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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of an Enhanced Radiation Physics Toolset for Modeling Spectral and Imaging Signatures in the Warm Dense Matter Experiments

Radiative and atomic processes in plasmas play a critical role in a wide variety of high energy density laboratory plasma (HEDLP) experiments. The emission, absorption, and transport of radiation can strongly affect the overall energetics and evolution of such plasmas. In addition, radiation-based diagnostics – including imaging, spectroscopy, and absolute flux measurements – are widely used to determine key features of HEDLPs. To advance our understanding of HEDLP science, it is vital to have high-fidelity computational physics tools that have well-tested radiation physics modeling, and that are readily accessible to researchers in the HEDLP community. Simulations play an extremely important role for planning and designing the experiments, as well as for post-experiment data analysis. Prism Computational Sciences develops software that is used by National Laboratories and universities (including five members of LaserNetUS network). Prominent examples of such research efforts include z-pinch and short-pulse laser experiments designed to study the basic physics of photoionized plasmas and photoionization fronts, as well as their application to astrophysical plasmas. The main effort was dedicated to the development of non-equilibrium equation-of-state (EOS) models within the HELIOS-CR code, a hydrodynamics code with inline collisional-radiative atomic kinetics. Gas cell experiments on Z and Omega demonstrated the importance of non-equilibrium effects on atomic kinetics in photoionized plasmas. Recent proof-of-principle experiments on Omega EP confirmed the advantages of using a short-pulse laser to create an intense radiation drive, leading to additional experiments being proposed. Photoionization front experiments at LLE also emphasizes the importance of radiation and atomic physics. In both studies, HELIOS-CR simulations played a crucial role in computing non-equilibrium opacities and ionization distributions. A newly developed non-LTE EOS model will help addressing possible non-equilibrium effects, on for example specific heat, and their influence in plasma evolution. Prism also implemented support for open-source atomic data generated by the Flexible Atomic Code. This allows researchers to generate custom atomic tables and use them within the complex framework of simulation tools developed by Prism. The ability to use open-source atomic data would be extremely valuable for hydrodynamics and spectroscopic simulations that include high-Z materials, e.g., picosecond x-ray pulse generation experiments. Support for new atomic structures was fully implemented, and the data can be used by all simulation tools developed at Prism: radiation-hydrodynamics, imaging and spectroscopy, EOS and opacity. The development resulted in a significant fidelity enhancement to the simulations tools developed by Prism that are currently used in other cutting-edge experiments including: opacity measurement experiments performed to both understand the basic radiative and atomic properties of plasmas as well as provide data for more accurately modeling the internal structure of the Sun and other stars, high-intensity short-pulse laser experiments performed to develop short-wavelength light sources for use as backlighters and to investigate fast ignition concepts for inertial fusion energy; capsule implosion experiments designed to develop inertial fusion as an energy source, etc.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Classical optimization with imaginary-time block encoding on quantum computers: The MaxCut problem

Optimization problems in finance, physics, and computer science are typically very hard to tackle in classical computing; quantum computing could help speed up computations and provide efficient methods for tackling large problems. Typically, to treat a problem with a quantum computer, the optimal solution is cast as the ground state of a diagonal Hamiltonian. Here, we develop a method, called imaginary-time evolution block encoding (ITE-BE), based on a recent imaginary-time algorithm, which requires no variational parameter optimization, as all parameters can be derived analytically from the target Hamiltonian. We also demonstrate that our method can be successfully combined with other quantum algorithms such as the quantum approximate optimization algorithm (QAOA). For illustration, here we study the MaxCut problem. We find that the QAOA ansatz increases the postselection success of ITE-BE, and shallow QAOA circuits, when boosted with ITE-BE, achieve better performance than deeper QAOA circuits. For the special case of the transverse initial state, we adapt our block-encoding scheme to allow for a deterministic application of the first layer of the circuit.

Zhong, Dawei [University of Southern California, L↗
DOE OSTI2020

The future of computing beyond Moore’s Law

Moore’s Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore’s Law for 50 years is failing and is anticipated to flatten by 2025. Here, this article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Visualization and Simulation of Carbon Structures with Higher Genus

