With the widespread use of semi-conductors in microelectronics and optoelectronics, it is hard to imagine that the initial excitement was due to their promise not in electronics, but in ...refrigeration. The discovery in the 1950s that semiconductors can act as efficient heat pumps led to premature expectations of environmentally benign solid-state home refrigerators containing no moving parts. Majumdar discusses further the thermoelectricity in semiconductor nanostructures.
Transmembrane proteins often contain nanoscale channels through which ions and molecules can pass either passively (by diffusion) or actively (by means of forced transport). These proteins play ...important roles in selective mass transport and electrical signalling in many biological processes. Fluidic nanochannels that are 1-2 nm in diameter act as functional mimics of protein channels, and have been used to explore the transport of ions and molecules in confined liquids. Here we report ion transport in 2-nm-deep nanochannels fabricated by standard semiconductor manufacturing processes. Ion transport in these nanochannels is dominated by surface charge until the ion concentration exceeds 100 mM. At low concentrations, proton mobility increases by a factor of four over the bulk value, possibly due to overlapping of the hydrogen-bonding network of the two hydration layers adjacent to the hydrophilic surfaces. The mobility of K+/Na+ ions also increases as the bulk concentration decreases, although the reasons for this are not completely understood.
We developed DeepSolar, a deep learning framework analyzing satellite imagery to identify the GPS locations and sizes of solar photovoltaic panels. Leveraging its high accuracy and scalability, we ...constructed a comprehensive high-fidelity solar deployment database for the contiguous US. We demonstrated its value by discovering that residential solar deployment density peaks at a population density of 1,000 capita/mile2, increases with annual household income asymptoting at ∼$150k, and has an inverse correlation with the Gini index representing income inequality. We uncovered a solar radiation threshold (4.5 kWh/m2/day) above which the solar deployment is “triggered.” Furthermore, we built an accurate machine learning-based predictive model to estimate the solar deployment density at the census tract level. We offer the DeepSolar database as a publicly available resource for researchers, utilities, solar developers, and policymakers to further uncover solar deployment patterns, build comprehensive economic and behavioral models, and ultimately support the adoption and management of solar electricity.
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•An accurate deep learning model for detecting solar panel on satellite imagery•Built a nearly complete solar installation database for the contiguous US•Identified key socioeconomic factors correlating with solar deployment density•A predictive model to estimate solar deployment density at census tract level
We built a nearly complete solar installation database for the contiguous US utilizing a novel deep learning model applied to satellite imagery. The data are published as the first publicly available, high-fidelity solar installation database in the contiguous US. We plan to update it annually and add other countries and regions of the world. We demonstrated the value of this database by identifying key environmental and socioeconomic factors correlated with solar deployment. We also developed high-accuracy machine learning models to predict solar deployment density utilizing these factors as input. We hope the data produced by DeepSolar can aid researchers, policymakers, and the industry in gaining a better understanding of solar adoption and its impacts.
We developed an accurate deep learning framework to automatically localize solar photovoltaic panels from satellite imagery and estimate their sizes. We used it to construct a comprehensive and publicly available solar installation database of the contiguous US. We demonstrated its value by identifying key environmental and socioeconomic factors correlating with solar deployment, such as income and education. We also found that the solar deployment density can be accurately estimated at the microscopic level with these factors using a novel predictive model.
Although it has been qualitatively demonstrated that surface roughness can reduce the thermal conductivity of crystalline Si nanowires (SiNWs), the underlying reasons remain unknown and warrant ...quantitative studies and analysis. In this work, vapor–liquid–solid (VLS) grown SiNWs were controllably roughened and then thoroughly characterized with transmission electron microscopy to obtain detailed surface profiles. Once the roughness information (root-mean-square, σ, correlation length, L, and power spectra) was extracted from the surface profile of a specific SiNW, the thermal conductivity of the same SiNW was measured. The thermal conductivity correlated well with the power spectra of surface roughness, which varies as a power law in the 1–100 nm length scale range. These results suggest a new realm of phonon scattering from rough interfaces, which restricts phonon transport below the Casimir limit. Insights gained from this study can help develop a more concrete theoretical understanding of phonon–surface roughness interactions as well as aid the design of next generation thermoelectric devices.
