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This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (NanoMOFdeli), ERC-2016-COG 726380, Innovate UK (104384) and EPSRC IAA (IAA/RG85685). N.R. acknowledges the support of the Cambridge International Scholarship and the TrinityHenry Barlow Scholarship (Honorary). O.K.F. and R.Q.S. acknowledge funding from the U.S. Department of Energy (DE-FG02-08ER15967). R.S.F. and D.B. acknowledge funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (SCoTMOF), ERC-2015-StG 677289. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525. The authors gratefully acknowledge funding from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office, through the Hydrogen Storage Materials Advanced Research Consortium (HyMARC). This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. J.D.E. acknowledges the support of the Alexander von Humboldt Foundation and the Center for Information Services and High Performance Computing (ZIH) at TU Dresden. S.K.G. and S.M. acknowledge SERB (Project No. CRG/2019/000906), India for financial support. K.K. and R.K. acknowledge Active Co. Research Grant for funding. S.K. acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (COSMOS), ERC-2017-StG 756489. N.L. and J.G.M acknowledge funding from the European Commission through the H2020-MSCA-RISE-2019 program (ZEOBIOCHEM -872102) and the Spanish MICINN and AEI/FEDER (RTI2018-099504-B-C21). N.L. thanks the University of Alicante for funding (UATALENTO17-05). ICN2 is supported by the Severo Ochoa program from the Spanish MINECO (Grant No. SEV-2017-0706) S.M.J.R. and A.L. wish to thank the Fund for Scientific Research Flanders (FWO), under grant nos. 12T3519N and 11D2220N. L.S. was supported by the EPSRC Cambridge NanoDTC EP/L015978/1. C.T.Y. and T.S.N. acknowledges funds from the National Research Foundation of Korea, NRF-2017M3A7B4042140 and NRF-2017M3A7B4042235. P.F. and H. Y. acknowledge US Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Award No. DE-SC0010596 (P.F.). R.O. would like to acknowledge funding support during his Ph.D. study from Indonesian Endowment Fund for Education-LPDP with the contract No. 202002220216006. Daniel Siderius: Official contribution of the National Institute of Standards and Technology (NIST), not subject to copyright in the United States of America. Daniel Siderius: Certain commercially available items may be identified in this paper. This identification does not imply recommendation by NIST, nor does it imply that it is the best available for the purposes described. B.V.L, S.T.E and A.M.P acknowledge funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Program (Grant agreement no. 639233, COFLeaf)., Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer–Emmett–Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of microand mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This roundrobin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called “BET surface identification” (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible., European Research Council (ERC) ERC-2016-COG 726380 ERC-2015-StG 677289 ERC-2017-StG 756489 639233, UK Research & Innovation (UKRI) Innovate UK 104384 UK Research & Innovation (UKRI), Engineering & Physical Sciences Research Council (EPSRC) IAA/RG85685, Cambridge International Scholarship TrinityHenry Barlow Scholarship, United States Department of Energy (DOE) DE-FG02-08ER15967, National Nuclear Security Administration DE-NA-0003525, United States Department of Energy (DOE), Alexander von Humboldt Foundation, Center for Information Services and High Performance Computing (ZIH) at TU Dresden, Department of Science & Technology (India), Science Engineering Research Board (SERB), India CRG/2019/000906, Active Co. Research Grant, European Commission through the H2020-MSCA-RISE-2019 program ZEOBIOCHEM -872102, Spanish MICINN and AEI/FEDER RTI2018-099504-B-C21, University of Alicante UATALENTO17-05, Spanish Government SEV-2017-0706 FWO 12T3519N 11D2220N, UK Research & Innovation (UKRI), Engineering & Physical Sciences Research Council (EPSRC) EP/L015978/1, National Research Foundation of Korea NRF-2017M3A7B4042140 NRF-2017M3A7B4042235, United States Department of Energy (DOE) DE-SC0010596, Indonesian Endowment Fund for Education-LPDP 202002220216006

Atomically detailed simulations have become an important complement to experimental studies of nanoporous materials. Large databases of crystalline porous material structures have been available fo...

