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Industrial process heat decarbonization through electrification could contribute significantly to climate change mitigation efforts. In the US industry, thermal processes accounted for more than two-thirds of the total final energy demand in 2021. Cross-cutting electrification technologies like industrial heat pumps are suitable for the process heat supply to several industrial unit operations in a sustainable way while also improving overall energy efficiency. This study employs a bottom-up approach to investigate the techno-enviro-economic potentials of deploying high-temperature and steam-generating heat pumps in US textile, pulp and paper, and automotive sectors in different timeframes. The results show that the annual technical potential energy and CO2 savings by electrifying heat supply are 310 PJ (or 36% of the projected energy demand) and 28 MtCO2 (or 71% of the projected CO2 emissions) in 2050 respectively, however, these incur additional costs in each sector (ranging between 5 and 18 $/GJ). The required heating capacity of industrial heat pumps is estimated at 15 GW, which translates roughly into a market of over 6000 heat pump units and an investment volume of $7 billion in the studied processes. Although there may be individual cost-effective opportunities for electrifying heat supply in specific industrial sites, the overall costs are estimated to be high in the three industrial sectors due to the large disparity between electricity and natural gas prices and low heat source temperatures. To overcome the identified techno-economic barriers, comprehensive action plans for different stakeholders are also given. This study provides novel insights that should inform policymakers’ and executives’ decisions about the electrification of the current and future US industrial heat supply in relevant industrial sectors.

The development of highly specific biomimetic recognition material is a challenge for rapid detection of harmful residues in foodstuff. In this study, a paper-based boronate affinity metal-organic framework/molecularly imprinted polymer microfluidic chip (FZS-BA@MIP) was constructed based on the in situ construction strategy, which was also designed as a highly specific biomimetic recognition module. Here, the homogeneous zeolitic imidazole framework-8 (ZIF-8) membrane served as a great scaffold and enrichment layer. Besides, the recognition layer of MIP was prepared based on a highly oriented boronate affinity surface imprinting strategy. With the aid of the liquid flow channel, the highly specific enrichment and visual detection for antibiotic residues like kanamycin in actual products were achieved on the paper chip module of an integrated lateral flow platform. The whole analysis process could be accomplished within 30 min. In brief, this study offered a new integrated biomimetic recognition platform for visually detecting harmful veterinary residues containing cis-diols, which demonstrated promising commercial value in point-of-care testing of foodborne hazardous compounds.

Loop-mediated isothermal amplification (LAMP) has been widely used to detect many infectious diseases. However, minor inconveniences during the steps of adding reaction ingredients and lack of simple color results hinder point-of-care detection. We therefore invented a fluorometric paper-based LAMP by incorporating LAMP reagents, including a biotinylated primer, onto a cellulose membrane paper, with a simple DNA fluorescent dye incubation that demonstrated rapid and accurate results parallel to quantitative polymerase chain reaction (qPCR) methods. This technology allows for instant paper strip detection of methicillin-resistant Staphylococcus aureus (MRSA) in the laboratory and clinical samples. MRSA represents a major public health problem as it can cause infections in different parts of the human body and yet is resistant to commonly used antibiotics. In this study, we optimized LAMP reaction ingredients and incubation conditions following a central composite design (CCD) that yielded the shortest reaction time with high sensitivity. These CCD components and conditions were used to construct the paper-based LAMP reaction by immobilizing the biotinylated primer and the rest of the LAMP reagents to produce the ready-to-use MRSA diagnostic device. Our paper-based LAMP device could detect as low as 10 ag (equivalent to 1 copy) of the MRSA gene mecA within 36-43 min, was evaluated using both laboratory (individual cultures of MRSA and non-MRSA bacteria) and clinical blood samples to be 100% specific and sensitive compared to qPCR results, and had 35 day stability under 25 °C storage. Furthermore, the color readout allows for quantitation of MRSA copies. Hence, this device is applicable for point-of-care MRSA detection.

In the present article we report a new hybrid microfluidic device (hyFlow) comprising a disposable paper electrode and a three-dimensional (3D) printed plastic chip for the electrochemical detection of a magnetic bead-silver nanoparticle (MB-AgNP) bioconjugate. This hybrid device evolved due to the difficulty of incorporating micron-scale MBs into paper-only fluidic devices. Specifically, paper fluidic devices can entrap MB-containing conjugates within their cellulose or nitrocellulose fiber matrix. The hyFlow system was designed to minimize such issues and transport MB conjugates more efficiently to the electrochemical detection zone of the device. The hyFlow system retains the benefit of fluid transport by pressure-driven flow, however, no pump is required for its operation. The hyFlow device is capable of detecting either pre-formed MB-AgNP conjugates or conjugates formed in situ. The detection limit of AgNPs using this device is 12 pM, which represents just 22 AgNPs per MB.

