Energy Sciences Research Articles

Geoscience for energy transition

We are living in the midst of a great technological revolution in history—the energy transition from today's fossil fuel‐dominated civilization to low‐carbon economies and industries. Geoscientists will significantly contribute to energy science, policy and technologies by advancing our knowledge base of the complex interacting processes and substances in Earth's lithosphere, oceans and atmosphere. Mapping the flow of energy in various forms and intensities in Earth systems, exploration of energy resources and minerals and evaluating the environmental impacts of energy technologies from upstream to downstream will be increasingly embedded in geoscience education, research and workforce development. This article outlines major pathways of how geoscience will contribute to various components of the energy transition.

Phonon dispersion at long and short wavelength as seen by ultrasound and neutron spectroscopy

Lattice excitations are fundamental energy carriers responsible for thermal transport in every solid. Whereas ultrasound spectroscopy typically probes these excitations in the kHz to MHz “sound” regime corresponding to mm to μm wavelengths, inelastic scattering of neutrons or x-rays probe the THz regime and Å wavelength. We will discuss a few examples of materials with peculiar sound and phonon properties, such as chiral α-TeO;2 and the AgSbTe;2-PbTe (LAST) solid solution. Analysis of resonant ultrasound data of α-TeO;2 requires the use of code that supports chiral space groups, such a RUSCal; intriguingly sound is extremely anisotropic, and in some directions the speed of sound is highly frequency dependent in the 0–1 THz range. LAST exhibits nanoscale inhomogeneities where the speed of sound is different in the matrix and the nanoinclusions. Work supported by the US Department of Energy (DOE), Office of Basic Energy Science (BES), and by Laboratory Directed Research at Oak Ridge National Laboratory; this research used resources at the Spallation Neutron Source a facility supported by DOE, BES, Scientific User Facilities Division. J. Torres, A. Flores-Bettancourt, M. Manley, B. Winn, G. Yumnam, I. Sergeev, P. Bauer-Pereira and A. Jafari are gratefully acknowledged for their collaboration.

Communication on Climate Change in the Mediterranean by Non-State Actors: A Framing Analysis

How do non-state actors frame climate change in a region labelled as a climate hotspot? To answer this question, this article explores the climate communication strategies of non-state actors with various country origins. Adopting the quantitative content analysis method, it comparatively analyses differing frame utilizations (e.g. ecological/meteorological, policy, economic and energy interests, culture, science and technology, civil society) of non-state actors in their selected climate change/global warming-related reports (n=89) on the Mediterranean. The findings provide clues on the cosmopolitan framing of non-state actors on the regional level.

A 10-m national-scale map of ground-mounted photovoltaic power stations in China of 2020

We provide a remote sensing derived dataset for large-scale ground-mounted photovoltaic (PV) power stations in China of 2020, which has high spatial resolution of 10 meters. The dataset is based on the Google Earth Engine (GEE) cloud computing platform via random forest classifier and active learning strategy. Specifically, ground samples are carefully collected across China via both field survey and visual interpretation. Afterwards, spectral and texture features are calculated from publicly available Sentinel-2 imagery. Meanwhile, topographic features consisting of slope and aspect that are sensitive to PV locations are also included, aiming to construct a multi-dimensional and discriminative feature space. Finally, the trained random forest model is adopted to predict PV power stations of China parallelly on GEE. Technical validation has been carefully performed across China which achieved a satisfactory accuracy over 89%. Above all, as the first publicly released 10-m national-scale distribution dataset of China’s ground-mounted PV power stations, it can provide data references for relevant researchers in fields such as energy, land, remote sensing and environmental sciences.

Optimization Examples for Water Allocation, Energy, Carbon Emissions, and Costs

The field of Water Resources Management (WRM) is becoming increasingly interdisciplinary, realizing its direct connections with energy, food, and social and economic sciences, among others. Computationally, this leads to more complex models, wherein the achievement of multiple goals is sought. Optimization processes have found various applications in such complex WRM problems. This entry considers the main factors involved in modern WRM, and puts them in a single optimization problem, including water allocation from different sources to different uses and non-renewable and renewable energy supplies, with their associated carbon emissions and costs. The entry explores the problem mathematically by presenting different optimization approaches, such as linear, fuzzy, dynamic, goal, and non-linear programming models. Furthermore, codes for each model are provided in Python, an open-source language. This entry has an educational character, and the examples presented are easily reproducible, so this is expected to be a useful resource for students, modelers, researchers, and water managers.

