scispace - formally typeset
Search or ask a question

Showing papers by "United States Department of Energy published in 2022"


Journal ArticleDOI
TL;DR: In this article, a multi-scale computational fluid dynamics (CFD) simulation bridge the gap between particle and reactor scales in the modeling of biomass pyrolysis is presented.

31 citations


Journal ArticleDOI
01 Jan 2022-Carbon
TL;DR: In this article, a neural-network potential (NNP) for carbon is generated to simulate the structural properties of various carbon structures using a database consisting of crystalline and liquid structures obtained by the first-principles density functional theory (DFT).

15 citations


Journal ArticleDOI
TL;DR: The development and validation of the Superquadric Discrete Element Method (SuperDEM) for non-spherical particle simulation using a superquadric particle method in open-source CFD suite MFiX is presented and it is demonstrated that the SuperDEM solver has great potential for industrial-scale systems simulation.

13 citations


Journal ArticleDOI
15 Jan 2022-Energy
TL;DR: In this paper, a novel structured PVT (photovoltaic-thermal) module was proposed, manufactured, and adopted to form a solar assisted PVT heat pump system to realize high-efficiency co-generation in building sectors.

13 citations


Journal ArticleDOI
15 Jan 2022-Energy
TL;DR: The results show that scenario 1 overestimates electricity consumption between 2 and 18 times, contrasted with a difference of 1–7% in scenarios2 and 3, leading to saving potentials in scenario 1 between 1.2 and 33.4 times higher than for scenarios 2 and 3.

9 citations


Journal ArticleDOI
17 Jan 2022-Energies
TL;DR: A review of the current challenges associated with the energy-efficient design, recovery, recycling, and separation of valuable metals employing ionic liquids is presented in this paper , where the authors focus on the challenges of sustainable design, efficiency, and environmental impacts.
Abstract: Population growth has led to an increased demand for raw minerals and energy resources; however, their supply cannot easily be provided in the same proportions. Modern technologies contain materials that are becoming more finely intermixed because of the broadening palette of elements used, and this outcome creates certain limitations for recycling. The recovery and separation of individual elements, critical materials and valuable metals from complex systems requires complex energy-consuming solutions with many hazardous chemicals used. Significant pressure is brought to bear on the improvement of separation and recycling approaches by the need to balance sustainability, efficiency, and environmental impacts. Due to the increase in environmental consciousness in chemical research and industry, the challenge for a sustainable environment calls for clean procedures that avoid the use of harmful organic solvents. Ionic liquids, also known as molten salts and future solvents, are endowed with unique features that have already had a promising impact on cutting-edge science and technologies. This review aims to address the current challenges associated with the energy-efficient design, recovery, recycling, and separation of valuable metals employing ionic liquids.

7 citations


Journal ArticleDOI
TL;DR: In this article, the exchange interactions between Ho-Dy and Ho-Ho were set as free parameters and adjusted to match the experimental results, and the heat capacity of polycrystalline materials in non-zero magnetic fields was satisfactory reproduced by using the average of multiple magnetic field directions with respect to the crystallographic coordinate system.

7 citations


Journal ArticleDOI
TL;DR: In this paper , a de novo peptide sequencing approach was proposed to identify the sample composition directly from metaproteomic data, and a deep learning model was used to predict the peptide sequences from mass spectrometry data and trained on 5 million peptide-spectrum matches from 55 phylogenetically diverse bacteria.
Abstract: Metaproteomics has been increasingly utilized for high-throughput characterization of proteins in complex environments and has been demonstrated to provide insights into microbial composition and functional roles. However, significant challenges remain in metaproteomic data analysis, including creation of a sample-specific protein sequence database. A well-matched database is a requirement for successful metaproteomics analysis, and the accuracy and sensitivity of PSM identification algorithms suffer when the database is incomplete or contains extraneous sequences. When matched DNA sequencing data of the sample is unavailable or incomplete, creating the proteome database that accurately represents the organisms in the sample is a challenge. Here, we leverage a de novo peptide sequencing approach to identify the sample composition directly from metaproteomic data. First, we created a deep learning model, Kaiko, to predict the peptide sequences from mass spectrometry data and trained it on 5 million peptide–spectrum matches from 55 phylogenetically diverse bacteria. After training, Kaiko successfully identified organisms from soil isolates and synthetic communities directly from proteomics data. Finally, we created a pipeline for metaproteome database generation using Kaiko. We tested the pipeline on native soils collected in Kansas, showing that the de novo sequencing model can be employed as an alternative and complementary method to construct the sample-specific protein database instead of relying on (un)matched metagenomes. Our pipeline identified all highly abundant taxa from 16S rRNA sequencing of the soil samples and uncovered several additional species which were strongly represented only in proteomic data.

