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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Scalable tuning of building models to hourly data

Energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Manual tuning requires a skilled professional, is prohibitively expensive for small projects, imperfect, non-repeatable, non-transferable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and cheap/ubiquitous sensors are beginning to make available today. A scalable, automated methodology is needed to quickly and intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The "Autotune'' project is a novel, model-agnostic methodology which leverages supercomputing, large simulation ensembles, and big data mining with multiple machine learning algorithms to allow automatic calibration of simulations that match measured experimental data in a way that is deployable on commodity hardware. This paper shares several methodologies employed to reduce the combinatorial complexity to a computationally tractable search problem for hundreds of input parameters. Furthermore, accuracy metrics are provided which quantify model error to measured data for either monthly or hourly electrical usage from a highly-instrumented, emulated-occupancy research home.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

The environmental and public health benefits of achieving high penetrations of solar energy in the United States

Here, we estimate the environmental and public health benefits that may be realized if solar energy cost reductions continue until solar power is competitive across the U.S. without subsidies. Specifically, we model, from 2015 to 2050, solar power–induced reductions to greenhouse gas (GHG) emissions, air pollutant emissions, and water usage. To find the incremental benefits of new solar deployment, we compare the difference between two scenarios, one where solar costs have fallen such that solar supplies 14% of the nation's electricity by 2030 and 27% by 2050, and a baseline scenario in which no solar is added after 2014. We monetize benefits, where credible methods exist to do so. We find that under these scenarios, solar power reduces GHG and air pollutants by ~10%, from 2015 to 2050, providing a discounted present value of 56–789 billion USD (central value of ~250 billion USD, equivalent to ~2 ¢/kWh-solar) in climate benefits and 77–298 billion USD (central value of 167 billion USD, or ~1.4 ¢/kWh-solar) in air quality and public health benefits. The ranges reflect uncertainty within the literature about the marginal impact of emissions of GHG and air pollutants. Solar power is also found to reduce water withdrawals and consumption by 4% and 9%, respectively, including in many drought-prone states.

14 SOLAR ENERGY↗
DOE OSTI2012

Lifestyle Factors in U.S. Residential Electricity Consumption

A multivariate statistical approach to lifestyle analysis of residential electricity consumption is described and illustrated. Factor analysis of selected variables from the 2005 U.S. Residential Energy Consumption Survey (RECS) identified five lifestyle factors reflecting social and behavioral choices associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use. These factors were also estimated for 2001 RECS data. Multiple regression analysis using the lifestyle factors yields solutions accounting for approximately 40% of the variance in electricity consumption for both years. By adding the associated household and market characteristics of income, local electricity price and access to natural gas, variance accounted for is increased to approximately 54%. Income contributed only {approx}1% unique variance to the 2005 and 2001 models, indicating that lifestyle factors reflecting social and behavioral choices better account for consumption differences than income. This was not surprising given the 4-fold range of energy use at differing income levels. Geographic segmentation of factor scores is illustrated, and shows distinct clusters of consumption and lifestyle factors, particularly in suburban locations. The implications for tailored policy and planning interventions are discussed in relation to lifestyle issues.

03 NATURAL GAS↗
DOE OSTI2018

Are vulnerable customers any different than their peers when exposed to critical peak pricing: Evidence from the U.S.

Recent broad-based deployment of Advanced Metering Infrastructure (AMI) enables the opportunity for broader adoption of time-based rates, and the benefits that result have been sizable contributors to making the investments cost effective. However, some stakeholders have raised concerns about the assumptions underlying the benefits assessments in AMI business cases. Such concerns are especially acute for certain subpopulations of residential customers. Low income, elderly and chronically ill (i.e., vulnerable) customers are believed to have less load that can be shifted or reduced to capture bill savings, lack the know-how or wherewithal with which to curtail usage, likely have more limited financial resources which may compel them to avoid high priced periods by reducing electricity for essential usage potentially causing them physical harm, and more generally may be more adversely affected by higher bills, which might possibly result from certain forms of time-based rates. There is very limited existing literature that addresses these questions specifically with regard to vulnerable subpopulations. This paper, based on a larger report, extends the existing empirical literature on the experiences of low-income customers exposed to critical peak pricing, and provides the first glimpses into the experiences of the elderly and those who reported being chronically ill.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Self-reported sunscreen use and urinary benzophenone-3 concentrations in the United States: NHANES 2003–2006 and 2009–2012