The Computational Science Initiative (CSI) department at Brookhaven National Laboratory involves varied and interdisciplinary work through out all sciences. In particular, we worked within the realm of computational chemistry through the means of studying carbon nanotori structures via their visualization and simulation. Compounds like graphene and other carbon allotropes,such as the nanotorus, have been in the eye of scientists for several years due to their unique polyhex structures which provide unique topologies and therefore possibly unique material properties. C++ code to generate Cartesian coordinates for an arbitrary torus was utilized to allow the use of molecular editing and modeling programs, such as Avogadro or Visual Molecular Dynamics (VMD) to design multiple genus nanocarbon toroidal structures. Several files were generated that contained multiple genus to them, namely a double torus, triple torus, and quadruple torus, all based off of a single genus carbon nanotorus from previous said code. Bond angle information was then utilized through .report files generated from structures files (.xyz or .cml) to allow for vertices and thereby neighboring atoms to the vertices to be identified. With these identified atoms for the above multiple genus structures, as well as for the C240 buckyball fullerene and carbon nanotorus, we wrote C++ code to generate an adjacency matrix for each respective one. These matrices were then subsequently used to generate eigenvalues and eigenvectors through a Mathmatica function for each structure. Using these values we can study the energies of these systems and thereby its functionalities and properties.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

NASA Aeronautics Multidisciplinary Analysis and Design Fellowship Program

For a number of years, Virginia Tech had been on the forefront of research in the area of multidisciplinary analysis and design. In June of 1994, faculty members from aerospace and ocean engineering, engineering science and mechanics, mechanical engineering, industrial engineering, mathematics and computer sciences, at Virginia Tech joined together to form the Multidisciplinary Analysis and Design (MAD) Center for Advanced Vehicles. The center was established with the single goal: to perform research that is relevant to the needs of the US industry and to foster collaboration between the university, government and industry. In October of 1994, the center was chosen by NASA headquarters as one of the five university centers to establish a fellowship program to develop a graduate program in multidisciplinary analysis and design. The fellowship program provides full stipend and tuition support for seven U. S. students per year during their graduate studies. To advise us regarding the problems faced by the industry, an industrial advisory board has been formed consisting of representatives from industry as well as government laboratories. The function of the advisory board is to channel information from its member companies to faculty members concerning problems that need research attention in the general area of multidisciplinary design optimization (MDO). The faculty and their graduate students make proposals to the board on how to address these problems. At the annual board meeting in Blacksburg, the board discusses the proposals and suggests which students get funded under the NASA fellowship program. All students participating in the program are required to spend 3-6 months in industry working on their research projects. We are completing the third year of the fellowship program and have had three advisory board meetings in Blacksburg.

Grossman, B.↗
NASA NTRS1999

NASA Aeronautics Multidisciplinary Analysis and Design Fellowship Program

This program began as a grant from NASA Headquarters, NGT-10025, which was in effect from 10/l/93 until 10/31/96. The remaining funding for this effort was transferred from NASA Headquarters to NASA Langley and a new grant NGT-1-52155 was issued covering the period II/l/96 to 5/15/99. This report serves as the final report of NGT-1-52155. For a number of years, Virginia Tech had been on the forefront of research in the area of multidisciplinary analysis and design. In June of 1994, faculty members from aerospace and ocean engineering, engineering science and mechanics, mechanical engineering, industrial engineering, mathematics and computer sciences, at Virginia Tech joined together to form the Multidisciplinary Analysis and Design (MAD) Center for Advanced Vehicles. The center was established with the single goal: to perform research that is relevant to the needs of the US industry and to foster collaboration between the university, government and industry. In October of 1994, the center was chosen by NASA headquarters as one of the five university centers to establish a fellowship program to develop a graduate program in multidisciplinary analysis and design. The fellowship program provides full stipend and tuition support for seven U. S. students per year during their graduate studies. The grant is currently being administered by the NMO Branch of NASA Langley. To advise us regarding the problems faced by the industry, an industrial advisory board has been formed consisting of representatives from industry as well as government laboratories. The present membership includes major aerospace companies: Aurora Flight Sciences, Boeing: Philadelphia, Boeing: Long Beach, Boeing: Seattle, Boeing: St. Louis, Cessna, Ford, General Electric, Hughes, Lockheed-Martin: Palo Alto, Northrop-Grumman, Sikorsky, smaller, aerospace software companies: Aerosoft, Phoenix Integration and Proteus Engineering, along with representatives from government agencies, including: NASA Ames, Langley and Lewis. The function of the advisory board is to channel information from its member companies to faculty members concerning problems that need research attention in the general area of multidisciplinary design optimization (MDO). The faculty and their graduate students make presentations to the board on their research. The board makes recommendations on the research and suggests new areas and problems which need attention. Many students participating in the program spend 3-6 months in industry working on their research projects. We are completing the fifth year of the fellowship program and have had four advisory board meetings in Blacksburg. Ten students have spent the three month periods in industry. In addition to the research element of the MAD Center efforts we also have an academic component. We have developed a menu of design-related graduate courses and two new courses: one in Aerospace Manufacturing and another in MDO. Some of the MAD Center activities are described on the world-wide web at http://www.aoe.vt.edu/mads.html The MAD Center represents an innovative approach for joint Industry-Government-University cooperation in the development of a comprehensive program in engineering education which addresses the design needs of industry. The following charts list detail of the grant: mission of the MAD center, faculty members, purpose of the advisory board, board members, summary of the graduate and undergraduate program, history of the fellowship program, mission of the fellowship program, requirements of MAD fellows, course requirements, students supported, advisory board participants, and MAD center research papers

