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Life-cycle analysis of greenhouse gas emissions from renewable jet fuel production

Background: The introduction of renewable jet fuel (RJF) is considered an important emission mitigation measure for the aviation industry. This study compares the well-to-wake (WtWa) greenhouse gas (GHG) emission performance of multiple RJF conversion pathways and explores the impact of different co-product allocation methods. The insights obtained in this study are of particular importance if RJF is included as an emission mitigation instrument in the global Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA). Results: Fischer–Tropsch pathways yield the highest GHG emission reduction compared to fossil jet fuel (86–104%) of the pathways in scope, followed by Hydrothermal Liquefaction (77–80%) and sugarcane- (71–75%) and corn stover-based Alcohol-to-Jet (60–75%). Feedstock cultivation, hydrogen and conversion inputs were shown to be major contributors to the overall WtWa GHG emission performance. The choice of allocation method mainly affects pathways yielding high shares of co-products or producing co-products which effectively displace carbon intensive products (e.g., electricity). Conclusions: Renewable jet fuel can contribute to significant reduction of aviation-related GHG emissions, provided the right feedstock and conversion technology are used. The GHG emission performance of RJF may be further improved by using sustainable hydrogen sources or applying carbon capture and storage. Based on the character and impact of different co-product allocation methods, we recommend using energy and economic allocation (for non-energy co-products) at a global level, as it leverages the universal character of energy allocation while adequately valuing non-energy co-products.

Bioenergy↗

Adding tetrahydrofuran to dilute acid pretreatment provides new insights into substrate changes that greatly enhance biomass deconstruction by Clostridium thermocellum and fungal enzymes

Consolidated bioprocessing (CBP) by anaerobes, such as Clostridium thermocellum, which combine enzyme production, hydrolysis, and fermentation are promising alternatives to historical economic challenges of using fungal enzymes for biological conversion of lignocellulosic biomass. However, limited research has integrated CBP with real pretreated biomass, and understanding how pretreatment impacts subsequent deconstruction by CBP vs. fungal enzymes can provide valuable insights into CBP and suggest other novel biomass deconstruction strategies. This study focused on determining the effect of pretreatment by dilute sulfuric acid alone (DA) and with tetrahydrofuran (THF) addition via co-solvent-enhanced lignocellulosic fractionation (CELF) on deconstruction of corn stover and Populus with much different recalcitrance by C. thermocellum vs. fungal enzymes and changes in pretreated biomass related to these differences.

09 BIOMASS FUELS↗

Correlation of structure, function and protein dynamics in GH7 cellobiohydrolases from Trichoderma atroviride, T. reesei and T. harzianum

The ascomycete fungus Trichoderma reesei is the predominant source of enzymes for industrial conversion of lignocellulose. Its glycoside hydrolase family 7 cellobiohydrolase (GH7 CBH) TreCel7A constitutes nearly half of the enzyme cocktail by weight and is the major workhorse in the cellulose hydrolysis process. The orthologs from Trichoderma atroviride (TatCel7A) and Trichoderma harzianum (ThaCel7A) show high sequence identity with TreCel7A, ~ 80%, and represent naturally evolved combinations of cellulose-binding tunnel-enclosing loop motifs, which have been suggested to influence intrinsic cellobiohydrolase properties, such as endo-initiation, processivity, and off-rate. The TatCel7A, ThaCel7A, and TreCel7A enzymes were characterized for comparison of function. The catalytic domain of TatCel7A was crystallized, and two structures were determined: without ligand and with thio-cellotriose in the active site. Initial hydrolysis of bacterial cellulose was faster with TatCel7A than either ThaCel7A or TreCel7A. In synergistic saccharification of pretreated corn stover, both TatCel7A and ThaCel7A were more efficient than TreCel7A, although TatCel7A was more sensitive to thermal inactivation. Structural analyses and molecular dynamics (MD) simulations were performed to elucidate important structure/function correlations. Moreover, reverse conservation analysis (RCA) of sequence diversity revealed divergent regions of interest located outside the cellulose-binding tunnel of Trichoderma spp. GH7 CBHs. We hypothesize that the combination of loop motifs is the main determinant for the observed differences in Cel7A activity on cellulosic substrates. Fine-tuning of the loop flexibility appears to be an important evolutionary target in Trichoderma spp., a conclusion supported by the RCA data. Our results indicate that, for industrial use, it would be beneficial to combine loop motifs from TatCel7A with the thermostability features of TreCel7A. Furthermore, one region implicated in thermal unfolding is suggested as a primary target for protein engineering.

