Molecular modelling and machine learning for high-throughput screening of metal-organic frameworks for hydrogen storage

ABSTRACT

Hydrogen is an appealing energy storage solution for electric vehicles due to its low environmental impact and faster recharge times compared to batteries. However, there are many engineering challenges involved in safely storing a sufficient amount of hydrogen onboard a vehicle with a reasonable volumetric density. Nanoporous materials such as metal–organic frameworks (MOFs) have the potential to store hydrogen at high density and only moderate pressure. Considerable research has been devoted to finding new MOFs for hydrogen storage in recent years; however, a MOF that provides sufficient hydrogen density and is suitable to commercial applications has not yet been found. Much of this research makes use of molecular modelling to screen thousands of materials in a high-throughput way. Computational screening can be an effective tool for gaining insight into structure-performance relationships as well as finding specific candidates for an application. Recently, some research groups have also used machine learning to analyze data more effectively and accelerate the screening process. In this review, we discuss some recent advances in using molecular modelling and machine learning to find materials for hydrogen storage. We also discuss and compare some popular models for the hydrogen molecule and the accuracy of different equations of state, which are important considerations for accurate molecular simulations.     

Influences of lithium doping and fullerene impregnation on hydrogen storage in metal organic frameworks

Using the grand canonical ensemble Monte Carlo method, two similar metal organic frameworks (isoreticular MOFs [IRMOF]-12 and -14) and their modified structures by doping lithium (Li) atoms above the organic units and/or impregnating with fullerenes in their cavities have been employed to investigate the capacities of H₂ storage. Our simulations show that the H₂ uptakes of Li-C₆₀@Li-IRMOF-12 and Li-C₆₀@Li-IRMOF-14 achieve the U.S. Department of Energy targets before 2017 both in gravimetric density and in volumetric density at 243 K and 100 bar. Combining the results of IRMOF-10-based structures, we further study the relationships between the H₂ uptakes and the physical properties of the materials to identify the influence factors on the H₂ storage at room temperature.     

Tuning hydrogen storage of carbon nanotubes by mechanical bending: theoretical study

The effects of mechanical bending on tuning the hydrogen storage of titanium functionalised (4,0) carbon nanotube have been assessed using density functional theory calculations with reference to the ultimate targets of the US Department of Energy (DOE). The assessment has been carried out in terms of physisorption, gravimetric capacity, projected densities of states, statistical thermodynamic stability and reaction kinetics. The Ti atom binds at the hollow site of the hexagonal ring. The average adsorption energies (?0.54 eV) per hydrogen molecule meet the DOE target for physisorption (?0.20 to ?0.60 eV). The curvature attributed to the bending angle has no effect on the average adsorption energies per H₂ molecule. With no metal clustering, the system gravimetric capacities are expected to be as large as 9.0 wt%. The reactions of the deformed (bent) carbon nanotube have higher probabilities of occurring than those of the un-deformed carbon nanotube. The Gibbs free energies, enthalpies and entropies meet the ultimate targets of the DOE for all temperatures and pressures. The closest reactions to zero free energy occur at (378.15 K/2.961 atm.) and reverse at (340 and 360 K/1 atm.). The translational component is found to exact a dominant effect on the total entropy change with temperature. Favourable kinetics of the reactions at the temperatures targeted by DOE are reported regardless of the applied pressure. The more preferable thermodynamic properties assigned to the bending nanotube imply that hydrogen storage can be improved compared to the nonbending nanotube.     

RecA-mediated homology search as a nearly optimal signal detection system

Homologous recombination facilitates the exchange of genetic material between homologous DNA molecules. This crucial process requires detecting a specific homologous DNA sequence within a huge variety of heterologous sequences. The detection is mediated by RecA in E. coli, or members of its superfamily in other organisms. Here, we examine how well the RecA-DNA interaction is adjusted to its task. By formulating the DNA recognition process as a signal detection problem, we find the optimal value of binding energy that maximizes the ability to detect homologous sequences. We show that the experimentally observed binding energy is nearly optimal. This implies that the RecA-induced deformation and the binding energetics are fine-tuned to ensure optimal sequence detection. Our analysis suggests a possible role for DNA extension by RecA, in which deformation enhances detection. The present signal detection approach provides a general recipe for testing the optimality of other molecular recognition systems.     