Grossman, B.↗
NASA NTRS2001

High-Performance Java Codes for Computational Fluid Dynamics

The computational science community is reluctant to write large-scale computationally -intensive applications in Java due to concerns over Java's poor performance, despite the claimed software engineering advantages of its object-oriented features. Naive Java implementations of numerical algorithms can perform poorly compared to corresponding Fortran or C implementations. To achieve high performance, Java applications must be designed with good performance as a primary goal. This paper presents the object-oriented design and implementation of two real-world applications from the field of Computational Fluid Dynamics (CFD): a finite-volume fluid flow solver (LAURA, from NASA Langley Research Center), and an unstructured mesh adaptation algorithm (2D_TAG, from NASA Ames Research Center). This work builds on our previous experience with the design of high-performance numerical libraries in Java. We examine the performance of the applications using the currently available Java infrastructure and show that the Java version of the flow solver LAURA performs almost within a factor of 2 of the original procedural version. Our Java version of the mesh adaptation algorithm 2D_TAG performs within a factor of 1.5 of its original procedural version on certain platforms. Our results demonstrate that object-oriented software design principles are not necessarily inimical to high performance.

Riley, Christopher↗
DOE OSTI2020

Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics

The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their as- sociated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

Parete-Koon, Suzanne↗
DOE OSTI2025

Circuit complexity and functionality: A statistical thermodynamics perspective

Circuit complexity, defined as the minimum circuit size required for implementing a particular Boolean computation, is a foundational concept in computer science. Determining circuit complexity is believed to be a hard computational problem. Recently, in the context of black holes, circuit complexity has been promoted to a physical property, wherein the growth of complexity is reflected in the time evolution of the Einstein-Rosen bridge (“wormhole”) connecting the two sides of an anti-de Sitter “eternal” black hole. Here, we are motivated by an independent set of considerations and explore links between complexity and thermodynamics for functionally equivalent circuits, making the physics-inspired approach relevant to real computational problems, for which functionality is the key element of interest. In particular, our thermodynamic framework provides an alternative perspective on the obfuscation of programs of arbitrary length—an important problem in cryptography—as thermalization through recursive mixing of neighboring sections of a circuit, which can be viewed as the mixing of two containers with “gases of gates.” This recursive process equilibrates the average complexity and leads to the saturation of the circuit entropy, while preserving functionality of the overall circuit. The thermodynamic arguments hinge on ergodicity in the space of circuits which we conjecture is limited to disconnected ergodic sectors due to fragmentation. The notion of fragmentation has important implications for the problem of circuit obfuscation as it implies that there are circuits of same size and functionality that cannot be connected via a polynomial number of local moves. Furthermore, we argue that fragmentation is unavoidable unless the complexity classes NP and coNP coincide, a statement that implies the collapse of the polynomial hierarchy of computational complexity theory to its first level.

Science & Technology - Other Topics↗
DOE OSTI2015

VERAIn

CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERA Input into an XML file that is used as input to different VERA codes.

Simunovic, Srdjan↗
DOE OSTI2015

VERAIn

CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERA Input into an XML file that is used as input to different VERA codes.

Simunovic, Srdjan↗
DOE OSTI2015

Dehydration pathways of 1-propanol on HZSM-5 in the presence and absence of water

The Brønsted acid-catalyzed gas-phase dehydration of 1-propanol (0.075-4 kPa) was studied on zeolite H-MFI (Si/Al = 26, containing minimal amounts of extraframework Al moieties) in the absence and presence of co-fed water (0-2.5 kPa) at 413-443 K. It is shown that propene can be formed from monomeric and dimeric adsorbed 1-propanol. The stronger adsorption of 1-propanol relative to water indicates that the reduced dehydration rates in the presence of water are not a consequence of the competitive adsorption between 1-propanol and water. Instead, the deleterious effect is related to the different extents of stabilization of adsorbed intermediates and the relevant elimination/substitution transition states by water. Water stabilizes the adsorbed 1-propanol monomer significantly more than the elimination transition state, leading to a higher activation barrier and a greater entropy gain for the rate-limiting step, which eventually leads to propene. In a similar manner, an excess of 1-propanol stabilizes the adsorbed state of 1-propanol more than the elimination transition state. In comparison with the monomer-mediated pathway, adsorbed dimer and the relevant transition states for propene and ether formation are similarly, while less effectively, stabilized by intrazeolite water molecules. This work was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, and was performed in part using the Molecular Sciences Computing Facility (MSCF) in the William R. Wiley Environmental Molecular Sciences Laboratory, a DOE national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located and the Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for DOE.