Paper-based microfluidic devices are an attractive platform for developing low-cost, point-of-care diagnostic tools. As paper-based devices' detection chemistries become more complex, more complicated devices are required, often entailing the sequential delivery of different liquids or reagents to reaction zones. Most research into flow control has been focused on introducing delays. However, delaying the flow can be problematic due to increased evaporation leading to sample loss. We report the use of a CO2 laser to uniformly etch the surface of the paper to modify wicking speeds in paper-based microfluidic devices. This technique can produce both wicking speed increases of up to 1.1× faster and decreases of up to 0.9× slower. Wicking speeds can be further enhanced by etching both sides of the paper, resulting in wicking 1.3× faster than unetched channels. Channels with lengthwise laser-etched grooves were also compared to uniformly etched channels, with the most heavily grooved channels wicking 1.9× faster than the fastest double-sided etched channels. Furthermore, sealing both sides of the channel in packing tape results in the most heavily etched channels, single-sided, double-sided, and grooved, wicking over 13× faster than unetched channels. By selectively etching individual channels, different combinations of sequential fluid delivery can be obtained without altering any channel geometry. Laser etching is a simple process that can be integrated into the patterning of the device and requires no additional materials or chemicals, enabling greater flow control for paper-based microfluidic devices.

Paper microfluidic devices (including lateral flow assays) offer an excellent combination of utility and low cost. Many paper microfluidic devices are fabricated using the Xerox ColorQube line of commercial wax-based color printers; the wax ink serves as a hydrophobic barrier to fluid flow. These printers are capable of depositing four different colors of ink, cyan (C), magenta (M), yellow (Y), and black (K), plus 11 combinations of these colors (CM, CY, CK, MY, MK, YK, CMY, CMK, CYK, MYK, and CMYK), although most researchers use only black ink to print paper microfluidic devices. Recently, as part of a project to develop a computer-aided design framework for use with paper microfluidics devices, we unexpectedly observed that different colors of wax ink behave differently in paper microfluidics. We found that among the single colors of ink, black ink actually had the most barrier failures, and magenta ink had the fewest barrier failures. In addition, some combinations of colors performed even better than magenta: the combinations CY, MK, YK, CMY, CYK and MYK had no barrier failures in our study. We also found that the printer delivers significantly different amounts of ink to the paper for the different color combinations, and in general, the color combinations that formed the strongest barriers to fluid flow were the ones that had the most ink delivered to the paper. This suggests that by simply weighing paper samples printed with all 15 combinations of colors, one can easily find the color combinations most likely to form a strong barrier for a given printer. Finally, to show that deliberate choices of ink colors can actually be used to create new functions in paper microfluidics, we designed and tested a new color-based "antifuse" structure that protects paper microfluidic devices from a typical operator error (addition of too much fluid to the device). Our results provide a set of color choice guidelines that designers can use to control the behavior of their paper microfluidics.

This paper introduces a novel software framework to support automated development of paper-based microuidic devices. Compared to existing lab-on-a-chip technologies, paper-based microuidics difiers in terms of substrate technologies and point-of-care usage across a wide variety environmental conditions. This paper addresses the contexts in which the software can address these challenges and presents several initial case studies that demonstrate the capabilities of the framework to produce workable and usable paper microuidic devices.

In this paper, we present an experimental study on measurement of the thermal conductivity and heat pipe effect in both hydrophilic and hydrophobic (Toray TGP-H60) carbon papers (around 200 μm thickness) with/out liquid water. An experimental setup is developed for measuring thermal conductance at different liquid water contents and temperatures without dissembling the testing device for water addition. Theoretical analysis is also performed to evaluate the apparent conductance of heat pipe effect. We found that liquid water presence inside these materials increases the overall thermal conductivity. At high temperature around 80 °C, the heat pipe effect is evident for the hydrophilic paper; while for the hydrophobic one, the heat pipe effect is found to be smaller. The distinction is likely due to the different patterns of the capillary liquid flow in the two media. For the hydrophobic paper, liquid water flows back to the evaporation side when the breakthrough pressure is reached and flow is through preferred routes of small flow resistance. As a result, heat pipe effect is active only in part of the medium, therefore smaller than that in the hydrophilic one. The results are important for understanding the heat transfer phenomena occurring in porous media and effects of material surface property. © 2012 Elsevier Ltd. All rights reserved.

In this paper, we present an experimental study on measurement of the thermal conductivity and heat pipe effect in both hydrophilic and hydrophobic (Toray TGP-H60) carbon papers (around 200 μm thickness) with/out liquid water. An experimental setup is developed for measuring thermal conductance at different liquid water contents and temperatures without dissembling the testing device for water addition. Theoretical analysis is also performed to evaluate the apparent conductance of heat pipe effect. We found that liquid water presence inside these materials increases the overall thermal conductivity. At high temperature around 80 °C, the heat pipe effect is evident for the hydrophilic paper; while for the hydrophobic one, the heat pipe effect is found to be smaller. The distinction is likely due to the different patterns of the capillary liquid flow in the two media. For the hydrophobic paper, liquid water flows back to the evaporation side when the breakthrough pressure is reached and flow is through preferred routes of small flow resistance. As a result, heat pipe effect is active only in part of the medium, therefore smaller than that in the hydrophilic one. The results are important for understanding the heat transfer phenomena occurring in porous media and effects of material surface property. © 2012 Elsevier Ltd. All rights reserved.