Exploring conditions that make cortical bone geometry optimal for physiological loading

Biomechanics and Modeling in Mechanobiology - While physiological loading on lower long bones changes during bone development, the bone cross section either remains circular or slowly changes from...     

Acetate as a carbon source for hydrogen production by photosynthetic bacteria

Hydrogen is a clean energy alternative to fossil fuels. Photosynthetic bacteria produce hydrogen from organic compounds by an anaerobic light-dependent electron transfer process. In the present study hydrogen production by three photosynthetic bacterial strains (Rhodopseudomonas sp., Rhodopseudomonas palustris and a non-identified strain), from four different short-chain organic acids (lactate, malate, acetate and butyrate) was investigated. The effect of light intensity on hydrogen production was also studied by supplying two different light intensities, using acetate as the electron donor. Hydrogen production rates and light efficiencies were compared. Rhodopseudomonas sp. produced the highest volume of H2. This strain reached a maximum H2 production rate of 25 ml H2 l(-1) h(-1), under a light intensity of 680 micromol photons m(-2) s(-1), and a maximum light efficiency of 6.2% under a light intensity of 43 micromol photons m(-2) s(-1). Furthermore, a decrease in acetate concentration from 22 to 11 mM resulted in a decrease in the hydrogen evolved from 214 to 27 ml H2 per vessel.     

Predicting the optimal geometry of microneedles and their array for dermal vaccination using a computational model

Microneedle arrays have been developed to deliver a range of biomolecules including vaccines into the skin. These microneedles have been designed with a wide range of geometries and arrangements within an array. However, little is known about the effect of the geometry on the potency of the induced immune response. The aim of this study was to develop a computational model to predict the optimal design of the microneedles and their arrangement within an array. The three-dimensional finite element model described the diffusion and kinetics in the skin following antigen delivery with a microneedle array. The results revealed an optimum distance between microneedles based on the number of activated antigen presenting cells, which was assumed to be related to the induced immune response. This optimum depends on the delivered dose. In addition, the microneedle length affects the number of cells that will be involved in either the epidermis or dermis. By contrast, the radius at the base of the microneedle and release rate only minimally influenced the number of cells that were activated. The model revealed the importance of various geometric parameters to enhance the induced immune response. The model can be developed further to determine the optimal design of an array by adjusting its various parameters to a specific situation.     

Terrestrial organic carbon storage in a British moorland

Accurate estimates for the size of terrestrial organic carbon (C) stores are needed to determine their importance in regulating atmospheric CO₂ concentrations. The C stored in vegetation and soil components of a British moorland was evaluated in order to: (i) investigate the importance of these ecosystems for C storage and (ii) test the accuracy of the United Kingdom's terrestrial C inventory. The area of vegetation and soil types was determined using existing digitized maps and a Geographical Information System (GIS). The importance of evaluating C storage using 2D area projections, as opposed to true surface areas, was investigated and found to be largely insignificant. Vegetation C storage was estimated from published results of productivity studies at the site supplemented by field sampling to evaluate soil C storage. Vegetation was found to be much less important for C storage than soil, with peat soils, particularly Blanket bog, containing the greatest amounts of C. Whilst the total amount of C in vegetation was similar to the UK national C inventory's estimate for the same area, the national inventory estimate for soil C was over three times higher than the value derived in the current study. Because the UK's C inventory can be considered relatively accurate compared to many others, the results imply that current estimates for soil C storage, at national and global scales, should be treated with caution.     