09 BIOMASS FUELS↗

Comparison of methodologies used to determine aromatic lignin unit ratios in lignocellulosic biomass

Abstract Background Multiple analytical methods have been developed to determine the ratios of aromatic lignin units, particularly the syringyl/guaiacyl (S/G) ratio, of lignin biopolymers in plant cell walls. Chemical degradation methods such as thioacidolysis produce aromatic lignin units that are released from certain linkages and may induce chemical changes rendering it difficult to distinguish and determine the source of specific aromatic lignin units released, as is the case with nitrobenzene oxidation methodology. NMR methods provide powerful tools used to analyze cell walls for lignin composition and linkage information. Pyrolysis-mass spectrometry methods are also widely used, particularly as high-throughput methodologies. However, the different techniques used to analyze aromatic lignin unit ratios frequently yield different results within and across particular studies, making it difficult to interpret and compare results. This also makes it difficult to obtain meaningful insights relating these measurements to other characteristics of plant cell walls that may impact biomass sustainability and conversion metrics for the production of bio-derived fuels and chemicals. Results The authors compared the S/G lignin unit ratios obtained from thioacidolysis, pyrolysis-molecular beam mass spectrometry (py-MBMS), HSQC liquid-state NMR and solid-state (ss) NMR methodologies of pine, several genotypes of poplar, and corn stover biomass. An underutilized approach to deconvolute ssNMR spectra was implemented to derive S/G ratios. The S/G ratios obtained for the samples did not agree across the different methods, but trends were similar with the most agreement among the py-MBMS, HSQC NMR and deconvoluted ssNMR methods. The relationship between S/G, thioacidolysis yields, and linkage analysis determined by HSQC is also addressed. Conclusions This work demonstrates that different methods using chemical, thermal, and non-destructive NMR techniques to determine native lignin S/G ratios in plant cell walls may yield different results depending on species and linkage abundances. Spectral deconvolution can be applied to many hardwoods with lignin dominated by S and G units, but the results may not be reliable for some woody and grassy species of more diverse lignin composition. HSQC may be a better method for analyzing lignin in those species given the wealth of information provided on additional aromatic moieties and bond linkages. Additionally, trends or correlations in lignin characteristics such as S/G ratios and lignin linkages within the same species such as poplar may not necessarily exhibit the same trends or correlations made across different biomass types. Careful consideration is required when choosing a method to measure S/G ratios and the benefits and shortcomings of each method discussed here are summarized.

09 BIOMASS FUELS↗

Cellulosic biofuel production using emulsified simultaneous saccharification and fermentation (eSSF) with conventional and thermotolerant yeasts

Abstract Background Future expansion of corn-derived ethanol raises concerns of sustainability and competition with the food industry. Therefore, cellulosic biofuels derived from agricultural waste and dedicated energy crops are necessary. To date, slow and incomplete saccharification as well as high enzyme costs have hindered the economic viability of cellulosic biofuels, and while approaches like simultaneous saccharification and fermentation (SSF) and the use of thermotolerant microorganisms can enhance production, further improvements are needed. Cellulosic emulsions have been shown to enhance saccharification by increasing enzyme contact with cellulose fibers. In this study, we use these emulsions to develop an emulsified SSF (eSSF) process for rapid and efficient cellulosic biofuel production and make a direct three-way comparison of ethanol production between S. cerevisiae , O. polymorpha , and K. marxianus in glucose and cellulosic media at different temperatures. Results In this work, we show that cellulosic emulsions hydrolyze rapidly at temperatures tolerable to yeast, reaching up to 40-fold higher conversion in the first hour compared to microcrystalline cellulose (MCC). To evaluate suitable conditions for the eSSF process, we explored the upper temperature limits for the thermotolerant yeasts Kluyveromyces marxianus and Ogataea polymorpha , as well as Saccharomyces cerevisiae , and observed robust fermentation at up to 46, 50, and 42 °C for each yeast, respectively. We show that the eSSF process reaches high ethanol titers in short processing times, and produces close to theoretical yields at temperatures as low as 30 °C. Finally, we demonstrate the transferability of the eSSF technology to other products by producing the advanced biofuel isobutanol in a light-controlled eSSF using optogenetic regulators, resulting in up to fourfold higher titers relative to MCC SSF. Conclusions The eSSF process addresses the main challenges of cellulosic biofuel production by increasing saccharification rate at temperatures tolerable to yeast. The rapid hydrolysis of these emulsions at low temperatures permits fermentation using non-thermotolerant yeasts, short processing times, low enzyme loads, and makes it possible to extend the process to chemicals other than ethanol, such as isobutanol. This transferability establishes the eSSF process as a platform for the sustainable production of biofuels and chemicals as a whole.