5 citations


Journal ArticleDOI
TL;DR: In this article, the authors proposed an Extended Multi-regional Input-Output model (EMRIO) that incorporates import dependence and governance along the value chain of alternative energy investments in Mexico.

5 citations


Journal ArticleDOI
TL;DR: In this paper, a general, systematic thermodynamic description of non-stoichiometric compounds is proposed by introducing a set of order parameters describing the extent of these internal processes, and an overall chemical composition is then obtained by minimizing the chemical potential of a compound with respect to these order parameters.

4 citations


Journal ArticleDOI
TL;DR: In this paper, the authors demonstrated a state-of-the-art approach predicting AGC loss of Zanzibar City Region under multiple alternative urban planning scenarios between 2013 and 2030.

Journal ArticleDOI
TL;DR: In this paper, the effects of H2S on the surface chemical composition and structure of the resulting catalysts were systematically studied, and the results showed isolated and well-dispersed Sn oxide sites of the deposited catalyst with nanoparticles observed only at relatively high coverages of 10% Sn at a coverage ranging from 0.48 to 2.8 Sn atoms.

Journal ArticleDOI
TL;DR: In this paper, a series of In-containing samples derived from the base Gd5Si1.2Ge2.8 stoichiometry were prepared to investigate the effect of Indium additions on the crystal structure, micro-structure, magnetic and magnetocaloric properties.

Journal ArticleDOI
TL;DR: In this article, the synthesis of a bimetallic-semi-aromatic polyester hybrid nanocomposite was reported, which was physicochemically characterized using FTIR analysis.

Journal ArticleDOI
TL;DR: In this article, the soft-sphere discrete element method was used to investigate the n-body instability with the soft sphere discrete elements method and the divergence of nearby trajectories was quantified by the dynamical memory time.

Journal ArticleDOI
TL;DR: The Stochastic Energy Deployment System (SESDS) as discussed by the authors was developed by the U.S. Department of Energy to support and improve public energy research and development decision-making.

Journal ArticleDOI
TL;DR: In this paper, a multi-modal approach combining synchrotron-based diffraction, and Raman spectroscopy with nano-scale electron microscopy techniques for investigating oxidation of Inconel 600 (A600) in steam and air environments at 1200°C for 2h.

Journal ArticleDOI
TL;DR: Zhang et al. as discussed by the authors developed a deep neural network potential of Zr-Rh system by using machine learning, which breaks the dilemma between the accuracy and efficiency in molecular dynamics simulations, and greatly improves the simulation scale in both space and time.
Abstract: Zr-Rh metallic glass has enabled its many applications in vehicle parts, sports equipment and so on due to its outstanding performance in mechanical property, but the knowledge of the microstructure determining the superb mechanical property remains yet insufficient. Here, we develop a deep neural network potential of Zr-Rh system by using machine learning, which breaks the dilemma between the accuracy and efficiency in molecular dynamics simulations, and greatly improves the simulation scale in both space and time. The results show that the structural features obtained from the neural network method are in good agreement with the cases inab initiomolecular dynamics simulations. Furthermore, we build a large model of 5400 atoms to explore the influences of simulated size and cooling rate on the melt-quenching process of Zr77Rh23. Our study lays a foundation for exploring the complex structures in amorphous Zr77Rh23, which is of great significance for the design and practical application.

DissertationDOI
30 Jul 2022
TL;DR: In this article , the authors explore how speculative architecture can challenge architecture's normative notions of space and temporality and simultaneously engender a multiplicity of temporal conditions by "sculpting in time".
Abstract: <p><b>In his 1979 film Stalker, Russian filmmaker Andrei Tarkovsky challenges normative notions of space and temporality. He refers to this as “sculpting in time”, arguing that a filmmaker—like a sculptor—redacts, excavates and curates material to reveal a final product. In relation to architecture, time is typically considered as the linear trajectory of continued existence, and temporality is the perception of experienced time by an individual. Tarkovsky, however, proposes that ‘polyscreen’ cinema - showing multiple perspectives of the same scene simultaneously on several screens - provides a filmic opportunity for experiencing multiple temporal realities all at once.</b></p> <p>The way we look at architecture is typically through a single temporal and spatial lens, which by default masks the multiplicity of temporal conditions that an architecture may represent and a visitor to architecture may experience.</p> <p>This thesis examines how speculative architecture can challenge architecture’s normative notions of space and temporality and simultaneously engender a multiplicity of temporal conditions. Using Tarkovsky’s film Stalker as a generative framework for an allegorical architectural proposition, the principle aim of this design-led research investigation is to investigate ways in which architecture can challenge normative notions of space and temporality by “sculpting in time”. Building upon and translating Tarkovsky’s filmic methods to architectural experiment, the principal research objectives are 1) to explore how excavation can redefine place identity through spatial and temporal relationships; 2) to explore how redaction can simultaneously establish multiple spatial and temporal conditions; and 3) to explore how curation can be used to re-present the allegorical implications of multiple spatial and temporal conditions.</p>

