3 resultados para triton binding energy
em Duke University
Resumo:
(1)H NMR spectroscopy is used to investigate a series of microporous activated carbons derived from a poly(ether ether ketone) (PEEK) precursor with varying amounts of burnoff (BO). In particular, properties relevant to hydrogen storage are evaluated such as pore structure, average pore size, uptake, and binding energy. High-pressure NMR with in situ H(2) loading is employed with H(2) pressure ranging from 100 Pa to 10 MPa. An N(2)-cooled cryostat allows for NMR isotherm measurements at both room temperature ( approximately 290 K) and 100 K. Two distinct (1)H NMR peaks appear in the spectra which represent the gaseous H(2) in intergranular pores and the H(2) residing in micropores. The chemical shift of the micropore peak is observed to evolve with changing pressure, the magnitude of this effect being correlated to the amount of BO and therefore the structure. This is attributed to the different pressure dependence of the amount of adsorbed and non-adsorbed molecules within micropores, which experience significantly different chemical shifts due to the strong distance dependence of the ring current effect. In pores with a critical diameter of 1.2 nm or less, no pressure dependence is observed because they are not wide enough to host non-adsorbed molecules; this is the case for samples with less than 35% BO. The largest estimated pore size that can contribute to the micropore peak is estimated to be around 2.4 nm. The total H(2) uptake associated with pores of this size or smaller is evaluated via a calibration of the isotherms, with the highest amount being observed at 59% BO. Two binding energies are present in the micropores, with the lower, more dominant one being on the order of 5 kJ mol(-1) and the higher one ranging from 7 to 9 kJ mol(-1).
Resumo:
The growth and proliferation of invasive bacteria in engineered systems is an ongoing problem. While there are a variety of physical and chemical processes to remove and inactivate bacterial pathogens, there are many situations in which these tools are no longer effective or appropriate for the treatment of a microbial target. For example, certain strains of bacteria are becoming resistant to commonly used disinfectants, such as chlorine and UV. Additionally, the overuse of antibiotics has contributed to the spread of antibiotic resistance, and there is concern that wastewater treatment processes are contributing to the spread of antibiotic resistant bacteria.
Due to the continually evolving nature of bacteria, it is difficult to develop methods for universal bacterial control in a wide range of engineered systems, as many of our treatment processes are static in nature. Still, invasive bacteria are present in many natural and engineered systems, where the application of broad acting disinfectants is impractical, because their use may inhibit the original desired bioprocesses. Therefore, to better control the growth of treatment resistant bacteria and to address limitations with the current disinfection processes, novel tools that are both specific and adaptable need to be developed and characterized.
In this dissertation, two possible biological disinfection processes were investigated for use in controlling invasive bacteria in engineered systems. First, antisense gene silencing, which is the specific use of oligonucleotides to silence gene expression, was investigated. This work was followed by the investigation of bacteriophages (phages), which are viruses that are specific to bacteria, in engineered systems.
For the antisense gene silencing work, a computational approach was used to quantify the number of off-targets and to determine the effects of off-targets in prokaryotic organisms. For the organisms of
Regarding the work with phages, the disinfection rates of bacteria in the presence of phages was determined. The disinfection rates of
In addition to determining disinfection rates, the long-term bacterial growth inhibition potential was determined for a variety of phages with both Gram-negative and Gram-positive bacteria. It was determined, that on average, phages can be used to inhibit bacterial growth for up to 24 h, and that this effect was concentration dependent for various phages at specific time points. Additionally, it was found that a phage cocktail was no more effective at inhibiting bacterial growth over the long-term than the best performing phage in isolation.
Finally, for an industrial application, the use of phages to inhibit invasive
In conclusion, this dissertation improved the current methods for designing antisense gene silencing targets for prokaryotic organisms, and characterized phages from an engineering perspective. First, the current design strategy for antisense targets in prokaryotic organisms was improved through the development of an algorithm that minimized the number of off-targets. For the phage work, a framework was developed to predict the disinfection rates in terms of the initial phage and bacterial concentrations. In addition, the long-term bacterial growth inhibition potential of multiple phages was determined for several bacteria. In regard to the phage application, phages were shown to protect both final product yields and yeast concentrations during fermentation. Taken together, this work suggests that the rational design of phage treatment is possible and further work is needed to expand on this foundation.
Resumo:
Free energy calculations are a computational method for determining thermodynamic quantities, such as free energies of binding, via simulation.
Currently, due to computational and algorithmic limitations, free energy calculations are limited in scope.
In this work, we propose two methods for improving the efficiency of free energy calculations.
First, we expand the state space of alchemical intermediates, and show that this expansion enables us to calculate free energies along lower variance paths.
We use Q-learning, a reinforcement learning technique, to discover and optimize paths at low computational cost.
Second, we reduce the cost of sampling along a given path by using sequential Monte Carlo samplers.
We develop a new free energy estimator, pCrooks (pairwise Crooks), a variant on the Crooks fluctuation theorem (CFT), which enables decomposition of the variance of the free energy estimate for discrete paths, while retaining beneficial characteristics of CFT.
Combining these two advancements, we show that for some test models, optimal expanded-space paths have a nearly 80% reduction in variance relative to the standard path.
Additionally, our free energy estimator converges at a more consistent rate and on average 1.8 times faster when we enable path searching, even when the cost of path discovery and refinement is considered.