09 BIOMASS FUELS↗

Saccharification of newspaper waste after ammonia fiber expansion or extractive ammonia

Here, the lignocellulosic fractions of municipal solid waste (MSW) can be used as renewable resources due to the widespread availability, predictable and low pricing and suitability for most conversion technologies. In particular, after the typical paper recycling loop, the newspaper waste (NW) could be further valorized as feedstock in biorefinering industry since it still contains up to 70 % polysaccharides. In this study, two different physicochemical methods— ammonia fiber expansion (AFEX) and extractive ammonia (EA) were tested for the pretraetment of NW. Furthermore, based on the previously demonstrated ability of the recombinant enzymes endocellulase rCelStrep, α-larabinofuranosidase rPoAbf and its evolved variant rPoAbf F435Y/Y446F to improve the saccharification of different lignocellulosic pretreated biomasses (such as corn stover and Arundo donax ), in this study these enzymes were tested for the hydrolysis of pretreated NW, with the aim of valorizing the lignocellulosic fractions of the MSW. In particular, a mixture of purified enzymes containing cellulases, xylanases and accessory hemicellulases, was chosen as reference mix and rCelStrep and rPoAbf or its variant were replaced to EGI and Larb. The results showed that these enzymatic mixes are not suitable for the hydrolysis of NW after AFEX or EA pretreatment. On the other hand, when the enzymes rCelStrep, rPoAbf and rPoAbf F435Y/Y446F were tested for their effect in hydrolysis of pretreated NW by addition to a commercial enzyme mixture, it was shown that the total polysaccharides conversion yield reached 37.32 % for AFEX pretreated NW by adding rPoAbf to the mix whilst the maximum sugars conversion yield for EA pretreated NW was achieved 40.80 % by adding rCelStrep. The maximum glucan conversion yield obtained (45.61 % for EA pretreated NW by adding rCelStrep to the commercial mix) is higher than or comparable to those reported in recent manuscripts adopting hydrolysis conditions similar to those used in this study.

municipal solid waste↗

Supranutrition of microalgal docosahexaenoic acid and calcidiol improved growth performance, tissue lipid profiles, and tibia characteristics of broiler chickens

Abstract Background Docosahexaenoic acid (DHA) and calcidiol could be enriched in chicken for improving public nutrition and health. It remains unclear if supranutritional levels of DHA and calcidiol impair growth performance or metabolism of broiler chickens. This study was to determine singular and combined effects of high levels of supplemental DHA-rich microalgal biomass or oil and calcidiol on growth performance, concentrations of triglycerides, cholesterol, and nonesterfied fatty acids in plasma, liver, breast, and thigh, and biophysical properties of tibia. Methods In Exp. 1, 144 day-old Cornish chicks were divided into 4 groups (6 cages/treatment, 6 birds/cage), and were fed a corn-soybean meal basal diet (BD), BD + 10,000 IU calcidiol/kg (BD + Cal), BD + 1% DHA-rich Aurantiochytrium (1.2 g DHA/kg; BD + DHA), and BD + Cal + DHA for 6 weeks. In Exp. 2, 180 day-old chicks were divided into 5 groups, and were fed: BD, BD + DHA (0.33% to 0.66% oil, 1.5 to 3.0 g DHA/kg), BD + DHA + EPA (1.9% to 3.8% eicosapentaenoic acid-rich Nannochloropsis sp. CO18, 0.3 to 0.6 g EPA/kg), BD + DHA + calcidiol (6000 to 12,000 IU/kg diet), and BD + DHA + EPA + Cal for 6 weeks. Results Birds fed BD + Cal diet in Exp. 1 and BD + DHA + EPA diet in Exp. 2 had higher ( P < 0.05) body weight gain (10%–11%) and gain:feed ratio (7%), and lower ( P < 0.05) total cholesterol and triglyceride concentrations in plasma (18%–54%), liver (8%–26%), breast (19%–26%), and thigh (10%–19%), respectively, over the controls. The two diets also improved ( P < 0.05) tibial breaking strength (8%–24%), total bone volume (2%–13%), and (or) bone mineral density (3%–19%) of chickens. Conclusion Supranutrition of dietary calcidiol and DHA alone or together did not produce adverse effects, but led to moderate improvements of growth performance, lipid profiles of plasma and muscle, and bone properties of broiler chickens.