Access to affordable and reliable energy has been a cornerstone of the world’s increasing prosperity and economic growth since the beginning of the Industrial Revolution. Our use of energy in the ...21st century must also be sustainable. This article provides a techno-economic snapshot of the current energy landscape and identifies several research and development opportunities and challenges, especially where they relate to materials science and engineering, to create the foundation for this new industrial revolution.
Abstract
Detailed and location-aware distribution grid information is a prerequisite for various power system applications such as renewable energy integration, wildfire risk assessment, and ...infrastructure planning. However, a generalizable and scalable approach to obtain such information is still lacking. In this work, we develop a machine-learning-based framework to map both overhead and underground distribution grids using widely-available multi-modal data including street view images, road networks, and building maps. Benchmarked against the utility-owned distribution grid map in California, our framework achieves > 80% precision and recall on average in the geospatial mapping of grids. The framework developed with the California data can be transferred to Sub-Saharan Africa and maintain the same level of precision without fine-tuning, demonstrating its generalizability. Furthermore, our framework achieves a R
2
of 0.63 in measuring the fraction of underground power lines at the aggregate level for estimating grid exposure to wildfires. We offer the framework as an open tool for mapping and analyzing distribution grids solely based on publicly-accessible data to support the construction and maintenance of reliable and clean energy systems around the world.
The field of thermoelectrics has progressed enormously and is now growing steadily because of recently demonstrated advances and strong global demand for cost‐effective, pollution‐free forms of ...energy conversion. Rapid growth and exciting innovative breakthroughs in the field over the last 10–15 years have occurred in large part due to a new fundamental focus on nanostructured materials. As a result of the greatly increased research activity in this field, a substantial amount of new data—especially related to materials—have been generated. Although this has led to stronger insight and understanding of thermoelectric principles, it has also resulted in misconceptions and misunderstanding about some fundamental issues. This article sets out to summarize and clarify the current understanding in this field; explain the underpinnings of breakthroughs reported in the past decade; and provide a critical review of various concepts and experimental results related to nanostructured thermoelectrics. We believe recent achievements in the field augur great possibilities for thermoelectric power generation and cooling, and discuss future paths forward that build on these exciting nanostructuring concepts.
Rapid growth in the thermoelectrics field has occurred over the past 15 years due to a new fundamental focus on nanostructured materials. While great advances have been made, there is still some confusion about the exact role that nanostructuring has played in affecting electrical and thermal properties. This review seeks to summarize and critically review achievements of nanostructured thermoelectrics, and discuss paths forward for further breakthroughs that will enable widespread commercial adoption of these materials.
We demonstrate rectification of ionic transport in a nanofluidic diode fabricated by introducing a surface charge discontinuity in a nanofluidic channel. Device current−voltage (I−V) characteristics ...agree qualitatively with a one-dimensional model at moderate to high ionic concentrations. This study illustrates ionic flow control using surface charge patterning in nanofluidic channels under high bias voltages.
Not all nanopores are created equal. By definition, nanopores have characteristic diameters or conduit widths between ∼1 and 100 nm. However, the narrowest of such pores, perhaps best called Single ...Digit Nanopores (SDNs) and defined as those with regular diameters less than 10 nm, have only recently been accessible experimentally for precision transport measurements. This Review summarizes recent experiments on pores in this size range that yield surprising results, pointing toward extraordinary transport efficiencies and selectivities for SDN systems. These studies have identified critical gaps in our understanding of nanoscale hydrodynamics, molecular sieving, fluidic structure, and thermodynamics. These knowledge gaps are, in turn, an opportunity to discover and understand fundamentally new mechanisms of molecular and ionic transport at the nanometer scale that may inspire a host of new technologies, from novel membranes for separations and water purification to new gas-permeable materials and energy storage devices. Here we highlight seven critical knowledge gaps in the study of SDNs and identify the need for new approaches to address these topics.
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