Background: Sunscreens protect against skin cancer and other harmful effects of solar ultraviolet radiation (UVR). Epidemiologic and public health surveys often rely on self-reported sunscreen use to estimate sun exposure and avoidance, but questions remain about the validity of self-reports. Benzophenone-3 (BP-3), a common sunscreen ingredient, can be detected in the urine. Prior studies suggest that BP-3 concentrations increase after application of sunscreen. Objectives: The goal of this study was to assess the validity of self-reported frequency of sunscreen use in relation to urinary BP-3 concentrations in a representative sample of the general US population, including in sub-groups defined by age, sex and race/ethnicity. Methods: To assess the relationship between categorical self-reported sunscreen use and creatinine-corrected urinary BP-3 concentrations, we conducted a linear regression adjusted for age, sex, race/ethnicity, six-month time period, body mass index, education, and sun avoidance behaviors. We tested for effect modification by age, sex, ethnicity and time period of measurement using multiplicative interaction terms and a F test. Results: BP-3 was positively associated with self-reported frequency of sunscreen use across all ages, sexes, race/ethnicities, and time periods. Crude and multivariate adjusted models were all statistically significant. R-square was relatively low for all models, ranging from 0.15 to 0.43. Conclusions: Urinary BP-3 is positively associated with self-reported frequency of sunscreen use in the general US population, even in groups with overall low sunscreen use. These results suggest that self-report is a valid, although weak, way of assessing relative frequencies of sunscreen usage in a population-based study. - Highlights: • Urinary benzophenone-3 (BP-3) is a metabolite of a common sunscreen ingredient. • We modeled urinary BP-3 against self-reported sunscreen usage. • We observed a positive association between sunscreen use and urinary BP-3. • R{sup 2} was low, suggesting self-report is a valid but weak way to assess sunscreen use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

From roads to roofs: How urban and rural mobility influence building energy consumption

In this article, understanding the relationship between travel behavior and building energy use at an urban scale is crucial for developing effective energy management strategies. Mobility patterns significantly impact building occupancy, which in turn affects energy consumption. However, existing methods often focus on individual buildings, whereas geographical influences on energy usage are not adequately examined. This study addresses this gap by using transportation origin-destination (OD) data to estimate building occupancy and energy. The proposed method assigns OD trips from census block groups to the building level, incorporating building, travel survey, and census data to derive building occupancy profiles. This method was applied to urban and rural areas with 4062 buildings in 70 census block groups. We found that the OD-informed occupancy profile exhibits smoother energy consumption patterns compared with that of Department of Energy reference occupancy profiles. Our analysis reveals distinct building energy consumption patterns among groups with long and short commutes, emphasizing the effect of commute times and work schedules on residential energy usage. This framework is useful for practitioners in transportation agencies and utility companies, enabling the estimation of building energy based on mobility patterns. Overall, this study shows the potential of integrating transportation and building energy data to inform cross-sector energy management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Performance characterization of scientific workflows for the optimal use of Burst Buffers

Scientific discoveries are significantly rely on the analysis of large volumes of data from observations and simulations of complex phenomena. Scientists compose the complex analyses as workflows and execute them on large-scale HPC systems. The workflow structures are in contrast with monolithic single simulations that have often been the primary use case on HPC systems. At the same time, new storage paradigms such as Burst Buffers are becoming available on HPC platforms. In this paper, we analyze the performance characteristics of a Burst Buffer and two representative scientific workflows with the aim of optimizing the usage of a Burst Buffer, extending our previous analyses (Daley et al., 2016). Our key contributions are (a) developing a performance analysis methodology pertinent to Burst Buffers, (b) improving the use of a Burst Buffer in workflows with bandwidth-sensitive and metadata-sensitive I/O workloads, (c) highlighting the key data management challenges when incorporating a Burst Buffer in the studied scientific workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Stability study of aqueous foams under high-temperature and high-pressure conditions relevant to Enhanced Geothermal Systems (EGS)