60 APPLIED LIFE SCIENCES↗

Thermo-mechanical characterization of silicone foams

Cellular solids such as elastomeric foams are used in many structural applications to absorb and dissipate energy, due to their light weight (low density) and high energy absorption capability. In this paper we will discuss foams derived from S5370, a silicone foam formulation developed by Dow Corning. In the application presented, the foam is consolidated into a cushion component of constant thickness but variable density. A mechanical material model developed by Lewis (2013), predicts material response, in part, as a function of relative density. To determine the required parameters for this model we have obtained the mechanical response in compression for ambient, cold and hot temperatures. The variable density cushion provided samples sufficient samples so that the effect of sample initial density on the mechanical response could be studied. The mechanical response data showed extreme sensitivity to relative density. We also observed at strains corresponding to 1 MPa a linear relationship between strain and initial density for all temperatures. Samples taken from parts with a history of thermal cycling demonstrated a stiffening response that was a function of temperature, with the trend of more stiffness as temperature increased above ambient. This observation is in agreement with the entropic effects on the thermo-mechanical behavior of silicone polymers. In this study, we present the experimental methods necessary for the development of a material model, the testing protocol, analysis of test data, and a discussion of load (stress) and gap (strain) as a function of sample initial densities and temperatures

36 MATERIALS SCIENCE↗

Simulated Land Allocation, Nitrogen Use, and Nitrogen Loss in the Mississippi Atchafalaya River Basin for Various RFS2 (Renewable Fuel Standard) Policy Scenarios

Total nitrogen leaching rates were calculated over the Mississippi Atchafalaya River Basin (MARB) using an integrated economic-biophysical modeling approach. Land allocation for corn production and total nitrogen application rates were calculated for crop reporting districts using the Biofuel and Environmental Policy Analysis Model (BEPAM) for 5 RFS2 policy scenarios. These were used as input in the Integrated BIosphere Simulator-Agricultural Version (Agro-IBIS) and the Terrestrial Hydrologic Model with Biogeochemistry (THMB) to calculate the nitrogen loss. Land allocation and total nitrogen application simulations were simulated for the period 2016-2030 for 303 crop reporting districts (https://www.nass.usda.gov/Data_and_Statistics/County_Data_Files/Frequently_Asked_Questions/county_list.txt). The final 2030 values are reported here. Both are stored in csv files. Units for land allocation are million ha and nitrogen application are million kg. The nitrogen leaching rates were modeled with a spatial resolution of 5' x 5' using the North American Datum of 1983 projection and stored in NetCDF files. The 30-year average is calculated over the last 30 years of the 45 years being simulated. Leaching rates are calculated in kg-N/ha.

bioenergy crops↗

<i>Finite Element Modeling of Biomass Hopper Flow</i>

The hopper is one of the widely used biomass handling devices that channels the bulk biomass from storage to the subsequent handling systems. Although Jenike's approach has been successfully used for hoppers handling grains and other agricultural produces for decades, designing a hopper, ensuring reliable biomass handling is found to be challenging. This study aims to address this engineering problem with alternative constitutive material models concerning the flow behavior of bulk solids. Finite element modeling is an approach that allows for implementing different material models. Underlying constitutive theories of different material models assist in investigating the mechanical behavior of a particulate system, including the flow characteristics of ground biomass. This study demonstrates hopper flow models of two types of biomass, i.e., ground corn stover and Douglas fir, with the Mohr-Coulomb model, which is based on Jenike's approach, modified Cam-Clay model, and Drucker-Prager/Cap model. The modeling results are compared with hopper flow experiments to highlights the advantages and shortfalls of each constitutive biomass flow model.

09 BIOMASS FUELS↗

Effectiveness of Residue and Tillage Management on Runoff Pollutant Reduction from Agricultural Areas

Highlights No-till and no-till residue systems were effective in reducing runoff particulate and total nutrients but increased dissolved nutrients. Maintaining >30% residue cover reduced most runoff constituents, irrespective of no-till or tillage. No-till-residue prevented runoff nutrient losses and benefitted farm revenue by avoiding tillage. Abstract. Reduced tillage management conservation practices (No-till and Reduced-till) are widely adopted in agriculture; however, understanding their overall effectiveness for water quality protection is challenging. A meta-analysis was conducted to understand and quantify the effectiveness of residue and tillage management on runoff, sediment, and nutrient losses from agricultural fields. Annual runoff and the associated sediment, and nutrient (nitrogen and phosphorus) loads were compiled from 60 peer reviewed research articles published across the United States and Canada. A total of 1575 site-years of data were categorized into tillage (<30% surface cover), no-tillage (<30% surface cover), tillage with residue (>30% surface cover), no-tillage with residue (>30% surface cover), and pasture management. No-tillage, no-tillage-residue, and tillage-residue managements were evaluated for their effectiveness in reducing runoff, nutrients, and sediment loads compared to tillage. Synthesized and surveyed corn yield data were used to evaluate the economic cost effectiveness of no-tillage-residue management with respect to tillage. Across the site years (1968-2019) studied, median runoff depth for no-tillage and no-tillage-residue were 84% and 70% greater than tillage and tillage-residue management, respectively. No-tillage-residue management had up to 86% less sediment losses than tillage systems, on average, for both >30% and <30% surface cover. No-tillage-residue management was most effective, with a positive performance effectiveness of 65% to 90% in controlling sediments, particulate, and total nutrient losses in runoff compared to tillage. Cost effectiveness analysis revealed the benefits of no-tillage-residue management in reducing nutrient loads and increasing net-farm revenue by avoiding tillage operational costs. Except for dissolved phosphorus, no-tillage-residue management cost effectiveness for sediments and nutrient loads ranged from negative $6 to negative $102 per every Mg or kg of load reduction, indicating it had both economic and environmental benefits compared to tillage management. Overall, these results indicate that over the long-term, no-tillage and tillage, combined with greater than 30% residue cover, can effectively reduce sediment and nutrient losses. This work highlights the importance of crop residues on the soil surface to reduce runoff losses, even in no-tillage systems. Keywords: Conservation tillage, No-tillage, Residue cover, Tillage, Water quality.

