aggregation of polymer and its fiber-network-forming ability is a very promising approach to improve charge dynamics, suppress carrier recombination, and fabricate highly efficient OSCs.

The chemical and electronic structure of the interface between a sputter-deposited Zn(O,S) buffer layer and an industrial Cu(In,Ga)(S,Se)2 (CIGSSe) absorber for thin-film solar cells is investigated with X-ray and UV photoelectron spectroscopy, inverse photoemission spectroscopy, and X-ray emission spectroscopy. We find a CIGSSe absorber surface band gap of 1.61 (±0.14) eV, which is significantly increased as compared to the minimal value derived with bulk-sensitive methods (≈1.1 eV). We find no indication for diffusion of absorber elements into the buffer layer. Surface- and bulk-sensitive measurements of the buffer layer suggest the presence of S-Zn and S-O bonds in the Zn(O,S) layer. We find that the naturally existing downward band bending toward the CIGSSe absorber surface is increased by the formation of the interface, likely enhancing carrier separation under illumination. We also derive a flat conduction band alignment, in line with the reported high conversion efficiencies of corresponding large-area solar cells.

Oil supply-side policies—setbacks, excise taxes and carbon taxes—are increasingly considered for decarbonizing the transportation sector. Understanding not only how such policies reduce oil extraction and greenhouse gas (GHG) emissions but also which communities receive the resulting health benefits and labour-market impacts is crucial for designing effective and equitable decarbonization pathways. Here we combine an empirical field-level oil-production model, an air pollution model and an employment model to characterize spatially explicit 2020–2045 decarbonization scenarios from various policies applied to California, a major oil producer with ambitious decarbonization goals. We find setbacks generate the largest avoided mortality benefits from reduced air pollution and the largest lost worker compensation, followed by excise and carbon taxes. Setbacks also yield the highest share of health benefits and the lowest share of lost worker compensation borne by disadvantaged communities. However, currently proposed setbacks may fail to meet California’s GHG targets, requiring either longer setbacks or additional supply-side policies.