Crystal Structures, Phase Stabilities, and Hydrogen Storage Properties of Metal Amidoboranes

Metal amidoboranes, M­(NH₂BH₃)_<i>n</i> (M = alkali metal or alkaline-earth metal), are candidates for on-board hydrogen storage materials with high gravimetric capacity, low H₂ release temperature, and the ability to suppress toxic borazine emission. We have used a first-principles density functional theory (DFT) combination with Monte Carlo method to search for crystal structures for a wide array of metal amidoboranes (M = Li, Na, K, Be, Mg, Ca, Sr, and Sc). In cases where the experimental structures are known, the DFT energies of the theoretically predicted LiNH₂BH₃, NaNH₂BH₃, KNH₂BH₃, and Ca­(NH₂BH₃)₂ structures are degenerate with the DFT energies computed for the experimental structures [to within 4 kJ/(mol f.u.)], confirming the accuracy of our approach. On the basis of the decomposition reaction pathway, M­(NH₂BH₃)_<i>n</i> → MH_<i>n</i> + <i>n</i>BN + 2<i>n</i>H₂, we compute the H₂ release reaction enthalpies and show that the stability of metal amidoboranes obeys the following trend: The metal amidoborane becomes more stable (the decomposition reaction becomes less exothermic) as the metal cation becomes more electropositive, that is, as the metal cation goes down in the periodic table along a given column or as the metal moves to the left along a given row. The only exception to this rule is Mg­(NH₂BH₃)₂, which is more stable than Ca­(NH₂BH₃)₂. Introducing vibrational entropy effects does not change this exceptional behavior of Mg amidoborane: the phonon contribution serves to shift all reaction enthalpies down by a roughly constant amount, ∼22 kJ/(mol H₂) at <i>T</i> = 300 K

Table6_The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.DOC

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear.Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics.Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.</p

Table5_The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.DOC

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear.Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics.Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.</p

First-Principles Prediction of Intermediate Products in the Decomposition of Metal Amidoboranes

The nonvolatile products remaining after the thermal decomposition of metal amidoboranes (MAB, M = metal) are amorphous and incompletely characterized, increasing the complexity of devising regeneration strategies for these potential hydrogen storage materials. Utilizing the combined prototype electrostatic ground state search and density-functional theory (PEGS+DFT), we find that potential reaction products ([NHBH₂]⁻, [NBH]⁻, [N₃H₂B₃H₃]⁻, and polymer-M­[NHBH₂] anion groups) in the decomposition of LiAB and CaAB are calculated to be significantly endothermic, in contrast to the experimentally measured nearly thermoneutral values [∼−4 kJ/(mol H₂) in LiAB and 3.5 kJ/(mol H₂) in CaAB], suggesting that there are alternative products formed. The dianion group [NHBHNHBH₃]^2– has recently been suggested to form in the decomposition of a calcium amidoborane complex in solution. In LiAB and CaAB, we use PEGS+DFT to predict intermediate metal–dianion compounds, and the static H₂ release enthalpy is 27.4 and 27.3 kJ/(mol H₂) in LiAB and CaAB, respectively. Introducing vibrational effects by phonon calculations, the enthalpies are shifted down by a roughly constant amount, ∼25 and ∼22 kJ/(mol H₂) at 0 and 300 K. Thus, our theoretical H₂ release enthalpies agree with the experimentally measured nearly thermoneutral data in the decomposition of LiAB and CaAB. This agreement supports the existence of the dianion phases as products in the decomposition of metal amidoboranes. Then, using the dianion compound as an intermediate in the decomposition of MAB, we further study the stability trends of a series of MAB (M = Li, Na, K, Ca)

Table2_The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.DOC

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear.Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics.Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.</p

Table4_The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.DOC

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear.Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics.Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.</p

Table7_The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.DOC

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear.Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics.Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.</p

Table1_The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.DOC

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear.Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics.Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.</p

Table8_The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.DOC

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear.Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics.Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.</p