https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/1914 Editorial líder en ciencia y tecnología, publica revistas y libros académicos. Wed, 24 Jun 2026 22:06:09 GMT 2026-06-24T22:06:09Z https://192.168.1.47:443/xmlui/bitstream/id/4ad49e81-6047-424d-b7f3-eb16fab33ae0/ https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/1914 https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22409 Machine learning for carbon dots: Capabilities, limitations, and the path toward rational design Leilei Zhang; Linquan Gan Carbon dots (CDs), as significant luminescent carbon-based nanomaterials, exhibit broad application potential in sensing, biomedicine, and optoelectronic devices. However, their synthesis processes are highly nonlinear, and their structural heterogeneity is prominent, resulting in a long-standing lack of a decipherable framework for the synthesis-structure-property relationship, which has restricted on-demand design and controllable preparation. In recent years, machine learning (ML) has provided a data-driven paradigm to address this complexity, yet related research still faces challenges such as scattered data, unclear task boundaries, and insufficient model interpretability. This review systematically examines recent key advances in machine learning for CDs research, focusing on three core tasks: property prediction, synthesis and inverse design, and mechanism analysis. It critically analyzes the capabilities and limitations of various models in predicting emission wavelength, photo luminescence quantum yield, and phosphorescence lifetime. By comparing data sources, feature construction, and validation strategies, it points out that many current high-prediction accuracies primarily stem from statistical fitting rather than learning physical causality, particularly facing structural data bottlenecks in red or near-infrared emission and cross-system generalization. Furthermore, from the perspective of CDs application systems, the review systematically evaluates the practical enabling role of machine earning in CDs-related applications such as sensing, biomedicine, optoelectronics, and information encryption, clearly distinguishing between its role as a tool for performance optimization and its function as a key means for rational design of CDs materials. Finally, a future-oriented pathway for machine learning-driven CDs research is proposed: by con structing standardized, high-quality databases, introducing physically constrained and interpretable models, and combining active learning with closed-loop experimental validation, the field can advance from empirical trial- and-error toward a predictive, interpretable, and translatable paradigm of rational design Tue, 23 Jun 2026 00:00:00 GMT https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22409 2026-06-23T00:00:00Z https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22408 Process–Structure–Property Relationships in Low- Phieraya Pulphol; Ying Tang With the rapid advancement of wireless communication from 5G to 6G, a pressing need has emerged for microwave dielectric ceramics with excellent performance at reduced processing temperatures, compatible with low-temperature Co-fired ceramic (LTCC) technology. This review traces historical milestones and highlights modern design strategies for achieving optimum dielectric constant, ultra-low dielectric loss, and near-zero temperature coefficient of resonant frequency. Special emphasis is placed on recent advances in low-temperature densification routes, including sintering aids, intrinsically low-sintering-temperature ceramic families, and novel techniques like the cold sintering process (CSP). This review provides a critical analysis of the performance trade-offs inherent to each strategy, addressing the persistent challenges in achieving ultra-low loss. Furthermore, we highlight the paradigm shift toward a holistic, multifunctional design imperative for 6G systems. Finally, the transformative potential of cross-disciplinary approaches, particularly AI-assisted discovery and computational modeling, is discussed as a key enabler for accelerating the design of next-generation, high-performance, and sustainable LTCCcompatible materials. Mon, 15 Jun 2026 00:00:00 GMT https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22408 2026-06-15T00:00:00Z https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22407 Long memory time series analysis Shan Han Li The book is primarily designed as a course textbook for advanced undergraduates. The content begins with shortrange stationary linear models, such as autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA) in Chapters 1 to 3. From Chapters 4 to 7, it considers long-range stationary linear models, such as autoregressive fractionally integrated moving average Fri, 19 Jun 2026 00:00:00 GMT https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22407 2026-06-19T00:00:00Z https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22406 Asymmetrically Cu-O-Cu Bridged dual-atom sites on bio Yeryong Lee; Akasch Prabhu Theelectrochemicalnitratereductionreaction(NO3RR)isapromisingstrategyfordecentralizedammonia(NH3)productionandenvironmental remediationunder ambient conditions. However, achieving complete eightelectron/nine-proton(8e /9H+)conversionofNO3 oNH3withhighselectivityandefficiencyremainschallengingowingtosluggishNO3 ctivationandcompetingN–uplingsidereactionssuchasN2,N2O,andNOgasevolution.Herein,wereportarationallydesignedCudual-atom(DA)catalystcomposedofasymmetricallycoordinatedCuatomicpairsanchoredonanL-tryptophan-functionalizedFe3O4/α-Fe2O3heterostructure(Cu2/ try-FeOx), synthesizedviaaCO2 laser irradiationmethodinvolvingmulti-stepcontinuous-waveexposure for interfaceengineering. ThehybridCu2/try-FeOx support provides abundantNandOcoordinationsites and enhancedelectronmobility,enablingspatiallyseparatedCuatombyasymmetricallycoordinatedCu–N/Odualsites exhibit synergistic electronic interactions, forming robustDAconfigurations. Insituandex situspectroelectrochemicalanalyses,supportedbytheoreticalcalculations,confirma*NO3→*NO2→*NO→*NHO→*NH2O→*NH3→NH3reactionpathway.Attheoptimalpotential,thetotalFaradaicefficiencytowardNH3andNO2approaches~95%,indicatingeffectivesuppressionofcompetingH2,N2,andN2Oformationandconfirmingahighlyselective8e‒/9H+NO3RRmechanism.Notably,NO3RRtestsusingCu2/try-FeOXachieveahighNH3yieldrateof0.29mmolh 1cm2andamaximumFaradaicefficiencyof88.5%at .2Vvs.RHE.Furthermore,whenintegratedintoaZn–NO3 battery, thecatalystenablesself-poweredNO3 toNH3conversionwithstableoperationover100h.ThisstudypresentsarationalapproachthatintegratesDAsiteengineeringcatalystdesignwithbio-unctionalsupportdesigntoregulateintermediateadsorptionandelectrontransfer,therebyenhancingtheactivityandselectivityforself-poweredmolecularNO3upcyclingtechnologies. Tue, 23 Jun 2026 00:00:00 GMT https://bibliotecadigital.bcb.gob.bo/xmlui/handle/123456789/22406 2026-06-23T00:00:00Z