Nanofiber mats hold potential in numerous applications that interface with microorganisms. However, a fundamental study that quantifies the transport of microorganisms into three-dimensional microenvironments, such as nanofiber mats, has not yet been conducted. Here, we evaluate the microbial uptake capacity of three hydrophilic cellulose sorbents, a high surface area electrospun nanofiber mat, as well as two commercial products, a macrofibrous Fisherbrand fabric and an adsorptive Sartorius membrane. The small average fiber diameter (∼1.0 μm) and large porosity of the nanofiber mats enabled a 21 times greater collection of Escherichia coli K12 per milligram of material than the macrofibrous Fisherbrand controls and 220 times more than the Sartorius controls. In most cases, the exposure time of the nanofiber mats to the microorganisms was sufficient to reach a quasi-equilibrium state of microbial uptake, allowing the calculation of an adsorption coefficient (Keq) that relates the concentration of cells in the sorbent to the concentration of cells remaining in solution. The Keq of the nanofiber mats was 420, compared to 9.2 and 0.67 for the Fisherbrand and Sartorius controls, respectively. In addition to E. coli, we studied the cellulose nanofiber mat uptake of two additional medically relevant and distinct microorganisms, Gram-negative Pseudomonas aeruginosa PA01 and Gram-positive Staphylococcus aureus MW2, to probe whether microorganism removal is bacteria-specific. The high uptake capacity of all three bacteria by the nanofiber mats indicates that microbial uptake is independent of the microorganism's adhesion mechanism. This work suggests that cellulose nanofiber mat “sponges” are a green platform technology that has the potential to remove detrimental microorganisms from wounds, trap bacteria within a protective military textile, or remediate contaminated water.

A computational study is presented in which real-time manipulation of the interaction potential between particles in a colloidal system is used to control their assembly into a close-packed crystalline object. The basic model used throughout the study is a high-fidelity representation of a real experimental system in which 32 colloidal silica particles are suspended in aqueous solution with polymer hydrogel providing a temperature-tunable attractive force between the particles. Diffusion mapping is used to determine a set of coarse variables that provide an appropriate low-dimensional representation of this system at four discrete values of the attraction strength. In this case the diffusion mapping process identified two dimensions; one correlates well with the radius of gyration of the entire set of particles and the other correlates well with the average distance between distinct clusters of particles. Two different stochastic models are then built in the two-dimensional (2D) space of these variables, using data from a large number of short Brownian dynamics simulations of the full 32-particle system. The first 2D model is based on a Smoluchowski framework and is used to characterize the overall equilibrium and diffusive properties of the system. The second 2D model is based on a transition rate matrix and is used for process control. A control policy based on an infinite-horizon Markov decision process is developed using the four different attraction strengths as the input variables. The resulting policy is non-trivial; rather than simply selecting the strongest level of attraction, some mix of weak and strong attractions generally provides the optimal approach to the target close-packed state. This study, while focused on the particular mechanism of tunable depletion attraction, suggests a general strategy that could be adapted to different mechanisms of actuating colloidal assembly.

Here we construct a low-dimensional Smoluchowski model for electric field mediated colloidal crystallization using Brownian dynamic simulations, which were previously matched to experiments. Diffusion mapping is used to infer dimensionality and confirm the use of two order parameters, one for degree of condensation and one for global crystallinity. Free energy and diffusivity landscapes are obtained as the coefficients of a low-dimensional Smoluchowski equation to capture the thermodynamics and kinetics of microstructure evolution. The resulting low-dimensional model quantitatively captures the dynamics of different assembly pathways between fluid, polycrystal, and single crystals states, in agreement with the full N-dimensional data as characterized by first passage time distributions. Numerical solution of the low-dimensional Smoluchowski equation reveals statistical properties of the dynamic evolution of states vs. applied field amplitude and system size. The low-dimensional Smoluchowski equation and associated landscapes calculated here can serve as models for predictive control of electric field mediated assembly of colloidal ensembles into two-dimensional crystalline objects.

The objective of this work is to elucidate controlling mechanisms in NOx reduction, develop reduced-order reaction models, and analyze the reactor performance using the reduced-order reaction model for the NO–CO reaction. We start with the microkinetic model on platinum, which describes the mechanism of catalytic reduction of NO by CO. The formation of the main product N2O and the competitive formation of the side product N2 are accounted for in the microkinetic model. Sensitivity and reaction path analysis have been carried out to determine the rate-limiting steps as well as the most abundant reactive intermediates in the system. Owing to the differences between system performance at high and low temperatures, the model has been analyzed in detail in these temperature regimes. Two closed-form expressions, corresponding to the two global reactions involved, have been derived. The characteristic features of the microkinetic model such as the sharp increase in NO conversion and the selectivity to N2O are captured well by the reduced model. The reduced-order model has been extended to the rhodium catalyst as well. © 2012 Wiley Periodicals, Inc. Int J Chem Kinet 44: 577–585, 2012