Effective Communication of Energy Science and Technology

Although research, development, and deployment of advanced energy technologies are essential for the clean energy transition, communication about these technologies is equally important to their success. Energy is part of everyday life; therefore, changes in energy systems should be accepted by communities and industries. Yet details about energy generation, transmission, and environmental impacts are complex. The combination of commonality and complexity requires communications to use visualization, localization, narrative, and understandable terminology to reach a range of stakeholders. Collaboration between technology experts and communications professionals builds integrity and accessibility of energy information that enables community‐based solutions for energy.

Subnanometer Scale Mapping of Hydrogen Doping in Vanadium Dioxide.

Hydrogen donor doping of correlated electron systems such as vanadium dioxide (VO2) profoundly modifies the ground state properties. The electrical behavior of HxVO2 is strongly dependent on the hydrogen concentration; hence, atomic scale control of the doping process is necessary. It is however a nontrivial problem to quantitatively probe the hydrogen distribution in a solid matrix. As hydrogen transfers its sole electron to the material, the ionization mechanism is suppressed. In this study, a methodology mapping the doping distribution at subnanometer length scale is demonstrated across a HxVO2 thin film focusing on the oxygen-hydrogen bonds using electron energy loss spectroscopy (EELS) coupled with first-principles EELS calculations. The hydrogen distribution was revealed to be nonuniform along the growth direction and between different VO2 grains, calling for intricate hydrogenation mechanisms. Our study points to a powerful approach to quantitatively map dopant distribution in quantum materials relevant to energy and information sciences.

Editorial for Clean Energy Science and Technology (Volume 1 Issue 2)

In the era of industrial revolution, from powering factories to keeping our digital world humming, energy resources are the hidden engine behind modern economic activity, fueling production, transportation, and every click of a keyboard[1]. However, these commercial endeavors generate contaminants and toxins, which are extremely harmful for the environment and public health. To overcome these concerns, the utilization of clean energy is the main focus to enhance the economic growth and environmental preservation. During this time, many researchers and academicians are pivoted to study and research on clean energy technologies. Their successful research work helped us in publishing one commentary and six review articles, centered around the efficient use of resources, sustainable development, and environmental protection, in issue 2, volume 1 of this journal. It offers readers an overview of the most recent research trends in clean energy technology.

Analysis of Students' Critical Thinking Ability in the Class IV Science Learning Process of Elementary Schools Through Mini Turbine Wind Power Plant Learning Media

Wind turbines work by converting wind into electrical energy. The moving turbine is exposed to the kinetic energy of the wind, while simultaneously driving a generator that can produce electricity. Wind electric energy is a simple, economical and non-polluting energy system. Several factors influence the performance of a wind turbine, such as wind speed, number of angles, and angle shape. The amount of wind power that can produce several coil (N) revolutions also affects the performance of the turbine. If the wind used is large, the pressure or movement made by the turbine will also be greater, so that the number of rotations produced will also increase, thus producing large amounts of electrical energy. The aim of this research is to help students think critically about natural science material. Carrying out this research is expected to be able to find out the character of students in learning, how students think about the material presented, and to find out how teachers provide natural science learning by involving learning media as a tool to help understand the material. The research method developed is Research and Development (RnD). The research model we use is to show how the media works to help explain electrical energy science material.

Simulating image coaddition with the Nancy Grace Roman Space Telescope – I. Simulation methodology and general results

ABSTRACT The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near-infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based coaddition techniques such as imcom that combine multiple undersampled images to produce a single oversampled output mosaic with a desired ‘target’ point spread function (PSF). We present here an initial application of imcom to 0.64 square degrees of simulated Roman data, based on the Roman branch of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) simulation. We show that imcom runs successfully on simulated data that includes features such as plate scale distortions, chip gaps, detector defects, and cosmic ray masks. We simultaneously propagate grids of injected sources and simulated noise fields as well as the full simulation. We quantify the residual deviations of the PSF from the target (the ‘leakage’), as well as noise properties of the output images; we discuss how the overall tiling pattern as well as Moiré patterns appear in the final leakage and noise maps. We include appendices on interpolation algorithms and the interaction of undersampling with image processing operations that may be of broader applicability. The companion paper (‘Paper II’) explores the implications for weak lensing analyses.