Electrospinning, a process that converts a solution or melt droplet into an ejected jet under a high electric field, is a well-established technique to produce one-dimensional (1D) fibers or two-dimensional (2D) randomly arranged fibrous meshes. Nevertheless, the direct electrospinning of fibers into controllable three-dimensional (3D) architectures is still a nascent technology. Here, we apply near-field electrospinning (NFES) to directly write arbitrarily shaped 3D structures through consistent and spatially controlled fiber-by-fiber stacking of polyvinylidene fluoride (PVDF) fibers. An element central to the success of this 3D electrospinning is the use of a printing paper placed on the grounded conductive plate and acting as a fiber collector. Once deposited on the paper, residual solvents from near-field electrospun fibers can infiltrate the paper substrate, enhancing the charge transfer between the deposited fibers and the ground plate via the fibrous network within the paper. Such charge transfer grounds the deposited fibers and turns them into locally fabricated electrical poles, which attract subsequent in-flight fibers to deposit in a self-aligned manner on top of each other. This process enables the design and controlled fabrication of electrospun 3D structures such as grids, walls, hollow cylinders, and other 3D logos. As such, this technique has the potential to advance the existing electrospinning technologies in constructing 3D structures for biomedical, microelectronics, and MEMS/NMES applications.

Sub-1 nm, extremely long nickel molybdate nanowires are synthesized based on a good/poor solvent system. The ultrathin nanowires can be hierarchically assembled into flexible, free-standing films with good mechanical properties. Compared with the large-size counterpart, nickel molybdate ultrathin nanowires display promising oxygen evolution reaction catalytic performance derived from the ultrathin feature.

Heart attack is mainly caused by the rupture of a vulnerable plaque. IVUS-OCT is a novel medical imaging modality that provides opportunities for accurate assessment of vulnerable plaques in vivo in patients. IVUS provides deep penetration to image the whole necrotic core while OCT enables accurate measurement of the fibrous cap of a plaque owing to its high resolution. In this paper, the authors describe the fundamentals, the technical designs and the applications of IVUS-OCT technology. Results from cadaver specimens are summarized, which indicated the complementary nature of OCT and IVUS for assessment of vulnerable plaques, plaque composition, and stent-tissue interactions. Furthermore, previously reported in vivo animal experiments are reviewed to assess the clinical adaptability of IVUS-OCT. Future directions for this technology are also discussed in this review.

This comment addresses the work of Wang and Li (DOI: 10.1007/s12293-009-0012-0, hereafter referred to as WL) published online on September 01, 2009 in a (special) issue of Memetic Computing. We respectfully beg to differ in opinion with WL and argue that the concept of multi-strategy evolutionary search used by WL is not particularly novel. Similar ideas have been presented elsewhere, and these publications date back to at least early 2007. For instance, in a series of papers published in PNAS (2007), SSSAJ (2008), WRR (2008), IEEE-TEVC (2009), JH (2010), Vrugt and coworkers have introduced AMALGAM, a multi-method (or ensemble) search approach to solve emerging single and multiple objective search and optimization problems. In the past few years, MATLAB, C++, Python, and R implementations of AMALGAM have been distributed extensively among researchers and practitioners in various fields of study.

A partnership of affluent nations is proposed to pursue the objective of universal electrification in the world with a challenging interim goal of bringing efficient and sustainable[2] 2 For the purposes of this paper sustainable electric systems are those that emit low or no net greenhouse gases (GHGs). This requirement is generally consistent with the goal expressed in the National Research Council report Our Common Journey: a Transition Toward Sustainability [National Research Council, 1999]: "... that the primary goals of transition toward sustainability should be to meet the needs of a much larger but stabilizing population, to sustain the life support systems of the planet and to sustainably reduce hunger and poverty." The authors believe that the electric systems targeted in the universal electrification proposal of this paper can contribute to the goals of the transition explored by the academy. The partners must assure this contribution, but for simplicity the authors use the criterion of low or no net greenhouse gas emissions from electricity generation to qualify a system as sustainable. electric services within 20 years to one billion people. Four plausible partners are the United States, the European Union, Japan with Australia and New Zealand, and, perhaps, the OPEC countries. The partners would provide part of the capital needed for electrification. This "concessionary" contribution should stimulate private investors and/or indigenous governments to supply the remainder of the capital needed, and to organize the management of each electrification project. The concessionary contribution would be designed for two objectives: (1) to help alleviate poverty, grow opportunities, and increase the quality of life in the developing world by providing electric services to all, and (2) to reduce future greenhouse gas emissions by supporting a low-carbon development path toward universal electrification. Paying for the difference in cost between high-efficiency end-use equipment and least-first-cost equipment would pursue the first objective. This concession would significantly lower the cost to the consumer of electricity services. The second objective would be pursued by paying the added cost (up to $ 1000/kW) of low-GHG or climate-friendly electricity generation (i.e., low or no-net carbon-emitting systems) over and above least-first-cost generation technology. This electrification of one billion people would require about 50 GWe of new electric generating capacity assuming 50% capacity factor and 15% line losses. The concessionary investment needed would be up to $50 billion for low-GHG generation plus about $30 billion for efficient end-use equipment. An additional 25% of the concessionary contribution would go for training, program management and evaluation. The total is $ 100 billion (or $ 100/person) spread over 20 years, or about $ 1.25 billion per partner per year assuming an equal share for each partner. The remainder of the capital required is estimated to be about $ 170/person for the electrical system including hook-up, plus another $ 140/person for efficient end-use equipment purchased at the cost of least-first-cost equipment. The consumer would pay back these non-concessionary investments through the price of electricity and through a lease-purchase charge for end-use equipment. Provision of basic electricity services for newly electrified communities is estimated to require about 0.025 kW/person on average for all electric uses including domestic, commercial, agricultural and industrial uses, compared with current electricity services of about 1.8 kW/person in the United States and 0.3 kW/person globally. Thus, electric power per capita in these poor, mostly rural areas would be very small initially, just sufficient to meet basic necessities, and consistent with customers' ability to pay. Not every community would choose or be able to buy even this much, but to have the opportunity for electric services at whatever level will make a huge difference in people's lives. Experience over many decades has shown that electrification can help alleviate poverty, improve health, reduce drudgery, and increase literacy, all contributing to the UN's Millennium Development Goals to which all countries are committed. © 2005 International Energy Initiative, Inc.