基于带宽优选地理加权回归模型的深圳市植被碳储量反演

植被碳储量估测是自然资源监测的重要内容,遥感技术结合地面样地进行反演可以获得区域范围内植被碳储量的空间连续分布,弥补了传统人工抽样调查估测的不足。然而,现有的参数和非参数遥感估测模型大多忽略了样地数据的变异与空间自相关关系。研究以Landsat 8 OLI影像为数据源提取遥感变量,结合植被碳储量实测调查数据,利用最小信息准则(AICc)、最大空间自相关距离(MSAD)和交叉验证(CV)分别确定最优带宽,组合Gaussian、Bi-square和Exponential核函数构建地理加权回归(GWR)模型估算深圳市植被碳储量,并与多元线性回归(MLR)进行比较,选择最优模型绘制深圳市植被碳储量空间分布图。研究结果表明,GWR模型整体精度优于MLR模型,GWR模型的决定系数(R~2)均高于MLR模型,且均方根误差(RMSE)和平均绝对误差(MAE)显著降低。带宽和核函数的选择对GWR模型估测结果产生了显著影响。以CV确定带宽、Exponential为核函数组合构建的GWR模型效果最佳,其R~2为0.697,RMSE为10.437 Mg C/hm~2,相比其它模型精度上升了13.87%—32....     

Statistical approach in search for optimal signal in simple olfactory neuronal models

Several models (concentration detectors and a flux detector) for coding of odor intensity in olfactory sensory neurons are investigated. Behavior of the system is described by different stochastic processes of binding the odorant molecules to the receptors and their activation. Characteristics how well the odorant concentration can be estimated from the knowledge of response, the number of activated neurons, are studied. The approach is based on the Fisher information and analogous measures. These measures of optimality are computed and applied to locate the odorant concentration which is most suitable for coding. The results are compared with the classical deterministic approach which judges the optimal odorant concentration via steepness of the input-output function.     

1997-2006年中国城市建成区有机碳储量的估算

随着城市区域碳排放的增加,城市碳循环在全球碳循环中的地位越来越重要,而城市碳排放和碳储量的估算是城市碳循环研究的基础.本研究利用统计资料,参考国内外相关研究成果,对1997-2006年中国城市建成区有机碳储量进行估算.结果表明:1997-2006年,中国城市建成区总有机碳储量呈上升趋势,由0.13 ～0.19 Pg C(平均值为0.16 Pg C)增加到0.28 ～0.41 Pg C(平均值为0.34 Pg C);建成区有机碳密度由9.86 ～ 14.03 kg C·m-2 (平均值为11.95 kg C·m-2)增加到10.54～15.54 kg C·m-2(平均值为13.04 kg C·m-2).建成区的有机碳主要储存在土壤中,其次是建筑物和绿地,居民有机体的碳储量可忽略不计.1997和2006年,土壤、建筑物、绿地和居民有机体在总碳库中的比例分别为78％、12％、9％、1％和73％、16％、10％、1％.     

Need for relevant timescales when crediting temporary carbon storage

Purpose

Earth faces an urgent need for climate change mitigation, and carbon storage is discussed as an option. Approaches for assessing the benefit of temporary carbon storage in relation to carbon footprinting exist, but many are based on a 100-year accounting period, disregarding impacts after this time. The aim of this paper is to assess the consequences of using such approaches that disregard the long timescale on which complete removal of atmospheric CO₂ occurs. Based on these findings, an assessment is made on what are relevant timescales to consider when including the value of temporary carbon storage in carbon footprinting.

Methods

Implications of using a 100-year accounting period is evaluated via a literature review study of the global carbon cycle, as well as by analysing the crediting approaches that are exemplified by the PAS 2050 scheme for crediting temporary carbon storage.