In Enhanced Geothermal System (EGS) hydraulic fracturing is carried out by injecting cold water into deep Hot Dry Rocks (HDR) under carefully controlled conditions to create new or reopen existing fractures. Water-based fracturing fluids demonstrate some challenges including immense quantity of water usage, water sensitivity of the formations, water blocking, and lack of proppant carrying capacity and transportation. Thus, an alternative is to use foam-based fracturing fluid which offers potential advantage over conventional water-based fracturing fluid such as minimum water usage, reduced wellbore damage, high proppant carrying capacity, and less environmental damage. However, foams are complex mixture of gaseous phase and liquid phase which are thermodynamically unstable at downhole conditions, and their stability can decrease over time due to liquid drainage, bubble coarsening, and coalescence. This paper shows laboratory experiments executed to study foam stability at high temperature (200°C) and high pressure (6.9MPa) conditions which simulates the geothermal environment. Foam stability was characterized by half-life of foam, which is defined as the time taken by the foam to decreases by 50% of its original height due to drainage. In this paper, two types of gaseous phases, nitrogen (N 2 ) and carbon dioxide (CO 2 ) were investigated. Also, based on successful practice of foam-based fracturing fluid in oil and gas industries, four surfactants, including Alpha olefin sulfonate (AOS), Sodium dodecyl sulfonate (SDS), Tergitol™ (NP – 40), and Cetyltrimethylammonium chloride (CTAC) at optimum concentration of 1wt.% were tested for best stability performance. In addition, different stabilizing agents including guar gum, bentonite clay, crosslinker, silicon dioxide nanoparticles (SiO 2 ), graphene oxide (GO) were also studied. Experimental results showed that N 2 foams were more stable than CO 2 foams. It was observed that foam half-life decreased with the increase in temperature. Among all the surfactants, AOS foams showed the most promising thermal stability at high temperatures. Moreover, with the addition of stabilizing agents, foam's half-life was enhanced. Stabilizing agents such as crosslinker and GO dispersion showed the most stable foams with half-life recorded at 20min and 17min, respectively, at 200°C and 6.9MPa. Finally, pressure also showed a positive effect on foam stability; with increased pressure, foam half-life was increased. Based on the experimental data, analytical models for the effect of temperature and pressure were developed, considering foam degradation is a first-order kinetic reaction that linearly depends on the foam drainage mechanism. The effect of temperature on foam half-life was studied as an exponential decay model. In this model, foam half-life is a function of drainage rate constant (D A ) and activation energy (E a ) of the foam system. The effect of pressure on foam half-life was found to obey a power-law model where an increase in pressure showed an increase in foam half-life. Furthermore, a linear relation was studied for the effect of pressure on foam activation energy and drainage rate. Then the combined effects of temperature and pressure were studied, which yielded an analytical model to predict the foam stabilities in terms of half-life for different foam compositions. In conclusion, this research indicates that with an appropriate selection of surfactants and stabilizing agents, it is possible to obtain stable foams, which could replace conventional water fracturing fluid under EGS conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Impact of Using Audit Data to Improve the Evidence-Based Use of Single-Fraction Radiation Therapy for Bone Metastases in British Columbia

Purpose: To assess the impact of a population-based intervention to increase the consistency and use of single-fraction radiation therapy (SFRT) for bone metastases. Methods and Materials: In 2012, an audit of radiation therapy prescriptions for bone metastases in British Columbia identified significant interphysician and -center (26%-73%) variation in the use of SFRT. Anonymous physician-level and identifiable regional cancer center SFRT use data were presented to all radiation oncologists, together with published guidelines, meta-analyses, and recommendations from practice leaders. The use of SFRT for bone metastases from 2007 through 2011 was compared with use of SFRT in 2013, to assess the impact of the audit and educational intervention. Multilevel logistic regression was used to assess the relationship between the usage of SFRT and the timing of the radiation while controlling for potentially confounding variables. Physician and center were included as group effects to account for the clustered structure of the data. Results: A total of 16,898 courses of RT were delivered from 2007 through 2011, and 3200 courses were delivered in 2013. The rates of SFRT use in 2007, 2008, 2009, 2010, 2011, and 2013 were 50.5%, 50.9%, 48.3%, 48.5%, 48.0%, and 59.7%, respectively (P<.001). Use of SFRT increased in each of 5 regional centers: A: 26% to 32%; B: 36% to 56%; C: 39% to 57%; D: 49% to 56%; and E: 73% to 85.0%. Use of SFRT was more consistent; 3 of 5 centers used SFRT for 56% to 57% of bone metastases RT courses. The regression analysis showed strong evidence that the usage of SFRT increased after the 2012 intervention (odds ratio 2.27, 95% confidence interval 2.06-2.50, P<.0001). Conclusion: Assessed on a population basis, an audit-based intervention increased utilization of SFRT for bone metastases. The intervention reversed a trend to decreasing SFRT use, reduced costs, and improved patient convenience. This suggests that dissemination of programmatic quality indicators in oncology can lead to increased utilization of evidence-based practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Management Trends and Outcomes for Stage I to II Mantle Cell Lymphoma Using the National Cancer Data Base: Ascertaining the Ideal Treatment Paradigm