Agriculture↗

Epoxy Coating of Biofiber: An Effective Modifier of Biofiber Physical and Flow Properties for Improved Tensile Behavior of Biofiber-Reinforced Biocomposite

Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber‘s characteristics and biocomposite‘s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young‘s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties.

36 MATERIALS SCIENCE↗

A Simple and Versatile 2-Dimensional Platform to Study Plant Germination and Growth under Controlled Humidity

We describe a simple, inexpensive, but remarkably versatile and controlled growth environment for the observation of plant germination and seedling root growth on a flat, horizontal surface over periods of weeks. The setup provides to each plant a controlled humidity (between 56% and 91% RH), and contact with both nutrients and atmosphere. The flat and horizontal geometry of the surface supporting the roots eliminates the gravitropic bias on their development and facilitates the imaging of the entire root system. Experiments can be setup under sterile conditions and then transferred to a non-sterile environment. The system can be assembled in 1-2 minutes, costs approximately 8.78$\$$ per plant, is almost entirely reusable (0.43$\$$ per experiment in disposables), and is easily scalable to a variety of plants. We demonstrate the performance of the system by germinating, growing, and imaging Wheat (Triticum aestivum), Corn (Zea mays), and Wisconsin Fast Plants (Brassica rapa). Germination rates were close to those expected for optimal conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancement of Synthetic Trichoderma -Based Enzyme Mixtures for Biomass Conversion with an Alternative Family 5 Glycosyl Hydrolase from Sporotrichum thermophile

Enzymatic conversion of lignocellulosic materials to fermentable sugars is a limiting step in the production of biofuels from biomass. We show here that combining enzymes from different microbial sources is one way to identify superior enzymes. Extracts of the thermophilic fungus Sporotrichum thermophile (synonym Myceliophthora thermophila) gave synergistic release of glucose (Glc) and xylose (Xyl) from pretreated corn stover when combined with an 8-component synthetic cocktail of enzymes from Trichoderma reesei. The S. thermophile extracts were fractionated and an enhancing factor identified as endo-β1,4- glucanase (StCel5A or EG2) of subfamily 5 of Glycosyl Hydrolase family 5 (GH5_5). In multi-component optimization experiments using a standard set of enzymes and either StCel5A or the ortholog from T. reesei (TrCel5A), reactions containing StCel5A yielded more Glc and Xyl. In a five-component optimization experiment (i.e., varying four core enzymes and the source of Cel5A), the optimal proportions for TrCel5A vs. StCel5A were similar for Glc yields, but markedly different for Xyl yields. Both enzymes were active on lichenan, glucomannan, and oat β-glucan; however, StCel5A but not TrCel5A was also active on β1,4-mannan, two types of galactomannan, and β1,4-xylan. Phylogenetically, fungal enzymes in GH5_5 sorted into two clades, with StCel5A and TrCel5A belonging to different clades. Structural differences with the potential to account for the differences in performance were deduced based on the known structure of TrCel5A and a homology-based model of StCel5A, including a loop near the active site of TrCel5A and the presence of four additional Trp residues in the active cleft of StCel5A. The results indicate that superior biomass-degrading enzymes can be identified by exploring taxonomic diversity combined with assays in the context of realistic enzyme combinations and realistic substrates. Substrate range may be a key factor contributing to superior performance within GH5_5.

