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Forest biomass and carbon storage models are crucial for inventorying, monitoring, and assessing forest resources. This study develops models specific to China's diverse forests, offering a methodological foundation for national carbon storage estimation and a quantitative basis for national, regional, and global carbon sequestration projections. Utilizing data from 52,700 permanent plots obtained during China's 9th national forest inventory, we calculated biomass and carbon storage per hectare for 35 tree species groups using respective individual tree biomass models and carbon factors. We then constructed a three-level volume-based model system for forest biomass and carbon storage, applying weighted regression, dummy variable modeling, and simultaneous equations with error-in-variables. This system encompasses one population of forests, three forest categories (level I), 20 forest types (level II), and 74 forest sub-types (level III). Finally, the assessment of these models was carried out with six evaluation indices, and comparative analyses with previously established biomass models of three major forest types were conducted. Determination coefficients (R2) for the population average model, and three dummy models on levels I, II, and III, exceed 0.78, 0.85, 0.92, and 0.95, respectively, with corresponding mean prediction errors (MPEs) of 0.42%, 0.34%, 0.24%, and 0.19%, and mean percent standard errors (MPSEs) of approximately 22%, 21%, 15%, and 12%. Models for 20 forest types and 74 sub-types yield R2 values above 0.87 and 0.85, with MPE values below 3% and 5%, respectively. Notably, the estimates of previous biomass models of three major forest types demonstrated considerable uncertainty, with TRE ranging from −20% to 74%. However, accuracy has improved with larger sample sizes. In total biomass and carbon storage estimations, the R2 values of dummy models for levels I, II, and III progressively increase and MPSE and MPE values decrease, whereas TRE approximates zero. The tiered model system of simultaneous equations developed herein offers a quantitative framework for precise evaluations of biomass and carbon storage on different scales. For enhanced accuracy in such estimations, applying level III models is recommended whenever feasible, especially for national estimation. [ABSTRACT FROM AUTHOR]

This study aimed to develop simultaneous models with universal applicability for the estimation of the main factors of forest stands based on airborne LiDAR data and to provide a reference for standardizing the approach and evaluation indices of main forest factor modeling. Using airborne LiDAR and field survey data from 190 sample plots in spruce (Picea spp.), fir (Abies spp.), and spruce–fir mixed forests in Northeast China, the simultaneous models for estimating the main factors of forest stands were developed. To develop the models, the relationships between mean tree height, stand basal area, stand volume, and the main metrics of the LiDAR data and the correlations between eight quantitative factors of forest stands were considered, and the error-in-variable simultaneous equations approach was employed to fit the models. The results showed that the mean prediction errors (MPEs) of eight forest stand factors estimated by the simultaneous models were mostly within 5%, and only the MPE of the number of trees per hectare exceeded 5%. The mean percentage standard errors (MPSEs) of the estimates, including the mean diameter at the breast height (DBH), mean tree height, and mean dominant tree height, were within 15%; the MPSEs of the estimates of the stand basal area, volume, biomass, and carbon stock per hectare were within 25%; and only the MPSE of the estimated number of trees per hectare exceeded 30%. The coefficients of determination (R2) of the core prediction models for the volume, biomass, and carbon storage were all greater than 0.7. It can be concluded that estimating the main factors of forest stands based on the combination of LiDAR and field survey data is technically feasible, and the simultaneous models developed in this study for the estimation of the eight main stand factors of spruce–fir forests can meet the precision requirements of forest resource inventory, except for the number of trees, indicating that the models can be applied in practice. [ABSTRACT FROM AUTHOR]