Moss et al.(2005) describe, in a recent paper, a filter that they use to detect lines. We noticed that the wavelet on which this filter is based is a difference of uniform filters. This filter is an approximation to the second derivative operator, which is commonly implemented as the Laplace of Gaussian (or Marr-Hildreth) operator (Marr & Hildreth, 1980; Jahne, 2002), Figure 1. We have compared Moss' filter with 1) the Laplace of Gaussian operator, 2) an approximation of the Laplace of Gaussian using uniform filters, and 3) a few common noise reduction filters. The Laplace-like operators detect lines by suppressing image features both larger and smaller than the filter size. The noise reduction filters only suppress image features smaller than the filter size. By estimating the signal to noise ratio (SNR) and mean square difference (MSD) of the filtered results, we found that the filter proposed by Moss et al. does not outperform the Laplace of Gaussian operator. We also found that for images with extreme noise content, line detection filters perform better than the noise reduction filters when trying to enhance line structures. In less extreme cases of noise, the standard noise reduction filters perform significantly better than both the Laplace of Gaussian and Moss' filter.

Predictive high-fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch-control, stall/vortex-induced vibrations, and aftermarket add-ons. The biggest challenge with high-fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high-performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU-enabled open-source incompressible-flow hybrid-computational fluid dynamics framework, comprising the near-body unstructured grid solver Nalu-Wind, and the off-body block-structured-grid solver AMR-Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds-averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds-averaged Navier–Stokes is used for near-body flow and large eddy simulation is used for off-body flow. Being two-way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry-resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt-scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states.

Correction to: Transport in Porous Media (2024) 151:55–84https://doi.org/10.1007/s11242-023-02033-0. There are three numbers in Table 2 of the original paper that were incorrect. Specfically, the value of the density of hydrogen (H2) for the DB model and the values of density and viscosity of H2 for the TOUGH2 model listed in Table 2 of the original paper were incorrect. (Table presented.) Properties of the H2-water upconing system for comparison against the DB model. Property DB model Used for TOUGH2 Gas cap thickness, total reservoir thickness, and radial extent (outer radius) of the reservoir Infinite, infinite, infinite 50 m, 100 m (with open boundary at bottom), 100 m (open boundary condition) Porosity (ϕ) 0.10 0.10 Permeability (kH) 1.0 × 10−12 m2 1.0 × 10−12 m2 Permeability (kV) 1.0 × 10−12 m2 1.0 × 10−12 m2 Relative permeability (krel) Not applicable Linear with Slr = 0.99 Distance from well to H2-water interface (d) 10 m 10 m Extraction rate of rate of H2 (Qm) − 5.5 kg s−1 − 5.5 kg s−1 Density of water 996 kg m−3 996 kg m−3 Density of H2 7.32 kg m−3 7.87 kg m−3 Viscosity of water 6.54 × 10−4 Pa s 5.11 × 10−4 Pa s Viscosity of H2 9.31 × 10−6 Pa s 9.53 × 10−6 Pa s A corrected Table 2 is shown below. The erroneous values in Table 2 were not used in any of the modeling and simulation. Accurate values for density and viscosity in the modeling and simulation come from CoolProp for the DB model and from EOS7CH for the TOUGH2 simulations.

Abstract: This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb-1 of LHC proton-proton collision data recorded at √(s) = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at E T ∼ 10 GeV, and 0.3% at E T ∼ 1 TeV; for photons at E T ∼ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays.

Although gold nanorods have been the subject of much research, the pathways for controlling their shape and thereby their optical properties remain largely heuristically understood. Although it is apparent that the simultaneous presence of and interaction between various reagents during synthesis control these properties, computational and experimental approaches for exploring the synthesis space can be either intractable or too time-consuming in practice. This motivates an alternative approach leveraging the wealth of synthesis information already embedded in the body of scientific literature by developing tools to extract relevant structured data in an automated, high-throughput manner. To that end, we present an approach using the powerful GPT-3 language model to extract structured multi-step seed-mediated growth procedures and outcomes for gold nanorods from unstructured scientific text. GPT-3 prompt completions are fine-tuned to predict synthesis templates in the form of JSON documents from unstructured text input with an overall accuracy of 86% aggregated by entities and 76% aggregated by papers. The performance is notable, considering the model is performing simultaneous entity recognition and relation extraction. We present a dataset of 11 644 entities extracted from 1137 papers, resulting in 268 papers with at least one complete seed-mediated gold nanorod growth procedure and outcome for a total of 332 complete procedures.

This paper examines building energy flexibility at an aggregated level and addresses the main barriers and research gaps for the development of this resource across three design and development phases: market and policy, early planning and design, and operation. We review methodologies and tools and discuss barriers, challenges, and opportunities, incorporating policy, economic, technical, professional, and social perspectives. Although various legal and regulatory frameworks exist to foster the development of energy flexibility for small buildings, financing mechanisms are limited with a significant number of perceived risks undermining private investment. For the early planning and design phase, planners and designers lack appropriate tools and face interoperability challenges, which often results in insufficient consideration of demand response programs. The review of the operational phase highlighted the socio-technical challenges related to both the complexity of deployment and communication, as well as privacy and acceptability issues. Finally, the paper proposes a number of targeted research directions to address challenges and promote greater energy flexibility deployments, including capturing building demand side dynamics, improving baseline estimations and developing seamless connectivity between buildings and districts.