59 BASIC BIOLOGICAL SCIENCES↗

Genome –Scale Reconstruction of Metabolic Networks of Lactobacillus casei ATCC 334 and 12A

Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

59 BASIC BIOLOGICAL SCIENCES↗

Agriculture, bioenergy, and water implications of constrained cereal trade and climate change impacts

International trade increases connections and dependencies between countries, weaving a network of global supply chains. Agricultural commodity trade has implications for crop producers, consumers, crop prices, water and land uses, and other human systems. Interconnections among these systems are not always easy to observe when external impacts penetrate across multiple sectors. To better understand the interactions of non-linear and globally coupled agricultural-bioenergy-water systems under the broader economy, we introduce systematic perturbations in two dimensions, one human (restrictions on agricultural trade) and the other physical (climate impacts on crop yields). We explore these independently and in combination to distinguish the consequences of individual perturbation and interactive effects in long-term projections. We show that most regions experience larger changes in cereal consumption due to cereal import dependency constraints than due to the impacts of climate change on agricultural yields. In the scenario where all regions ensure an import dependency ratio of zero, the global trade of cereals decreases ~50% in 2050 compared to the baseline, with smaller decreases in cereal production and consumption (4%). The changes in trade also impact water and bioenergy: global irrigation water consumption increases 3% and corn ethanol production decreases 7% in 2050. Climate change results in rising domestic prices and declining consumption of cereal crops in general, while the import dependency constraint exacerbates the situation in regions which import more cereals in the baseline. The individual and interactive effects of trade perturbations and climate change vary greatly across regions, which are also affected by the regional ability to increase agricultural production through intensification or extensification.

