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Qi-Jun Hong

Bio: Qi-Jun Hong is an academic researcher from Brown University. The author has contributed to research in topics: Melting point & Ab initio. The author has an hindex of 13, co-authored 26 publications receiving 667 citations. Previous affiliations of Qi-Jun Hong include Arizona State University & California Institute of Technology.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the catalytic kinetics of CO2 fixation to methanol over a binary catalyst Cu/ZrO2 is investigated by first principles kinetic Monte Carlo simulation.

169 citations

Journal ArticleDOI
04 Jan 2021
TL;DR: In this article, the authors identify a promising pool of candidate substitute alloys consisting of Mo, Ru, Ta, and W and demonstrate that one of the candidates, Mo0.122, exhibits a high melting temperature (around 2626 K), thus supporting its use in high-temperature applications.
Abstract: While rhenium is an ideal material for rapid thermal cycling applications under high temperatures, such as rocket engine nozzles, its high cost limits its widespread use and prompts an exploration of viable cost-effective substitutes. In prior work, we identified a promising pool of candidate substitute alloys consisting of Mo, Ru, Ta, and W. In this work we demonstrate, based on density functional theory melting temperature calculations, that one of the candidates, Mo0.292Ru0.555Ta0.031W0.122, exhibits a high melting temperature (around 2626 K), thus supporting its use in high-temperature applications.

125 citations

Journal ArticleDOI
TL;DR: In this paper, the authors conduct an extensive investigation into the Hf-Ta-C system, which includes the compounds that have the highest melting points known to date, and identify three major chemical factors that contribute to the high melting temperatures.
Abstract: Using electronic structure calculations, we conduct an extensive investigation into the Hf-Ta-C system, which includes the compounds that have the highest melting points known to date. We identify three major chemical factors that contribute to the high melting temperatures. Based on these factors, we propose a class of materials that may possess even higher melting temperatures and explore it via efficient ab initio molecular dynamics calculations in order to identify the composition maximizing the melting point. This study demonstrates the feasibility of automated and high-throughput materials screening and discovery via ab initio calculations for the optimization of “higher-level” properties, such as melting points, whose determination requires extensive sampling of atomic configuration space.

120 citations

Posted ContentDOI
Estee Y Cramer1, Evan L. Ray1, Velma K. Lopez2, Johannes Bracher3  +281 moreInstitutions (53)
05 Feb 2021-medRxiv
TL;DR: In this paper, the authors systematically evaluated 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level at the CDC.
Abstract: Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies In 2020, the COVID-19 Forecast Hub (https://covid19forecasthuborg/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level One of these models was a multi-model ensemble that combined all available forecasts each week The performance of individual models showed high variability across time, geospatial units, and forecast horizons Half of the models evaluated showed better accuracy than a naive baseline model In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

68 citations

Journal ArticleDOI
TL;DR: In this paper, the authors performed an extensive analysis on CO 2 hydrogenation over a Cu/ZrO 2 model catalyst by employing density functional theory (DFT) calculations and kinetic Monte Carlo (kMC) simulations based on the continuous stirred tank model.

64 citations


Cited by
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01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 citations

Journal ArticleDOI
TL;DR: A critical review of recent developments in hydrogenation reaction, with emphases on catalytic reactivity, reactor innovation, and reaction mechanism, provides an overview regarding the challenges and opportunities for future research in the field.
Abstract: Owing to the increasing emissions of carbon dioxide (CO2), human life and the ecological environment have been affected by global warming and climate changes. To mitigate the concentration of CO2 in the atmosphere various strategies have been implemented such as separation, storage, and utilization of CO2. Although it has been explored for many years, hydrogenation reaction, an important representative among chemical conversions of CO2, offers challenging opportunities for sustainable development in energy and the environment. Indeed, the hydrogenation of CO2 not only reduces the increasing CO2 buildup but also produces fuels and chemicals. In this critical review we discuss recent developments in this area, with emphases on catalytic reactivity, reactor innovation, and reaction mechanism. We also provide an overview regarding the challenges and opportunities for future research in the field (319 references).

2,539 citations

Journal ArticleDOI
TL;DR: Chemical recycling of CO2 to renewable fuels and materials, primarily methanol, offers a powerful alternative to tackle both issues, that is, global climate change and fossil fuel depletion.
Abstract: Starting with coal, followed by petroleum oil and natural gas, the utilization of fossil fuels has allowed the fast and unprecedented development of human society. However, the burning of these resources in ever increasing pace is accompanied by large amounts of anthropogenic CO2 emissions, which are outpacing the natural carbon cycle, causing adverse global environmental changes, the full extent of which is still unclear. Even through fossil fuels are still abundant, they are nevertheless limited and will, in time, be depleted. Chemical recycling of CO2 to renewable fuels and materials, primarily methanol, offers a powerful alternative to tackle both issues, that is, global climate change and fossil fuel depletion. The energy needed for the reduction of CO2 can come from any renewable energy source such as solar and wind. Methanol, the simplest C1 liquid product that can be easily obtained from any carbon source, including biomass and CO2, has been proposed as a key component of such an anthropogenic carbon cycle in the framework of a “Methanol Economy”. Methanol itself is an excellent fuel for internal combustion engines, fuel cells, stoves, etc. It's dehydration product, dimethyl ether, is a diesel fuel and liquefied petroleum gas (LPG) substitute. Furthermore, methanol can be transformed to ethylene, propylene and most of the petrochemical products currently obtained from fossil fuels. The conversion of CO2 to methanol is discussed in detail in this review.

1,012 citations

Journal ArticleDOI
TL;DR: In this article, a mean-field microkinetic model for methanol synthesis and water-gas-shift (WGS) reactions is presented, which includes novel reaction intermediates, such as formic acid (HCOOH) and hydroxymethoxy (CH3O2) and allows for the formation of formic acids, formaldehyde (CH2O), and methyl formate (HCOCH3) as byproducts.
Abstract: We present a comprehensive mean-field microkinetic model for the methanol synthesis and water-gas-shift (WGS) reactions that includes novel reaction intermediates, such as formic acid (HCOOH) and hydroxymethoxy (CH3O2) and allows for the formation of formic acid (HCOOH), formaldehyde (CH2O), and methyl formate (HCOOCH3) as byproducts. All input model parameters were initially derived from periodic, self-consistent, GGA-PW91 density functional theory calculations on the Cu(111) surface and subsequently fitted to published experimental methanol synthesis rate data, which were collected under realistic conditions on a commercial Cu/ZnO/Al2O3 catalyst. We find that the WGS reaction follows the carboxyl (COOH)-mediated path and that both CO and CO2 hydrogenation pathways are active for methanol synthesis. Under typical industrial methanol synthesis conditions, CO2 hydrogenation is responsible for ∼2/3 of the methanol produced. The intermediates of the CO2 pathway for methanol synthesis include HCOO*, HCOOH*, C...

904 citations