1-propanol↗
DOE OSTI2023

Engineering Computational Practices (Rev. 1)

This manual will attempt to motivate the use of an automated build system for the purposes of computational science and engineering. As part of this motivation, the surrounding computational practices of version control, documen tation, compute environment management, and regression testing will also be addressed as applied to the practice of computational engineering. Specifically, this manual intends to motivate the adoption of these traditional software engineering practices for use in research and production engineering simulation projects. This manual is not the first such effort in the greater scientific computing community. In fact, the authors relied heavily on the lesson plans of the Software Carpentry, established to teach computing skills to researchers in 1998. As the intention for this manual is to lay out fundamental practices of engineering computing, it will not attempt to fully teach the underlying concepts and will instead reference the well designed lesson plans of the Software Carpentry. Where possible, this manual will explain to general computing practices and concepts and limit discussion of specific software implementations to examples or vehicles for practice in concrete application. The specific software taught by the Software Carpentry curriculum is an excellent starting point to learn the core concepts of computational engi neering. However, the authors have found that applications to engineering simulation and analysis require translation of these software development concepts into the language and workflows of computational engineers. Adopting these computational tools may require engineers to re-imagine their workflows in some combination of traditional engineer ing and software concepts. It has also been necessary to extend existing software build systems for engineering practices beyond the simple wrap ping of engineering software execution. Where necessary, examples of specific software and their method of extension to engineering simulations will be given, with reference to the User Manual for recommended practical use. Where this manual relies on specific implementation examples, it should be understood that the practicing engineer may find that different software is more amenable to their specific work. It is always the overall collection of computational practices is more important than any specific software implementation. The ability to recognize which concepts are implemented by a software package will make a practicing engineer agile to changing project needs, computing resources, numeric solvers, programming languages, and even available funding.

42 ENGINEERING↗
NASA NTRS2004

Computing and combustion

Coming into the Combustion Branch of the Turbomachinery and Propulsion Systems Division, there was not any set project planned out for me to work on. This was understandable, considering I am only at my sophmore year in college. Also, my mentor was a division chief and it was expected that I would be passed down the line. It took about a week for me to be placed with somebody who could use me. My first project was to write a macro for TecPlot. Commonly, a person would have a 3D contour volume modeling something such as a combustion engine. This 3D volume needed to have slices extracted from it and made into 2D scientific plots with all of the appropriate axis and titles. This was very tedious to do by hand. My macro needed to automate the process. There was some education I needed before I could start, however. First, TecPlot ran on Unix and Linux, like a growing majority of scientific applications. I knew a little about Linux, but I would need to know more to use the software at hand. I took two classes at the Learning Center on Unix and am now comfortable with Linux and Unix. I already had taken Computer Science I and II, and had undergone the transformation from Computer Programmer to Procedural Epistemologist. I knew how to design efficient algorithms, I just needed to learn the macro language. After a little less than a week, I had learned the basics of the language. Like most languages, the best way to learn more of it was by using it. It was decided that it was best that I do the macro in layers, starting simple and adding features as I went. The macro started out slicing with respect to only one axis, and did not make 2D plots out of the slices. Instead, it lined them up inside the solid. Next, I allowed for more than one axis and placed each slice in a separate frame. After this, I added code that transformed each individual slice-frame into a scientific plot. I also made frames for composite volumes, which showed all of the slices in the same XYZ space. I then designed an addition companion macro that exported each frame into its own image file. I then distributed the macros to a test group, and am awaiting feedback. In the meantime, a am researching the possible applications of distributed computing on the National Combustor Code. Many of our Linux boxes were idle for most of the day. The department thinks that it would be wonderful if we could get all of these idle processors to work on a problem under the NCC code. The client software would have to be easily distributed, such as in screensaver format or as a program that only ran when the computer was not in use. This project proves to be an interesting challenge.