Results and discussion

The global carbon cycle shows timescales of thousands of years for the transport of carbon from the atmosphere to pools beyond the near-surface layers of the Earth, from where it will not readily be re-emitted as a response to change in near-surface conditions. Compared to such timescales, the use of the 100-year accounting period appears hard to justify. We illustrate how the use of the 100-year accounting period can cause long-term global warming impacts to be hidden by short-term storage solutions that may not offer real long-term climate change mitigation. Obtaining long-term climatic benefits is considered to require storage of carbon for at least thousand years. However, it has been proposed that there may exist tipping points for the atmospheric CO₂ concentration beyond which irreversible climate changes occur. To reduce the risk of passing such tipping points, fast mitigation of the rise in atmospheric greenhouse gas concentration is required and in this perspective, shorter storage times may still provide climatic benefits.

Conclusions

Both short- and long-term perspectives should be considered when crediting temporary carbon storage, addressing both acute effects on the climate and the long-term climate change. It is however essential to distinguish between short- and long-term mitigation potential by treating them separately and avoid that short-term mitigation is used to counterbalance long-term climate change impacts from burning of fossil fuels.     

Biodiversity and ecosystem productivity: implications for carbon storage

Recent experiments have found that Net Primary Productivity (NPP) can often be a positive saturating function of plant species and functional diversity. These findings raised the possibility that more diverse ecosystems might store more carbon as a result of increased photosynthetic inputs. However, carbon inputs will not only remain in plant biomass, but will be translocated to the soil via root exudation, fine root turnover, and litter fall. Thus, we must consider not just plant productivity (NPP), but also net productivity of the whole ecosystem (NEP), which itself measures net carbon storage. We currently know little about how plant diversity could influence soil processes that return carbon back to the atmosphere, such as heterotrophic respiration and decomposition of organic matter. Nevertheless, it is clear that any effects on such processes could make NPP a poor predictor of whole-ecosystem productivity, and potentially the ability of the ecosystem to store carbon. We examine the range of mechanisms by which plant diversity could influence net ecosystem productivity, incorporating processes involved with carbon uptake (productivity), loss (autotrophic and heterotrophic respiration), and residence time within the system (decomposition rate). Understanding the relationship between plant diversity and ecosystem carbon dynamics must be made a research priority if we wish to provide information relevant to global carbon policy decisions. This goal is entirely feasible if we utilize some basic methods for measuring the major fluxes of carbon into and out of the ecosystem.     

1997-2006年中国城市建成区有机碳储量的估算

随着城市区域碳排放的增加,城市碳循环在全球碳循环中的地位越来越重要,而城市碳排放和碳储量的估算是城市碳循环研究的基础.本研究利用统计资料,参考国内外相关研究成果,对1997-2006年中国城市建成区有机碳储量进行估算.结果表明： 1997-2006年,中国城市建成区总有机碳储量呈上升趋势,由0.13～0.19 Pg C（平均值为0.16 Pg C）增加到0.28～0.41 Pg C（平均值为0.34 Pg C）;建成区有机碳密度由9.86～14.03 kg C·m^-2（平均值为11.95 kg C·m^-2）增加到10.54～15.54 kg C·m^-2（平均值为13.04 kg C·m^-2）.建成区的有机碳主要储存在土壤中,其次是建筑物和绿地,居民有机体的碳储量可忽略不计.1997和2006年,土壤、建筑物、绿地和居民有机体在总碳库中的比例分别为78%、12%、9%、1%和73%、16%、10%、1%.     

Enhancing soil carbon storage for carbon remediation: potential contributions and constraints by microbes

Terrestrial carbon sequestration represents an important option for partially mitigating anthropogenic CO(2) emissions. Evidence suggests that terrestrial ecosystems can be managed for carbon sequestration, but it is not certain to what extent the microbes within them can be manipulated. Challenges include identifying which specific microbes and mechanisms contribute to sequestered carbon; understanding how microbial communities respond over large spatial and long temporal scales to crucial environmental variables; and developing management strategies suitable for large spatial and long temporal scales. The growing recognition that microbes produce proteins that limit organic matter degradation suggests targets for basic research. Directly manipulating microbes to sequester CO(2) through other processes such as mineral formation offers intriguing alternatives that merit further attention, but at present the prospects for practical implementation appear remote.