Correction to: Nature Energy. Published online 25 May 2023. This paper was originally published under a standard Springer Nature license (© The Author(s), under exclusive licence to Springer Nature Limited). It is now available as an open-access paper under a Creative Commons Attribution 4.0 International license, © The Author(s). The error has been corrected in the online version of the article.

K-12 schools are the largest energy consumers in the public sector, with their HVAC energy consumption representing the largest portion of their total energy use. While transitioning these schools to grid-interactive HVAC system operation through advanced controls offers significant financial and environmental benefits, and model predictive control (MPC) has been identified as a promising solution to achieve that, very few MPCs are affordable and have been deployed in K-12 schools. This situation raises concerns about the unclear real-world benefits of MPC technology among facility managers and industries. To address this gap, this paper presents a low-cost MPC solution that requires minimal control infrastructure costs and a unique field demonstration at a K-12 school, conducted for both cooling and heating seasons. This work adopted a previously developed MPC and extended it for use in the school application. The MPC aims to coordinate multiple packaged units to eliminate unnecessary peaks and shift cooling or heating loads in response to grid signals based on load conditions, while maintaining thermostat temperatures within school-defined bounds. Throughout the field tests, the MPC achieved a 24% reduction in peak demand during the cooling season and shifted cooling or heating loads by up to 16% in response to the school's utility tariff, considering load conditions, while also allowing end-users to override thermostat setpoints. The paper also discusses the limitations of this study and future research directions for better performance of the MPC at K-12 schools.

This paper introduces the District Optimization Testing (DOPTEST) concept, which naturally extends from the Building Optimization Testing (BOPTEST) framework, for simulation-based testing of advanced control strategies in districts. While the focus of the BOPTEST framework is on individual building control, DOPTEST is meant to assess system integration strategies at a district level. This paper lays down the design requirements and modeling methodology for district emulators in DOPTEST and shows a simulation example of its first test case prototype.

As part of the Snowmass'21 community planning excercise, the Advanced Accelerator Concepts (AAC) community proposed future linear colliders with center-of-mass energies up to 15 TeV and luminosities up to 50 × 1034 cm-2 s-1 in a compact footprint. In addition to being compact, these machines must also be energy efficient. We identify two challenges that must be addressed in the design of these machines. First, the Beam Delivery System (BDS) must not add significant length to the accelerator complex. Second, beam parameters must be chosen to mitigate beamstrahlung effects and maximize the luminosity-per-power of the machine. In this paper, we review advances in plasma lens technology that will help to reduce the length of the BDS system and we detail new Particle-in-Cell simulation studies that will provide insight into beamstrahlung mitigation techniques. We apply our analysis to both e + e - and γγ colliders. The challenges and solutions described in this paper are considered independently. A unified, self-consistent concept for a BDS system for a 15 TeV linear collider will be the subject of future work.

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.

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.

ObjectiveWe performed a scoping review of algorithms using electronic health record (EHR) data to identify patients with Alzheimer's disease and related dementias (ADRD), to advance their use in research and clinical care.Materials and methodsStarting with a previous scoping review of EHR phenotypes, we performed a cumulative update (April 2020 through March 1, 2023) using Pubmed, PheKB, and expert review with exclusive focus on ADRD identification. We included algorithms using EHR data alone or in combination with non-EHR data and characterized whether they identified patients at high risk of or with a current diagnosis of ADRD.ResultsFor our cumulative focused update, we reviewed 271 titles meeting our search criteria, 49 abstracts, and 26 full text papers. We identified 8 articles from the original systematic review, 8 from our new search, and 4 recommended by an expert. We identified 20 papers describing 19 unique EHR phenotypes for ADRD: 7 algorithms identifying patients with diagnosed dementia and 12 algorithms identifying patients at high risk of dementia that prioritize sensitivity over specificity. Reference standards range from only using other EHR data to in-person cognitive screening.ConclusionA variety of EHR-based phenotypes are available for use in identifying populations with or at high-risk of developing ADRD. This review provides comparative detail to aid in choosing the best algorithm for research, clinical care, and population health projects based on the use case and available data. Future research may further improve the design and use of algorithms by considering EHR data provenance.

This paper provides a literature review of methods and modeling techniques to estimate the cost of power system outages, along with the value of outage mitigation or system resilience. Regulators, policymakers, and infrastructure owners have a growing need to understand the methods for estimating the benefits of resilience improvements of electric infrastructure against natural and man-made disasters. There is a broad literature that estimates the cost of short-duration outages and a small but developing literature on estimating the cost of long-duration outages. This article reviews the models used to estimate the cost of outages and discusses their relative strengths. Additionally, this paper identifies key questions from stakeholders regarding resilience investment and maps them to the relevant models that would help answer them. We include recommendations for future work to include recent advances in regional economic modeling that can estimate region and demographic-specific costs and the distributional consequences of potential resilience projects.