Thompson, Daniel↗
NASA NTRS1995

NASA Tech Briefs, May 1995

This issue features an resource report on Jet Propulsion Laboratory and a special focus on advanced composites and plastics. It also contains articles on electronic components and circuits, electronic systems, physical sciences, computer programs, mechanics, machinery, manufacturing and fabrication, mathematics and information sciences, and life sciences. This issue also contains a supplement on federal laboratory test and measurements.

Source record↗
DOE OSTI2015

Neuromorphic Computing – From Materials Research to Systems Architecture Roundtable

Computation in its many forms is the engine that fuels our modern civilization. Modern computation—based on the von Neumann architecture—has allowed, until now, the development of continuous improvements, as predicted by Moore’s law. However, computation using current architectures and materials will inevitably—within the next 10 years—reach a limit because of fundamental scientific reasons. DOE convened a roundtable of experts in neuromorphic computing systems, materials science, and computer science in Washington on October 29-30, 2015 to address the following basic questions: Can brain-like (“neuromorphic”) computing devices based on new material concepts and systems be developed to dramatically outperform conventional CMOS based technology? If so, what are the basic research challenges for materials sicence and computing? The overarching answer that emerged was: The development of novel functional materials and devices incorporated into unique architectures will allow a revolutionary technological leap toward the implementation of a fully “neuromorphic” computer. To address this challenge, the following issues were considered: The main differences between neuromorphic and conventional computing as related to: signaling models, timing/clock, non-volatile memory, architecture, fault tolerance, integrated memory and compute, noise tolerance, analog vs. digital, and in situ learning New neuromorphic architectures needed to: produce lower energy consumption, potential novel nanostructured materials, and enhanced computation Device and materials properties needed to implement functions such as: hysteresis, stability, and fault tolerance Comparisons of different implementations: spin torque, memristors, resistive switching, phase change, and optical schemes for enhanced breakthroughs in performance, cost, fault tolerance, and/or manufacturability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Quantum Computing as a High School Module

Quantum computing is a growing field at the intersection of physics and computer science. This module introduces three of the key principles that govern how quantum computers work: superposition, quantum measurement, and entanglement. The goal of this module is to bridge the gap between popular science articles and advanced undergraduate texts by making some of the more technical aspects accessible to motivated high school students. Problem sets and simulation based labs of various levels are included to reinforce the conceptual ideas described in the text. This is intended as a one week course for high school students between the ages of 15-18 years. The course begins by introducing basic concepts in quantum mechanics which are needed to understand quantum computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

The promotional effects of cesium promoter on higher alcohol synthesis from syngas over cesium-promoted Cu/ZnO/Al2O3 catalysts

In this study, the promotional effects of cesium promoter on higher alcohol (C2+OH) synthesis from syngas over Cs-Cu/ZnO/Al2O3 catalysts were investigated using a combined experimental and theoretical density functional theory (DFT) calculation method. In the presence of cesium, the C2+OH productivity increases from 77.1 g•kgcat-1•h-1 to 157.3 g•kgcat-1•h-1 at 583 K due to the enhancement of the initial C–C bond formation. Detailed analysis of chain growth probabilities (CGPs) confirms that initial C–C bond formation is the rate-determining step in the temperature range of 543-583 K. Addition of cesium promoter significantly increases the productivities of 2-methyl-1-propanol, while the CGPs values (C3* to 2-methyl-C3*) is almost unaffected. With the assistance of cesium promoter, the CGPs of the initial C–C bond formation step (C1* to C2*) could be increased from 0.13 to 0.25 at 583 K. DFT calculations indicate that the initial C–C bond formation is mainly contributed by the HCO+HCO coupling reaction over the ZnCu(211) model surface. In the presence of the Cs2O, the stabilities of key reaction intermediates such as HCO and H2CO are enhanced which facilitates both HCO+HCO and HCO+H2CO coupling reaction steps with lower activation barriers over the Cs2O-ZnCu(211) surface. The promotional effects of cesium on the C2+OH productivity are also benefited from the competitive CH+HCO coupling reaction over CH hydrogenation that leads to lower alkane formation. In addition, Bader charge analysis suggests that the presence of cesium ions would facilitate the nucleophilic reaction between HCO and H2CO for initial C–C bond formation. This work was supported by the National Natural Science Foundation of China (No. 91545114 and No. 91545203). We appreciate the joint PhD scholarship support from the China Scholarship Council. The authors would also like to thank the support from Collaborative Innovation Center of Chemistry for Energy Materials (2011-iChEM). DM was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences. Computing time was granted by the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research. PNNL is a multiprogram national laboratory operated for DOE by Battelle Memorial Institute. We also appreciate the support from Sinochem Quanzhou Petrochemical Co. Ltd.

cesium↗