Diketopyrrolopyrrole (DPP) is an excellent photosensitizer and photothermal agent with the advantages of good planarity, strong electron affinity, high electron mobility, easy purification, easy structural modification and high molar absorption coefficient. It is regarded as one of the ideal choices for the design and synthesis of efficient organic photovoltaic materials. Therefore, two kinds of donor–acceptor (D–A) conjugated polymers were designed and synthesized with DPP as the acceptor, and their optical properties and applications in the near-infrared region were studied. The quantum yield (QY) of PBDT-DPP is 0.46%, and the highest temperature reached within 10 minutes after irradiation with a 660 nm laser is 60 °C. Another polymer, EDOT-DPP, has a QY of 0.48%, and its semiconductor polymer nanoparticle aqueous solution can reach 60 °C within 12 minutes under laser irradiation, achieving photothermal treatment of nude mice tumors. Both polymer NPs have good biocompatibility and promising applications in bioimaging and photothermal therapy. [ABSTRACT FROM AUTHOR]

Carbon quantum dots (CQDs) have emerged as prominent contenders in the realm of luminescent nanomaterials over the past decade owing to their tunable optical properties, robust photostability, versatile surface functionalization and doping potential, low toxicity, and straightforward synthesis utilizing environmentally friendly precursors. In this review, we commence with a concise introduction, presenting both top‐down and bottom‐up strategies for the eco‐friendly synthesis of CQDs. Subsequently, we delve into a comprehensive examination of CQDs' structure and optical characteristics, encompassing their ultraviolet–visible absorption properties, surface confinement effects, and surface state emissions contributing to room‐temperature photoluminescence (PL). This review proceeds to elucidate recent advancements in modification strategies for CQDs, specifically focusing on surface oxidation, passivation, and the incorporation of heteroatoms. These strategies serve to afford control over the physicochemical properties, facilitating the enhancement of PL through the decoration of highly visible‐responsive CQDs. This enhancement is achieved by suppressing the nonradiative recombination of electron‐hole pairs, enabling red/blue shifts in CQDs for the generation of a full‐color emission spectrum, and regulating the band‐gap and surface states to broaden the photoabsorption range. Finally, we offer an overview of the most recent developments in the applications of fluorescent CQDs, emphasizing their utility in biomedicine, fluorescent sensors, lighting, and displays, as well as photocatalysis. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: All‐solution‐processed organic solar cells (OSCs) (from the bottom electrode to the top electrode) are highly attractive thanks to their low cost, lightweight and high‐throughput production. However, achieving highly efficient all‐solution‐processed OSCs remains a significant challenge. One of the key issues is the lack of high‐quality solution‐processed electrode systems that can replace indium tin oxide (ITO) and vacuum‐deposited metal electrodes. In this paper, we comprehensively review recent advances in all‐solution‐processed OSCs, and classified the devices as the top electrode materials, including silver nanowires (AgNWs), conducting polymers and composite conducting materials. The correlation between electrode materials, properties of electrodes, and device performance in all‐solution‐processed OSCs is elucidated. In addition, the critical roles of the active layer and interface layer are also discussed. Finally, the prospects and challenges of all‐solution‐processed OSCs are presented. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: With the tactful material design, skillful device engineering, and in‐depth understanding of morphology optimization, organic solar cells (OSCs) have achieved considerable success. Therefore, OSCs have reached high power conversion efficiencies (PCEs) exceeding 19%. Especially, continuously emerging new materials have been considered as one of the key factors to improve the PCEs of OSCs. Among molecular design strategies, side‐chain engineering is an easy and commonly‐used means which can optimize the solubility, alter intermolecular stacking arrangement, fine‐tune the open circuit voltage (VOC), thus ultimately improve the performance. As hybrid side chains, silane and siloxane side chains have considerable effects, not only in increasing the carrier mobility and tuning the energy level, but also in affecting the crystallinity and molecular orientation. In this review, the latest developments in photovoltaic materials based on silane and siloxane side chains are presented to illustrate the structure‐property relationships. The review comprehensively includes silane‐side based polymer/small molecule donors; siloxane‐side based polymer/small molecule donors, and polymer/small molecule acceptors. Then the similarities and differences between these two side chains are demonstrated. Finally, the possible applications and future prospects of silane and siloxane side chains are presented. [ABSTRACT FROM AUTHOR]