Control hunting due to improper proportional–integral–derivative (PID) parameters in the building automation system (BAS) is one of the most common faults identified in commercial buildings. It can cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC) equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest growing market segments in smart building technologies in the United States. Implementation of PID retuning procedures as an auto-correction algorithm and integration into FDD software has the potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in a scalable way. This paper presents the development, implementation, and field testing of an automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The algorithm was developed in a commercial FDD software and successfully tested among nine variable air volume boxes in an office building in the United States. The paper shows the feasibility of using FDD tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a path forward for the HVAC industry and academia to further improve this technology.

Simulating the dynamics of a nonequilibrium quantum many-body system by computing the two-time Green's function associated with such a system is computationally challenging. However, we are often interested in the time-diagonal of such a Green's function or time-dependent physical observables that are functions of one time. In this paper, we discuss the possibility of using dynamic mode decomposition (DMD), a data-driven model order reduction technique, to characterize one-time observables associated with the nonequilibrium dynamics using snapshots computed within a small time window. The DMD method allows us to efficiently predict long time dynamics from a limited number of trajectory samples. We demonstrate the effectiveness of DMD on a model two-band system. We show that, in the equilibrium limit, the DMD analysis yields results that are consistent with those produced from a linear response analysis. In the nonequilibrium case, the extrapolated dynamics produced by DMD is more accurate than a special Fourier extrapolation scheme presented in this paper. We point out a potential pitfall of the standard DMD method caused by insufficient spatial/momentum resolution of the discretization scheme. We show how this problem can be overcome by using a variant of the DMD method known as higher order DMD.

This paper investigates the transport of drugs delivered by direct injection into the cerebrospinal fluid (CSF) that fills the intrathecal space surrounding the spinal cord. Because of the small drug diffusivity, the dispersion of neutrally buoyant drugs has been shown in previous work to rely mainly on the mean Lagrangian flow associated with the CSF oscillatory motion. Attention is given here to effects of buoyancy, arising when the drug density differs from the CSF density. For the typical density differences found in applications, the associated Richardson number is shown to be of order unity, so that the Lagrangian drift includes a buoyancy-induced component that depends on the spatial distribution of the drug, resulting in a slowly evolving cycle-averaged flow problem that can be analysed with two-time scale methods. The asymptotic analysis leads to a nonlinear integro-differential equation for the spatiotemporal solute evolution that describes accurately drug dispersion at a fraction of the cost involved in direct numerical simulations of the oscillatory flow. The model equation is used to predict drug dispersion of positively and negatively buoyant drugs in an anatomically correct spinal canal, with separate attention given to drug delivery via bolus injection and constant infusion.

Beer has over 600 flavor compounds and creates a positive tasting experience with acceptable sensory properties, which are essential for the best consumer experience. Spontaneous and mixed-culture fermentation beers, generally classified as sour beers, are gaining popularity compared to typical lager or ale styles, which have dominated in the USA for the last few decades. Unique and acceptable flavor compounds characterize sour beers, but some unfavorable aspects appear in conjunction. One such unfavorable flavor is called "mousy". This description is usually labeled as an unpleasant odor, identifying spoilage of fermented food and beverages. It is related as having the odor of mouse urine, cereal, corn tortilla chips, or freshly baked sour bread. The main compounds responsible for it are N-heterocyclic compounds: 2-acetyltetrahydropyridine, 2-acetyl-1-pyrroline, and 2-ethyltetrahydropyridine. The most common beverages associated with mousy off-flavor are identified in wines, sour beers, other grain-based beverages, and kombucha, which may contain heterofermentative lactic acid bacteria, acetic acid bacteria, and/or yeast/fungus cultures. In particular, the fungal species Brettanomyces bruxellensis are associated with mousy-off flavor occurrence in fermented beverages matrices. However, many factors for N-heterocycle formation are not well-understood. Currently, the research and development of mixed-cultured beer and non/low alcohol beverages (NABLAB) has increased to obtain the highest quality, sensory, functionality, and most notably safety standards, and also to meet consumers' demand for a balanced sourness in these beverages. This paper introduces mousy off-flavor expression in beers and beverages, which occurs in spontaneous or mixed-culture fermentations, with a focus on sour beers due to common inconsistency aspects in fermentation. We discuss and suggest possible pathways of mousy off-flavor development in the beer matrix, which also apply to other fermented beverages, including non/low alcohol drinks, e.g., kombucha and low/nonalcohol beers. Some precautions and modifications may prevent the occurrence of these off-flavor compounds in the beverage matrix: improving raw material quality, adjusting brewing processes, and using specific strains of yeast and bacteria that are less likely to produce the off-flavor. Conceivably, it is clear that spontaneous and mixed culture fermentation is gaining popularity in industrial, craft, and home brewing. The review discusses important elements to identify and understand metabolic pathways, following the prevention of spoilage targeted to off-flavor compounds development in beers and NABLABs.

Hydrogen (H2) combustion and solid oxide fuel cells (SOFCs) can potentially reduce aviation-produced greenhouse gas emissions compared to kerosene propulsion. This paper outlines a methodology for evaluating performance and emission tradeoffs when retrofitting conventional kerosene-powered aircraft with lower-emissionH2 combustion and SOFC hybrid alternatives. The proposed framework presents a constant-range approach for designing liquid hydrogen fuel tanks, considering insulation, sizing, center of gravity, and power constraints. A lifecycle assessment evaluates greenhouse gas emissions and contrail formation effects for carbon footprint mitigation, while a cost analysis examines retrofit implementation consequences. A Cessna Citation 560XLS+ case study shows a 5% mass decrease for H2 combustion and a 0.4% mass decrease for the SOFC hybrid, at the tradeoff of removing three passengers. The lifecycle analysis of green hydrogen in aviation reveals a significant reduction in CO2 emissions for H2 combustion and SOFC systems, except for natural-gas-produced H2 combustion, when compared to Jet-A fuel. However, this environmental benefit is contrasted by an increase in fuel cost per passenger-km for green H2 combustion and a rise for natural-gas-produced H2 SOFC compared to kerosene. The results suggest that retrofitting aircraft with alternative fuels could lower carbon emissions, noting the economic and passenger capacity tradeoffs.