Purpose: Mantle cell lymphoma (MCL) is a rare, albeit aggressive subset of non-Hodgkin lymphoma, resulting in varied treatment approaches. Given the paucity of data defining the optimal management for early-stage MCL, we conducted an analysis using the National Cancer Data Base (NCDB) to identify practice patterns and outcomes. Methods and Materials: The NCDB was queried for patients with stage I to II MCL diagnosed from 1998 to 2012 receiving chemotherapy (CT) or radiation therapy (RT), or both (CT+RT). Univariate and multivariable analyses for factors associated with treatment selection were completed using logistic regression. Propensity scores with inverse probability treatment weighting (IPTW) were calculated based on the conditional probability of receiving CT+RT. The log-rank test and Cox proportional hazards modeling with IPTW adjustment were conducted for the survival analyses. Results: In total, 2539 patients were identified. The key characteristics were as follows: 69% were male, 71% were aged ≥60 years, 28% had extranodal involvement, and 51% had stage I disease. Of the 2539 patients, 70% underwent CT, 11% underwent RT, and 19% underwent CT+RT. The use of CT+RT decreased from 23.1% to 14.1% in 1998 to 2002 and 2010 to 2012 (P<.001). CT+RT usage was lower for patients with the following characteristics: age ≥60 years, female sex, stage II disease, and the presence of B symptoms. With a median follow-up period of 42.8 months, the unadjusted 3-year overall survival estimates for patients receiving CT, RT, or CT+RT were 67.8%, 72.4%, and 79.8%, respectively (P<.001). After correcting for indication bias through IPTW-adjusted modeling, CT+RT reduced the risk of overall mortality compared with monotherapy (hazard ratio 0.65, P=.029). Conclusions: Although uncommon, patients with stage I-II MCL can have favorable outcomes. Despite a continued decline in the usage of consolidative RT, combined modality therapy improves survival in this cohort compared with monotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

A novel design optimization framework to sustain remanufacturability

The ever-increasing global carbon emissions have urged the need for environmentally conscious/sustainable product design, for which the design for remanufacturing (DfRem) is one potential approach. DfRem targets at designing products that have multiple life cycles, thus significantly reducing raw material usage, energy consumption, and carbon emissions. In this paper, we develop a three-stage framework that consists of (1) systematic design space exploration and a multi-objective optimization formulation to minimize the likelihood of failure causes (such as fatigue and wear) and environmental footprint, (2) topology optimization to further reduce material usage without significantly affecting the load-carrying capability of the product, and (3) post-topology optimization design verification to ensure the proposed design satisfies all design constraints. The environmental impact can be assessed at varying comprehensiveness levels (e.g., design and manufacturing phase, use phase) and in terms of carbon or GHG emission, energy use, and waste generation. Because the novel design framework predominantly adjusted the geometry, we focused on mass-based change and energy savings due to sustained remanufacturability. The multi-objective optimization formulation in the first step results in a Pareto optimal set of possible design solutions that the designer can use for the second step. Finally, we demonstrate the utility of this framework through a case study of an engine cylinder head subjected to thermo-mechanical loads, where we find that about 5% of the product mass can be conserved with only about a 3% increase in surface area that has a fatigue life less than 10,000 cycles.