An Innovative Tubular Thermoelectric Generator (TTEG) for Enhanced Waste Heat Recovery in Industrial and Automotive Applications

In response to the growing need for efficient energy conversion technologies, this paper introduces an innovative Tubular Thermoelectric Generator (TTEG), specifically designed for the high-efficiency conversion of waste heat into electrical energy. Unlike conventional flat-plate thermoelectric generators (FTEGs), the TTEG incorporates full-ring thermoelectric elements within a tubular layout, offering a novel approach to thermal energy recovery from fluid-based systems. This design significantly enhances the heat transfer capabilities, thereby improving the efficiency of energy conversion. Moreover, it is optimally tailored for integration into any cylindrical pipe to recapture and repurpose waste heat. Comprehensive simulations and analyses form the core of this study, where the performance of the TTEG is rigorously compared with traditional FTEGs. Under identical conditions of heat exposure, volume, and properties of thermoelectric materials, the TTEG demonstrates a 62.5% increase in output power compared to the TGM1-127-1.0-0.8 thermoelectric module (FTEG). These comparisons highlight the advantages of the tubular design in terms of energy conversion efficiency and practical applicability in various scenarios. The findings reveal that the TTEG not only outperforms its flat-plate counterparts but also presents a scalable and adaptable solution for waste heat recovery in a wide range of industrial and automotive applications. This research contributes to the field of energy science and technology by presenting a detailed experimental setup, complete with reproducible procedures and results. It opens new pathways for the development of more sustainable and efficient energy conversion systems, aligning with the goal of harnessing renewable and sustainable energy sources. The potential applications of this technology in enhancing energy efficiency and reducing environmental impact are vast, making it a significant step forward in the quest for clean and sustainable energy solutions.

Extension of nature's NIR-I chromophore into the NIR-II region.

The development of chromophores that absorb in the near-infrared (NIR) region beyond 1000 nm underpins numerous applications in medical and energy sciences, yet also presents substantial challenges to molecular design and chemical synthesis. Here, the core bacteriochlorin chromophore of nature's NIR absorbers, bacteriochlorophylls, has been adapted and tailored by annulation in an effort to achieve absorption in the NIR-II region. The resulting bacteriochlorin, Phen2,1-BC, contains two annulated naphthalene groups spanning meso,β-positions of the bacteriochlorin and the 1,2-positions of the naphthalene. Phen2,1-BC was prepared via a new synthetic route. Phen2,1-BC is an isomer of previously examined Phen-BC, which differs only in attachment via the 1,8-positions of the naphthalene. Despite identical π-systems, the two bacteriochlorins have distinct spectroscopic and photophysical features. Phen-BC has long-wavelength absorption maximum (912 nm), oscillator strength (1.0), and S1 excited-state lifetime (150 ps) much different than Phen2,1-BC (1292 nm, 0.23, and 0.4 ps, respectively). These two molecules and an analogue with intermediate characteristics bearing annulated phenyl rings have unexpected properties relative to those of non-annulated counterparts. Understanding the distinctions requires extending concepts beyond the four-orbital-model description of tetrapyrrole spectroscopic features. In particular, a reduction in symmetry resulting from annulation results in electronic mixing of x- and y-polarized transitions/states, as well as vibronic coupling that together reduce oscillator strength of the long-wavelength absorption manifold and shorten the S1 excited-state lifetime. Collectively, the results suggest a heuristic for the molecular design of tetrapyrrole chromophores for deep penetration into the relatively unutilized NIR-II region.

Understanding ion-transfer reactions in silver electrodissolution and electrodeposition from first-principles calculations and experiments.