This paper introduces an innovative approach to 3D environmental mapping through the integration of a compact, handheld sensor package with a two-stage sensor fusion pipeline. The sensor package, incorporating LiDAR, IMU, RGB, and thermal cameras, enables comprehensive and robust 3D mapping of various environments. By leveraging Simultaneous Localization and Mapping (SLAM) and thermal imaging, our solution offers good performance in conditions where global positioning is unavailable and in visually degraded environments. The sensor package runs a real-time LiDAR-Inertial SLAM algorithm, generating a dense point cloud map that accurately reconstructs the geometric features of the environment. Following the acquisition of that point cloud, we post-process these data by fusing them with images from the RGB and thermal cameras and produce a detailed, color-enriched 3D map that is useful and adaptable to different mission requirements. We demonstrated our system in a variety of scenarios, from indoor to outdoor conditions, and the results showcased the effectiveness and applicability of our sensor package and fusion pipeline. This system can be applied in a wide range of applications, ranging from autonomous navigation to smart agriculture, and has the potential to make a substantial benefit across diverse fields.

Existing simplified procedures for evaluating soil liquefaction potential or for estimating excess pore pressures during earthquakes are typically based on undrained cyclic tests performed on saturated soil samples under controlled loading and boundary conditions. Under such conditions, the effect of excess pore pressure (ue) dissipation and redistribution to neighboring soil layers cannot be accounted for. Existing simplified procedures treat liquefiable layers as isolated soil layers without any boundary conditions even if dense and loose layers are very thin, permeable, and adjacent to each other. However, redistribution is likely to increase and decrease ue in the neighboring dense and loose layers respectively. Until now, no procedure short of fully coupled numerical analysis is available to estimate the importance of redistribution. This paper presents an approximate analytical procedure for assessing the effects of ue redistribution in (1) soil layers that would have liquefied if they were undrained, and (2) soil layers that would have not liquefied even if undrained. It is found that a layer that is initially assumed liquefied under undrained conditions might not even liquefy accounting for the ue redistribution to neighboring layers. On the other hand, a layer initially assumed to not liquefy can develop significant ue and can even liquefy due to pore pressure migration from the neighboring layers. Thus, accounting for redistributed ue is important for liquefaction consequence assessment quantification, particularly in systems that span the depth of these effects like deep foundations. Migration of u toward the tip of a pile can reduce its capacity, even if the tip is embedded in a dense sand layer. On the other hand, if redistribution can result in the reduction of ue in initially assumed liquefied layers, risks associated with liquefaction might be avoided. A criterion is also developed to evaluate the thicknesses of a layer below which redistribution could prevent liquefaction even if the layer is deemed liquefied according to the existing liquefaction-triggering procedures. Finally, the proposed procedure is illustrated by application to selected shaking events of centrifuge tests involving liquefaction of layered soil profiles. The predictions from the procedure matched the centrifuge test results reasonably.

Proton resonance frequency shift (PRFS) MR thermometry is the most common method used in clinical thermal treatments because of its fast acquisition and high sensitivity to temperature. However, motion is the biggest obstacle in PRFS MR thermometry for monitoring thermal treatment in moving organs. This challenge arises because of the introduction of phase errors into the PRFS calculation through multiple methods, such as image misregistration, susceptibility changes in the magnetic field, and intraframe motion during MRI acquisition. Various approaches for motion correction have been developed for real-time, motion-robust, and volumetric MR thermometry. However, current technologies have inherent trade-offs among volume coverage, processing time, and temperature accuracy. These tradeoffs should be considered and chosen according to the thermal treatment application. In hyperthermia treatment, precise temperature measurements are of increased importance rather than the requirement for exceedingly high temporal resolution. In contrast, ablation procedures require robust temporal resolution to accurately capture a rapid temperature rise. This paper presents a comprehensive review of current cutting-edge MRI techniques for motion-robust MR thermometry, and recommends which techniques are better suited for each thermal treatment. We expect that this study will help discern the selection of motion-robust MR thermometry strategies and inspire the development of motion-robust volumetric MR thermometry for practical use in clinics.

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. We demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times.