42 ENGINEERING↗
DOE OSTI2016

Conjunctive management of surface and groundwater resources under projected future climate change scenarios

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimized conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Dynamics of virtual water networks: Role of national socio-economic indicators across the world

Intensified water usage due to rapid industrialization is often dictated by economic policies based on monetary growth rather than sustainable use of environmental resources. In addition, interdependence within economic sectors further interweaves water usage through product transactions, which further makes it difficult to quantify the dynamics of hydro-economic systems at regional, national and global scale. In this study, we investigated the dynamics of domestic virtual water networks (VWN) of 189 countries based on concept of information theory by quantifying network metrics that describes VWN flow capacity, robustness, efficiency and flexibility. These networks represent virtual water interconnected through economic sectors within a specified country built based on environmentally extended multi region input output (EE-MRIO) approach. We further estimated trends associated with network metrics, as well as coupling intensity between metrics with respect to socio-economic indicators, such as, population, Gross Domestic Product (GDP) and Gross National Income (GNI). It was observed that capacity and flexibility of VWNs are strongly and positively correlated indicating that a high capacity VWN can be more flexible. Our results also indicate that, in general a higher percentage of developing countries (i.e. both least developing and developing nations) have exhibited increasing trends in capacity, robustness, efficiency and flexibility of VWN compared to developed nations. It was revealed that the dynamics of VWNs are positively coupled with socio-economic growth for few countries, which indicates the sustainable behavior of VWN with socio-economic growth. Our results argue that the information theory-based metrics by embedding water footprints can holistically capture sustainability aspect of the VWN dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A manufacturing process design for producing a membrane-based energy recovery ventilator with high aspect ratio support ribs

Heating, ventilation, and air conditioning systems represent nearly half of building energy usage in the United States. Recent building regulations requiring increased air turnover within buildings will result in even greater air conditioning usage. To alleviate these concerns, membrane-based heat-and-moisture exchangers known as energy recovery ventilators have been developed to reduce the energy expenditure of air conditioning systems by pre-conditioning incoming air through sensible and latent heat transfer with building air exhaust. Here in this work, we propose and validate a manufacturing process design for channel lamination based on surface mount adhesives capable of meeting the process requirements of a membrane-based ventilator. In particular, the device requires rib supports with height-to-width aspect ratios greater than one. The proposed manufacturing process design is capable of meeting this process requirement by stretching the adhesive after initial adhesive tacking. A manufacturing process flow diagram, a machine tool specification and a cost model are proposed for meeting process requirements. A set of design constraints are developed detailing the adhesive requirements necessary for meeting requirements. The cost model is validated by building a sub-scale mesochannel array demonstrating the ability to meet process requirements. Results show that additional work is needed to validate the curing step but that the process is capable of producing a mesochannel array with an acceptable level of variation.

42 ENGINEERING↗
DOE OSTI2022

Model predictive control of heating, ventilation, and air conditioning (HVAC) systems: A state-of-the-art review

Due to the fast advancement of communication and information technology, intelligent buildings have garnered great interest. These buildings can forecast weather, ambient temperature, and sun irradiation and can modify heating, ventilation, and air conditioning (HVAC) operations appropriately, based on current and previous data. This change is intended to reduce HVAC system energy usage while maintaining an appropriate degree of thermal comfort and indoor air quality. Since its inception, model predictive control (MPC) has been one of the prospective solutions for HVAC management systems to reduce both costs and energy usage. Additionally, MPC is becoming increasingly practical as the processing capacity of building automation systems increases and a large quantity of monitored building data becomes available. MPC also provides the potential to improve the energy efficiency of HVAC systems via its capacity to consider limitations, to predict disruptions, and to factor in multiple competing goals such as interior thermal comfort and building energy consumption. Although substantial research has been conducted on MPC in building HVAC systems, there is a shortage of critical reviews and a lack of a comprehensive framework that formulates and defines the applications. Here, this article provides a comprehensive state-of-the-art overview of MPC in HVAC systems. Detailed discussions of modeling approaches and optimization algorithms are included. Numerous design aspects such as prediction horizon, occupancy behavior, building type, and cost function, that impact MPC performance are discussed in detail. The technical characteristics, advantages, and disadvantages of various types of modeling software are discussed. The primary objective of this work is to highlight critical design characteristics for the MPC control scheme and to give improved suggestions for future research. Moreover, numerous prospective scenarios have been suggested that might provide future research direction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Uncovering I/O demands on HPC platforms: Peeking under the hood of Santos Dumont