The electrified aqueous/metal interface is critical in controlling the performance of energy conversion and storage devices, but an atomistic understanding of even basic interfacial electrochemical reactions challenges both experiment and computation. We report a combined simulation and experimental study of (reversible) ion-transfer reactions involved in anodic Ag corrosion/deposition, a model system for interfacial electrochemical processes generating or consuming ions. With the explicit modeling of the electrode potential and a hybrid implicit-explicit solvation model, the density functional theory calculations produce free energy curves predicting thermodynamics, kinetics, partial charge profiles, and reaction trajectories. The calculated (equilibrium) free energy barriers (0.2 eV), and their asymmetries, agree with experimental activation energies (0.4 eV) and transfer coefficients, which were extracted from temperature-dependent voltage-step experiments on Au-supported, Ag-nanocluster substrates. The use of Ag nanoclusters eliminates the convolution of the kinetics of Ag+(aq.) generation and transfer with those of nucleation or etch-pit formation. The results indicate that the barrier is controlled by the bias-dependent competition between partial solvation of the incipient ion, metal-metal bonding, and electrostatic stabilization by image charge, with the latter two factors weakened by stronger positive biases. We also report simulations of the bias-dependence of defect generation relevant to nucleating corrosion by removing an atom from a perfect Ag(100) surface, which is predicted to occur via a vacancy-adatom intermediate. Together, these experiments and calculations provide the first validated, accurate, molecular model of the central steps that govern the rates of important dissolution/deposition reactions broadly relevant across the energy sciences.

Constructing covalent organic frameworks with dense thiophene S sites for effective iodine capture.

Developing versatile sorption materials for radionuclides (e.g. iodine) capture has been a critical goal in nuclear energy and environmental science. At the same time, covalent organic frameworks (COFs), on account of their high porosity and functional scaffolds, have opened up a new way to develop adsorbents in recent years. Herein, two kinds of COF materials containing thiophene (TAPT-COF and TAB-COF), as iodine sorbents, are designed and synthesized by Schiff base reaction. Among them, TAB-COF has a higher surface area (TAPT-COF: 1141 m2 g-1, TAB-COF: 1378 m2 g-1), which is helpful for the physical iodine adsorption. More importantly, the COF backbone is rich in both N and S sites, which is advantageous to the chemical adsorption of iodine. These two features make the two COFs ideal iodine sorption materials. For example, TAB-COF has an excellent gaseous iodine adsorption capacity (2.81 g g-1) and is one of the most efficient iodine adsorption materials. Meanwhile, TAB-COF has an excellent adsorption effect on iodine in the cyclohexane system, which can reach 200 mg g-1. In addition, the DFT calculations proved that both imine N and thiophene S serve as active sites during the iodine adsorption. TAB-COF exposes more active sites on the premise of having a higher surface area, thereby leading to a higher iodine adsorption capacity. The results here indicate improved sorption efficacy by introducing thiophene in COFs for sorption applications in general and especially pave the way for developing stable and effective COF sorbents for iodine capture from various environments.

Nano Informatics: The Bridge between Nanotechnology and Data Science

Nanotechnology, the manipulation of matter at the nanoscale, has emerged as a transformative field with profound implications for various industries, including medicine, electronics, energy, and materials science. The vast amount of data generated in nanotechnology research presents both an opportunity and a challenge. Nano informatics, a multidisciplinary field at the intersection of nanotechnology and data science, has evolved to harness the potential of data-driven insights in nanoscience and nanotechnology applications. The concept of nano informatics as a critical bridge between nanotechnology and data science. It highlights the significance of data collection, analysis, and interpretation in nanoscale research, emphasizing the need for advanced data-driven approaches to extract meaningful knowledge. Nano informatics not only plays a crucial role in managing the immense volume of data produced in nanotechnology experiments but also contributes to accelerating scientific discovery and innovation.