Book ChapterDOI
02 Mar 2022
TL;DR: In this paper , the authors provide an overview of characteristics, treatment, and beneficial reuse of produced water plus some policy and regulatory considerations and stakeholder viewpoints and provide a topic of interest to various stakeholders in the over 30 oil and gas producing states in the USA.
Abstract: Oil and gas deposits are generally colocated with water, which is coproduced with oil and gas during production. Produced water does not have a market as do oil and gas, so it is considered a waste. The cost of its disposal is very low compared to the potential cost of treating the produced water for reuse. The initial character of produced water will include those elements dissolved by the water during the centuries that it lay buried in the unique geologic setting. It will also include any chemicals added during oil and gas exploration and production operations plus any nascent bacteria in the original geologic setting. Also affecting the character of the produced water are any bones, plant residues, shells, and other materials that were deposited and buried in these geologic deposits. Treatment technologies that can change the character of the produced water depend on the initial produced water constituent profile and the profile needed for reuse and cost. Potential areas of reuse for treated produced water include oilfield, agriculture, and manufacturing. However, reuse of produced water is primarily associated with oilfield reuse. This is because there are few policies and regulations in place or being put in place for the use of treated produced water outside the oilfield. This is a topic of interest to various stakeholders in the over 30 oil- and gas-producing states in the USA. This chapter provides an overview of characteristics, treatment, and beneficial reuse of produced water plus some policy and regulatory considerations and stakeholder viewpoints.


Book ChapterDOI
01 Jan 2022
TL;DR: In this article, the basic properties of gas/solid and gas/liquid two-phase flows are examined, including fluidization concepts, flow regimes, and Geldart particle classifications.
Abstract: The basic properties of gas/solid and gas/liquid two-phase flows are examined. In the gas/solid flow section, fluidization concepts, flow regimes, and Geldart particle classifications are discussed. In the gas/liquid flow section, an overview is provided and fundamental relations of gas/liquid two-phase flows and some differences between gas/liquid flows and single-phase flow are explained. Furthermore, classical gas/liquid flow regimes maps and co-current gas/liquid flow patterns are discussed.

Journal ArticleDOI
TL;DR: In this paper , a semi-empirical procedure for estimating steady-state, groundwater inflow in shallow rock tunnels is presented and discussed, and two case study analyses are presented.
Abstract: The construction of tunnels in rock terrain has increased in importance around the world as the need for new transportation routes and water and wastewater conveyances has grown. Large cities and nearby suburbs have limited space for extensive, above-ground thoroughfares; therefore, underground systems may be the only viable means for developing new infrastructure. Excessive groundwater inflow into rock tunnels under construction can injury personnel and terminate the construction of the tunnel project. Therefore, it is important to accurately estimate groundwater inflow into rock tunnels. A semi-empirical procedure for estimating steady-state, groundwater inflow in shallow rock tunnels is presented and discussed in this paper. In addition, this paper presents two case study analyses which include the Elizabethtown tunnel in New Jersey and the Toledo tunnel in Ohio. Packer test (i.e., pressure test) data was analyzed for both case studies utilizing this semi-empirical procedure. This paper reviews the basic theory behind the procedure and validates the procedure through case study analyses. It also describes previous proposed modifications and clarifies the need for any such modifications. In general, good groundwater inflow estimates were derived for shallow rock tunnels utilizing this semi-empirical procedure. This research will benefit large and small municipalities (e.g., owners of major infrastructure tunnels projects) who need to install underground conveyances for water supply lines, sewer lines, railway, and roadways. By knowing the amount of water that might flow into the rock tunnel during its construction, the owners will save money, but more importantly lives if groundwater inflow are estimated accurately.