High-Performance Computing (HPC) platforms are required to solve the most diverse large-scale scientific problems in various research areas, such as biology, chemistry, physics, and health sciences. Researchers use a multitude of scientific softwares, which have different requirements. These include input and output operations, which directly impact performance due to the existing difference in processing and data access speeds. Thus, supercomputers must efficiently handle mixed workload when storing data from the applications. Understanding the set of applications and their performance running in a supercomputer is paramount to understanding the storage system's usage, pinpointing possible bottlenecks, and guiding optimization techniques. This research proposes a methodology and visualization tool to evaluate a supercomputer's data storage infrastructure's performance, taking into account the diverse workload and demands of the system over a long period of operation. As a study case, we focus on the Santos Dumont supercomputer, identifying inefficient usage, problematic performance factors, and providing guidelines on how to tackle those issues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

A novel contrast agent with rare earth-doped up-conversion luminescence and Gd-DTPA magnetic resonance properties

The magnetic-luminescent multifunctional nanoparticles based on Gd-DTPA and NaYF{sub 4}:Yb, Er were successfully synthesized by the conjugation of activated DTPA and silica-coated/surface-aminolated NaYF{sub 4}:Yb, Er nanoparticles through EDC/NHS coupling chemistry. The as-prepared products were characterized by powder X-ray diffraction, transmission electron microscopy, dynamic light scattering, energy dispersive X-ray analysis, and fourier transform infrared spectrometry. The room-temperature upconversion luminescent spectra and T{sub 1}-weighted maps of the obtained nanoparticles were carried out by 980 nm NIR light excitation and a 3T MR imaging scanner, respectively. The results indicated that the as-synthesized multifunctional nanoparticles with small size, highly solubility in water, and both high MR relaxivities and upconversion luminescence may have potential usage for MR imaging in future. - Graphical abstract: We have synthesized magnetic-luminescent multifunctional nanoparticles based on Gd-DTPA and NaYF4:Yb, Er by the conjugation of activated DTPA and silica-coated/surface-aminolated NaYF4:Yb, Er nanoparticles through EDC/NHS coupling chemistry. Highlights: Black-Right-Pointing-Pointer A novel magnetic-luminescent multifunctional nanoparticles are synthesized. Black-Right-Pointing-Pointer The nanoparticles are highly efficient for luminescence and T{sub 1}-weighted MR imaging. Black-Right-Pointing-Pointer The nanoparticles are small in size and highly solubility in water. Black-Right-Pointing-Pointer The nanoparticles hold great potential usage for future biomedical engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Simplifying activations with linear approximations in neural networks

A key step in Neural Networks is activation. Among the different types of activation functions, sigmoid, tanh, and others involve the usage of exponents for calculation. From a hardware perspective, exponential implementation implies the usage of Taylor series or repeated methods involving many addition, multiplication, and division steps, and as a result are power-hungry and consume many clock cycles. We implement a piecewise linear approximation of the sigmoid function as a replacement for standard sigmoid activation libraries. This approach provides a practical alternative by leveraging piecewise segmentation, which simplifies hardware implementation and improves computational efficiency. In this paper, we detail piecewise functions that can be implemented using linear approximations and their implications for overall model accuracy and performance gain. Our results show that for the DenseNet, ResNet, and GoogLeNet architectures, the piecewise linear approximation of the sigmoid function provides faster execution times compared to the standard TensorFlow sigmoid implementation while maintaining comparable accuracy. Specifically, for MNIST with DenseNet, accuracy reaches 99.91% (Piecewise) vs. 99.97% (Base) with up to 1.31x speedup in execution time. For CIFAR-10 with DenseNet, accuracy improves to 98.97% (Piecewise) vs. 99.40% (Base) while achieving 1.24x faster execution. Similarly, for CIFAR-100 with DenseNet, the accuracy is 97.93% (Piecewise) vs. 98.39% (Base), with a 1.18x execution time reduction. These results confirm the proposed method’s capability to efficiently process large-scale datasets and computationally demanding tasks, offering a practical means to accelerate deep learning models, including LSTMs, without compromising accuracy.

Activation function↗