54 ENVIRONMENTAL SCIENCES↗

Materials Data on CsMg12Al25Si29O108 by Materials Project

CsMg12Al25Si29O108 crystallizes in the triclinic P1 space group. The structure is three-dimensional. Cs is bonded in a 12-coordinate geometry to twelve O atoms. There are a spread of Cs–O bond distances ranging from 3.51–3.72 Å. There are twelve inequivalent Mg sites. In the first Mg site, Mg is bonded to six O atoms to form MgO6 octahedra that share corners with six SiO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.06–2.22 Å. In the second Mg site, Mg is bonded to six O atoms to form MgO6 octahedra that share a cornercorner with one AlO4 tetrahedra, corners with five SiO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.09–2.24 Å. In the third Mg site, Mg is bonded to six O atoms to form MgO6 octahedra that share corners with six SiO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.05–2.22 Å. In the fourth Mg site, Mg is bonded to six O atoms to form MgO6 octahedra that share a cornercorner with one AlO4 tetrahedra, corners with five SiO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.09–2.24 Å. In the fifth Mg site, Mg is bonded to six O atoms to form MgO6 octahedra that share corners with six SiO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.06–2.22 Å. In the sixth Mg site, Mg is bonded to six O atoms to form MgO6 octahedra that share corners with six SiO4 tetrahedra and edges with three AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.10–2.16 Å. In the seventh Mg site, Mg is bonded to six O atoms to form distorted MgO6 octahedra that share corners with two SiO4 tetrahedra, corners with four AlO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.01–2.22 Å. In the eighth Mg site, Mg is bonded to six O atoms to form distorted MgO6 octahedra that share corners with two SiO4 tetrahedra, corners with four AlO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.00–2.23 Å. In the ninth Mg site, Mg is bonded to six O atoms to form distorted MgO6 octahedra that share corners with three AlO4 tetrahedra, corners with three SiO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.01–2.20 Å. In the tenth Mg site, Mg is bonded to six O atoms to form distorted MgO6 octahedra that share corners with three AlO4 tetrahedra, corners with three SiO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.01–2.20 Å. In the eleventh Mg site, Mg is bonded to six O atoms to form distorted MgO6 octahedra that share corners with two SiO4 tetrahedra, corners with four AlO4 tetrahedra, an edgeedge with one SiO4 tetrahedra, and edges with two AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.00–2.23 Å. In the twelfth Mg site, Mg is bonded to six O atoms to form distorted MgO6 octahedra that share corners with two SiO4 tetrahedra, corners with four AlO4 tetrahedra, and edges with three AlO4 tetrahedra. There are a spread of Mg–O bond distances ranging from 2.03–2.29 Å. There are twenty-five inequivalent Al sites. In the first Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra and corners with four SiO4 tetrahedra. The corner-sharing octahedral tilt angles are 49°. There is two shorter (1.73 Å) and two longer (1.81 Å) Al–O bond length. In the second Al site, Al is bonded to four O atoms to form distorted AlO4 tetrahedra that share corners with two AlO4 tetrahedra, corners with two SiO4 tetrahedra, and edges with two MgO6 octahedra. There is two shorter (1.74 Å) and two longer (1.82 Å) Al–O bond length. In the third Al site, Al is bonded to four O atoms to form distorted AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. In the fourth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with four SiO4 tetrahedra and edges with two MgO6 octahedra. There is one shorter (1.76 Å) and three longer (1.77 Å) Al–O bond length. In the fifth Al site, Al is bonded to four O atoms to form distorted AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.74–1.79 Å. In the sixth Al site, Al is bonded to four O atoms to form distorted AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. In the seventh Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with four SiO4 tetrahedra and edges with two MgO6 octahedra. There is one shorter (1.76 Å) and three longer (1.77 Å) Al–O bond length. In the eighth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. In the ninth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra, corners with two AlO4 tetrahedra, and corners with two SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 43–44°. There are a spread of Al–O bond distances ranging from 1.73–1.76 Å. In the tenth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra, corners with two AlO4 tetrahedra, and corners with two SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 45–46°. There are a spread of Al–O bond distances ranging from 1.74–1.76 Å. In the eleventh Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.74–1.79 Å. In the twelfth Al site, Al is bonded to four O atoms to form distorted AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.79 Å. In the thirteenth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. In the fourteenth Al site, Al is bonded to four O atoms to form distorted AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.79 Å. In the fifteenth Al site, Al is bonded to four O atoms to form distorted AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. In the sixteenth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share a cornercorner with one AlO4 tetrahedra, corners with three SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. In the seventeenth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra, a cornercorner with one AlO4 tetrahedra, and corners with three SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 43–52°. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. In the eighteenth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra and corners with four SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 48–50°. There is two shorter (1.72 Å) and two longer (1.79 Å) Al–O bond length. In the nineteenth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra and corners with four SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 48–50°. There are a spread of Al–O bond distances ranging from 1.72–1.79 Å. In the twentieth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra, corners with two AlO4 tetrahedra, and corners with two SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 45–47°. There are a spread of Al–O bond distances ranging from 1.74–1.76 Å. In the twenty-first Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra, corners with two AlO4 tetrahedra, and corners with two SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 43–44°. There are a spread of Al–O bond distances ranging from 1.73–1.76 Å. In the twenty-second Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra, corners with two AlO4 tetrahedra, and corners with two SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 43–44°. There are a spread of Al–O bond distances ranging from 1.73–1.76 Å. In the twenty-third Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra and corners with four SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 50–51°. There are a spread of Al–O bond distances ranging from 1.71–1.79 Å. In the twenty-fourth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra and corners with four SiO4 tetrahedra. The corner-sharing octahedral tilt angles are 50°. There are a spread of Al–O bond distances ranging from 1.72–1.79 Å. In the twenty-fifth Al site, Al is bonded to four O atoms to form AlO4 tetrahedra that share corners with two MgO6 octahedra, a cornercorner with one AlO4 tetrahedra, and corners with three SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 43–52°. There are a spread of Al–O bond distances ranging from 1.73–1.78 Å. There are twenty-nine inequivalent Si sites. In the first Si site, Si is bonded to four O atoms to form SiO4 tetrahedra that share corners with two MgO6 octahedra, a cornercorner with one AlO4 tetrahedra, and corners with three SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 47–48°. There are a spread of Si–O bond distances ranging from 1.57–1.70 Å. In the second Si site, Si is bonded to four O atoms to form SiO4 tetrahedra that share corners with two MgO6 octahedra, corners with two AlO4 tetrahedra, and corners with two SiO4 tetrahedra. The corner-sharing octahedra tilt angles range from 41–49°. There are a spread of Si–O bond distances ranging from 1.59–1.71 Å. In the third Si site, Si is bonded to four O atoms to form SiO4 tetrahedra that share corners with two AlO4 tetrahedra, corners with two SiO4 tetrahedra, and edges with two MgO6 octahedra. There are a spread of Si–O bond distances ranging from 1.62–1.70 Å. In the fourth Si site, Si is bonded to four O atoms to form SiO4 tetrahedra that share a corn