GENERATION OF ELECTRICITY FROM WASTE MATERIALS USING Node MCU AND IOT

Nowadays, electricity is considered one of the major commodities in our lives. Due to the increase in demand for electricity, the supply also needs to be increased. There are many effective methods like hydroelectricity, solar power, nuclear power etc, one such method is the generation of electricity from waste materials which is eco-friendly and cost-effective, about 75% of waste in India is reduced by waste-to-energy conversion plants which decrease the number of pollutants like CO, SO2 , NO2 to a huge number. With India's substantial population and the corresponding waste generation, implementing such solutions can significantly alleviate environmental concerns while meeting energy demands. To ensure effectiveness and sustainability, it's crucial to address any drawbacks associated with waste-toenergy conversion. This might involve optimizing technology to maximize energy output while minimizing emissions, ensuring proper waste management practices to handle various types of waste safely, and conducting thorough environmental assessments to mitigate any potential negative impacts. Collaborating with experts in renewable energy, waste management, and environmental science can provide valuable insights and guidance for our project. Additionally, engaging with local communities and stakeholders can help garner support and ensure the project aligns with their needs and concerns. Overall, we focus on reducing pollutants and promoting renewable energy production through innovative waste-to-energy solutions is commendable and holds great potential for a sustainable future.

The Rubin Observatory’s Legacy Survey of Space and Time DP0.2 processing campaign at CC-IN2P3

The Vera C. Rubin Observatory, currently in construction in Chile, will start performing the Legacy Survey of Space and Time (LSST) in 2025 for 10 years. Its 8.4-meter telescope will survey the southern sky in less than 4 nights in six optical bands, and repeatedly generate about 2 000 exposures per night, corresponding to a data volume of about 20 TiB every night. Three data facilities are preparing to contribute to the production of the annual data releases: the US Data Facility will process 35% of the raw data, the UK data facility will process 25% of the raw data and the French data facility, operated by CC-IN2P3, will locally process the remaining 40% of the raw data.In the context of the Data Preview 0.2 (DP0.2), the Data Release Production pipelines have been executed on the DC-2 simulated dataset (generated by the Dark Energy Science Collaboration, DESC). This dataset includes 20 000 simulated exposures, representing 300 square degrees of Rubin images with a typical depth of 5 years.DP0.2 ran at the Interim Data Facility (based on Google cloud), and the full exercise was independently replicated at CC-IN2P3. During this exercise, 3 PiB of data and more than 200 million files were produced. In this contribution we will present a detailed description of the system that we set up to perform this processing campaign using CC-IN2P3’s computing and storage infrastructure. Several topics will be addressed: workflow generation and execution, batch job submission, memory and I/O requirements, etc. We will focus on the issues that arose during this campaign and how we addressed them and will present some perspectives after this exercise.

ИССЛЕДОВАНИЕ СЛОЖНОСТИ ИЗМЕНЕНИЙ В ЭНЕРГЕТИЧЕСКИХ ТЕХНОЛОГИЯХ

Disruptive technologies will bring about revolutionary changes in the energy sector. Energy is linked to national security, overall economic development, and the lives and well-being of people. The rapid development of energy science and technology affects all aspects of human society, and disruptive energy technologies (disruptive technologies), born from the cross-integration of many fields and disciplines, play a particularly prominent role. They have enormous economic potential and have a profound impact on future industrial development, business models and types of work, as well as lifestyles and even national competitiveness.

Impact of blending on weak lensing measurements with the Vera C. Rubin Observatory

Upcoming deep optical surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will scan the sky to unprecedented depths and detect billions of galaxies. This amount of detections will however cause the apparent superposition of galaxies on the images, called blending, and generate a new systematic error due to the confusion of sources. As consequences, the measurements of individual galaxies properties such as their redshifts or shapes will be impacted, and some galaxies will not be detected. However, galaxy shapes are key quantities, used to estimate masses of large scale structures, such as galaxy clusters, through weak gravitational lensing. This work presents a new catalog matching algorithm, called friendly, for the detection and characterization of blends in simulated LSST data for the Dark Energy Science Collaboration (DESC) Data Challenge 2. By identifying a specific type of blends, we show that removing them from the data may partially correct the amplitude of the excess surface mass density ΔΣ weak lensing profile that could be biased low by around 20% due to blending. This would result in impacting clusters weak lensing mass estimate and cosmology.

Thinking on the Education Reform of Experiment Design and Analysis Course for New Energy Science and Engineering Major

Thinking on the Education Reform of Experiment Design and Analysis Course for New Energy Science and Engineering Major