Understanding the impact of repository gas, generated from degradation of waste and its interaction with the host rock, is essential when assessing the performance and safety function of long-term disposal systems for radioactive waste. Numerical models based on conventional multi-phase flow theory have historically been applied to predict the outcome and impact of gas flow on different repository components. However, they remain unable to describe the full complexity of the physical processes observed in water-saturated experiments (e.g., creation of dilatant pathways) and thus, the development of novel representations for their description is required when assessing fully saturated clay-based systems. This was the primary focus of Task A within the international cooperative project DECOVALEX-2019 (D-2019) and refinement of these approaches is the primary focus of this study (Task B in the current phase of DECOVALEX-2023). This paper summarises development of enhanced numerical representations of key processes and compares the performance of each model against high-quality laboratory test data. Experimental data reveals that gas percolation in water-saturated compacted bentonite is characterised by four key features: (i) a quiescence phase, followed by (ii) the gas breakthrough, which leads to a (iii) peak value, which is then followed by (iv) a negative decay. Three models based on the multiphase flow theory have been developed. These models can provide good initial values and reasonable responses for gas breakthrough (although some of them still predict a too-smooth response). Peak gas pressure values are in general reasonably well captured, although maximum radial stress differences are observed at 48 mm from the base of the sample. Here, numerical peak values of 12.8 MPa are predicted, whereas experimental values are about 11 MPa. These models are also capable of providing a reasonable representation of the negative pressure decay following peak pressure. However, other key specific features (such as the timing of gas breakthrough) still require a better representation. The model simulations and their comparison with experimental data show that these models need to be further improved with respect to model parameter calibration, the numerical representation of spatial heterogeneities in material properties and flow localisation, and the upscaling of the related physical processes and parameters. To further understand gas flow localisation, a new conceptual model has been developed, which shows that discrete channels can possibly be induced through the instability of gas-bentonite interface during gas injection, thus providing a new perspective for modeling gas percolation in low-permeability deformable media.

A novel approach for determining triaxial residual stress states by coupling energy dispersive X-ray diffraction and contour method measurements is provided and validated in a Ti‐5Al‐5V‐5Mo‐3Cr additive manufactured (AM) bridge sample. Synchrotron X-ray diffraction (SXRD) can provide relatively fine spatial resolution (on the order of 10–100 µm) for mapping 3D elastic strain fields within a sample. However, for samples with dimensions larger than one or two centimeters the path length can get prohibitive as both constant wavelength and energy dispersive SXRD are based upon transmission measurements. As an example, for a plate-like sample geometry where the thickness is limited (less than a centimeter) it is trivial to measure the longitudinal and height direction elastic strain components with excellent in-plane spatial resolution (∼100 µm) and a somewhat lower through-thickness resolution (10–15 times larger) but obtaining the through thickness component is often not possible as the beam path must be parallel to one of the large dimensions of the plate. While small samples of low Z-number alloys (e.g., Ti or Al) allow determination of the three elastic strain components, this is often not the case for higher Z alloys (e.g., Fe or Ni) or large samples where some strain components can be indeterminable. To overcome these limitations, this work applies a combination of synchrotron X-ray diffraction and the contour method (a mechanical relaxation technique), to determine the triaxial stress state. This novel combination is demonstrated and validated in a relatively small additive manufactured sample where all three orthogonal strain components are accessible via X-ray diffraction for stress determination. The paper also explores methods for determining the strain-free lattice parameter, typically obtained from a small stress-free reference sample. This work shows that a small size AM sample is not stress free, producing unreliable magnitudes of strain and stress. Instead, a strain-free lattice parameter is determined using residual stress equilibrium conditions, which gives consistent strain and stress trends for both X-ray diffraction (alone) and the new diffraction-contour coupling technique. This demonstrates that the coupling technique can be confidently applied to samples to determine stress when path length (size or Z-number) prohibit determination of three orthogonal strain components via diffraction.

Buried water reservoirs are increasingly being built to replace open aboveground municipal water supply reservoirs in urban areas to enhance water quality and utilize their surface footprint for other purposes such as public parks or placement of solar arrays. Many of these lifeline structures are in seismically active regions and, as such, need to be designed to remain operational after severe earthquake shaking. However, evaluating their seismic response is challenging and involves accounting for the interaction of the structure with the stored fluid and the retained soil; in other words, accounting for fluid-structure-soil interaction (FSSI). This paper presents a combined experimental-numerical study on the seismic behavior of buried water reservoirs while considering FSSI. Two series of centrifuge model tests were performed at different reservoir orientations to investigate one-dimensional (1D) and two-dimensional (2D) motion effects under full, half-full, and empty reservoir conditions. Corresponding numerical models were developed whereby the structure and the soil were represented by continuum Lagrangian finite elements, while the fluid was modeled via Arbitrary Lagrangian Eulerian formulation. Soil-structure and fluid-structure interface parameters were calibrated using the experimental measurements. The simulations successfully captured the measured reservoir responses in terms of accelerations, bending moment increments, and water pressures. The study found that the common assumption of plane strain is not applicable for reservoirs because their behavior was found to be truly three-dimensional (3D) whereby stresses accumulated at the corners. Furthermore, the full reservoir resulted in the highest seismic demands in the reservoir walls and roof while the empty reservoir yielded the highest base slippage. The study demonstrates that the complex reservoir seismic response is best captured by carrying out a 3D FSSI numerical simulation.

Energy efficiency programs funded by utility customers provide an electricity resource in most U.S. states, but their scale and cost of saving electricity varies significantly by state. In this paper, we explore the drivers of the cost of saved electricity in these programs with an econometric model and nearly a decade of data reported by efficiency program administrators. We found strong evidence for economies of scale and weak evidence for diseconomies of scale, which suggests that states with low levels of efficiency savings relative to retail sales can increase the size of their efficiency programs without large increases to the cost of saved electricity. We discuss examples of energy efficiency forecasting and potential modeling in light our econometric analysis and identify methodological improvements relevant to utilities and grid operators. This paper provides insights into the economics of customer-funded efficiency programs that will support regulators, utilities, and policymakers to utilize energy efficiency as a resource.