36 MATERIALS SCIENCE↗

Materials Data on Li15(NiO2)14 by Materials Project

Li15(NiO2)14 crystallizes in the monoclinic Cm space group. The structure is three-dimensional. there are fifteen inequivalent Li1+ sites. In the first Li1+ site, Li1+ is bonded in a 4-coordinate geometry to four O2- atoms. There are a spread of Li–O bond distances ranging from 1.80–2.07 Å. In the second Li1+ site, Li1+ is bonded in a 4-coordinate geometry to one Ni+2.93+ and four O2- atoms. The Li–Ni bond length is 2.19 Å. There are a spread of Li–O bond distances ranging from 1.79–1.95 Å. In the third Li1+ site, Li1+ is bonded in a 3-coordinate geometry to six O2- atoms. There are a spread of Li–O bond distances ranging from 1.93–2.46 Å. In the fourth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with five NiO6 octahedra, edges with four LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 6–7°. There are a spread of Li–O bond distances ranging from 2.02–2.21 Å. In the fifth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–7°. There are a spread of Li–O bond distances ranging from 2.11–2.17 Å. In the sixth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–7°. There are a spread of Li–O bond distances ranging from 2.08–2.16 Å. In the seventh Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Li–O bond distances ranging from 2.13–2.17 Å. In the eighth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Li–O bond distances ranging from 2.13–2.17 Å. In the ninth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Li–O bond distances ranging from 2.13–2.17 Å. In the tenth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Li–O bond distances ranging from 2.12–2.17 Å. In the eleventh Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Li–O bond distances ranging from 2.12–2.17 Å. In the twelfth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–7°. There are a spread of Li–O bond distances ranging from 2.11–2.16 Å. In the thirteenth Li1+ site, Li1+ is bonded to six O2- atoms to form LiO6 octahedra that share corners with six NiO6 octahedra, edges with four LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–9°. There are a spread of Li–O bond distances ranging from 2.06–2.18 Å. In the fourteenth Li1+ site, Li1+ is bonded in a distorted rectangular see-saw-like geometry to four O2- atoms. There are a spread of Li–O bond distances ranging from 1.74–2.02 Å. In the fifteenth Li1+ site, Li1+ is bonded in a 6-coordinate geometry to six O2- atoms. There are a spread of Li–O bond distances ranging from 1.96–2.39 Å. There are fourteen inequivalent Ni+2.93+ sites. In the first Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form distorted edge-sharing NiO6 octahedra. There are a spread of Ni–O bond distances ranging from 1.96–2.11 Å. In the second Ni+2.93+ site, Ni+2.93+ is bonded in a 6-coordinate geometry to one Li1+ and six O2- atoms. There are a spread of Ni–O bond distances ranging from 1.96–2.16 Å. In the third Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with three LiO6 octahedra, edges with three equivalent LiO6 octahedra, and edges with four NiO6 octahedra. The corner-sharing octahedral tilt angles are 6°. There are a spread of Ni–O bond distances ranging from 1.88–2.06 Å. In the fourth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with five LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–7°. There are a spread of Ni–O bond distances ranging from 1.87–2.05 Å. In the fifth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with six LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Ni–O bond distances ranging from 1.88–2.05 Å. In the sixth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with six LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Ni–O bond distances ranging from 1.89–2.05 Å. In the seventh Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with six LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There is two shorter (1.91 Å) and four longer (2.05 Å) Ni–O bond length. In the eighth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with six LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There is two shorter (1.90 Å) and four longer (2.05 Å) Ni–O bond length. In the ninth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with six LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–7°. There is two shorter (1.91 Å) and four longer (2.05 Å) Ni–O bond length. In the tenth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with six LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–7°. There is two shorter (1.90 Å) and four longer (2.05 Å) Ni–O bond length. In the eleventh Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with six LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–7°. There are a spread of Ni–O bond distances ranging from 1.90–2.05 Å. In the twelfth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with five LiO6 octahedra, edges with six LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 4–8°. There are a spread of Ni–O bond distances ranging from 1.89–2.05 Å. In the thirteenth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form NiO6 octahedra that share corners with three LiO6 octahedra, edges with three equivalent LiO6 octahedra, and edges with six NiO6 octahedra. The corner-sharing octahedra tilt angles range from 5–6°. There are a spread of Ni–O bond distances ranging from 1.90–2.05 Å. In the fourteenth Ni+2.93+ site, Ni+2.93+ is bonded to six O2- atoms to form distorted NiO6 octahedra that share a cornercorner with one LiO6 octahedra and edges with six NiO6 octahedra. The corner-sharing octahedral tilt angles are 9°. There are a spread of Ni–O bond distances ranging from 1.88–2.10 Å. There are twenty-eight inequivalent O2- sites. In the first O2- site, O2- is bonded in a 6-coordinate geometry to three Li1+ and three Ni+2.93+ atoms. In the second O2- site, O2- is bonded in a 6-coordinate geometry to three Li1+ and three Ni+2.93+ atoms. In the third O2- site, O2- is bonded in a 5-coordinate geometry to two Li1+ and three Ni+2.93+ atoms. In the fourth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 3°. In the fifth O2- site, O2- is bonded in a 7-coordinate geometry to four Li1+ and three Ni+2.93+ atoms. In the sixth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedra tilt angles range from 0–2°. In the seventh O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedra tilt angles range from 0–3°. In the eighth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the ninth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedra tilt angles range from 0–3°. In the tenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the eleventh O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the twelfth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the thirteenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the fourteenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the fifteenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the sixteenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the seventeenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the eighteenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the nineteenth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corner-sharing octahedral tilt angles are 0°. In the twentieth O2- site, O2- is bonded to three Li1+ and three Ni+2.93+ atoms to form a mixture of edge and corner-sharing OLi3Ni3 octahedra. The corn

36 MATERIALS SCIENCE↗