Aqueous tin (Sn) metal batteries have attracted growing attention for energy storage; however, the drastic Sn2+ hydrolysis reaction has significantly hindered their development. Currently, strong alkaline and acidic solutions prevail as the leading method to suppress hydrolysis and stabilize Sn2+ electrolytes. Nevertheless, this approach incurs critical issues, including the self-corrosion of Sn metal, parasitic hydrogen evolution, and inferior efficiency under harsh conditions. Herein, we rationally designed an inexpensive and moderately concentrated electrolyte of 0.2 m SnSO4 + 5 m (NH4)(2)SO4, which overcomes the hydrolysis challenge by strengthening H2O molecules and regulating Sn2+/H2O interactions. Importantly, our electrolyte features a mild pH environment (pH = 3.2) and outperforms the aggressive alkaline (pH > 14) and acidic (pH<0) electrolytes. Consequently, exceptional electrode/electrolyte compatibility is achieved, leading to high-efficiency Sn plating behavior (99.95% at 1 mA cm(-2)) and robustness against harsh conditions, including exceptionally low currents (0.1 mA cm(-2), 99.8%; 0.01 mA cm(-2), approximate to 98.6%), long storage (1 month, 93.8% retention), and extreme temperatures (-10-+80 degrees C, >98.7%). We also demonstrated high-capacity Sn & Vert;S batteries (approximate to 2300 mAh g(-1), sulfur-based) and long-cycling Sn & Vert;KNiFe(CN)(6) batteries (7,500 cycles). This work offers new insights into advanced Sn2+ electrolytes and Sn plating chemistry for energy storage.
For emerging adults, developing and maintaining close relationships is an important developmental task relevant for well-being. Therefore, it is important to understand and assess relationship self-efficacy (RSE), reflecting one's confidence in maintaining and managing close relationships. Most previous research on RSE has focused on romantic relationships, but developing work suggests similar processes may occur in friendships and other types of relationships, a key conceptual question. This study randomly assigned 654 US emerging adults to complete measures of RSE for either romantic relationships, friendships, or close relationships (generally), and examined associations with other key correlates (general and social self-efficacy, self-esteem, relationship satisfaction). With minor modifications, measurement invariance testing supported partial invariance up to the scalar level, suggesting items had similar meanings across contexts. Correlations with self and relational constructs were similar across RSE types with minor exceptions. Further research is needed to understand how RSE develops and relationships between different types of RSE.
This article argues for the urgent need to reframe oral reading assessments through a lens of linguistic justice by centering Black Language as a sophisticated linguistic system within a decolonizing framework. Despite rhetorical claims of honoring linguistic diversity, assessment practices often demand assimilation to standardized English, perpetuating colonial and deficit-oriented ideologies. Drawing on translanguaging theory as a decolonizing project, the article demonstrates how features of Black Language in oral reading reflect students' active meaning-making and should be recognized as strengths in reading development rather than treated as errors. Through analysis of assessment practices, raciolinguistic ideologies, and historical contexts, I examine the harm caused when Black Language goes unacknowledged and offer concrete pathways for educators to move from deficit-oriented evaluation toward linguistically sustaining practice. The article concludes with five decolonizing paradigm shifts spanning assessment, classroom instruction, multimodal representation, and teacher education, moving educators from policing to sustaining Black Language.
Second-generation bioethanol from food industry lignocellulosic residues offers a promising route toward low-carbon, circular bioenergy systems. However, the reported environmental impacts differ markedly across studies, challenging efforts to assess the true sustainability of these waste-derived bioethanol routes. This review synthesizes current knowledge on the production of bioethanol from key agro-industrial wastes including oil palm empty fruit bunches, sugarcane bagasse, brewers' spent grain, spent coffee grounds, tea waste, citrus residues, and potato peel waste. We outline feedstock characteristics, availability, and prevailing management practices, and map the principal biochemical conversion routes to identify process steps that drive environmental performance. A systematic comparison of life cycle assessments reveals substantial methodological heterogeneity across functional units, system boundaries, allocation procedures, and impact assessment methods. Nonetheless, consistent hotspots emerge, particularly associated with pretreatment severity, enzyme production, thermal energy demand, and co-product handling. The review highlights robust cross-study trends, pinpoints methodological gaps, and proposes recommendations for harmonized LCA practice. By integrating technological and methodological perspectives, this work aims to support the development and policy uptake of sustainable, waste-based bioethanol within circular bioeconomies.
This study examined artificial intelligence (AI) policies in school psychology training programs. Ninety-six faculty members from US school psychology programs completed an online survey regarding AI policies at the institution, college, and program levels and submitted policy documents. Twenty-seven percent of institutions, 6% of colleges, and 23% of programs had established AI policies. Institution-level policies more comprehensively addressed ethical considerations (100%), data privacy (71%), and diversity concerns (67%) compared to program-level policies (88%, 24%, and 24%, respectively). Program-level policies showed significant gaps in monitoring AI impacts (0%), transparency requirements (6%), and equitable access provisions (12%). Findings reveal substantial disparities between institution and program-level AI governance, with program policies inadequately addressing critical areas including data privacy, bias mitigation, and equitable access.
