Catalysts design for higher alcohols synthesis by CO2 hydrogenation: Trends and future perspectives

Global warming due to the accumulation of atmospheric CO2 has received great attention in recent years. Hence, it is urgent to reduce CO2 emissions into the atmosphere and develop sustainable technologies for a circular carbon economy. In this regard, CO2 capture coupled with the conversion into chemicals and fuels provides a promising solution to reduce CO2 emissions as well as to store and utilize renewable energy. Among the many possible CO2 conversion pathways, CO2 hydrogenation to higher alcohols is considered an important strategy for the synthesis of carbon-based fuels and feedstock and holds great promise for the chemical industry. Thus, this review provides an overview of advances in CO2 hydrogenation to higher alcohols that have been achieved recently in terms of catalyst design, catalytic performance, and insight into the reaction mechanism under different experimental conditions. First, the limitations provided by reaction thermodynamics and the indispensability of catalysts for CO2 hydrogenation to higher alcohols are discussed. Then, four main categories of catalysts will be introduced and discussed (i.e. Rh-, Cu-, Mo-, and Co-based catalysts). Moreover, important factors significantly influencing the efficiency of the catalytic transformation such as alkali/alkaline earth metal promoters, transition metal promoters, catalyst supports, catalyst precursors, and reaction conditions, as well as the reaction mechanism are explained. Finally, the review discusses emerging methodologies yet to be explored and future directions to achieve a high efficiency for the hydrogenation of CO2 to higher alcohols

Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models

Multimodal data, which can comprehensively perceive and recognize the physical world, has become an essential path towards general artificial intelligence. However, multimodal large models trained on public datasets often underperform in specific industrial domains. This paper proposes a multimodal federated learning framework that enables multiple enterprises to utilize private domain data to collaboratively train large models for vertical domains, achieving intelligent services across scenarios. The authors discuss in-depth the strategic transformation of federated learning in terms of intelligence foundation and objectives in the era of big model, as well as the new challenges faced in heterogeneous data, model aggregation, performance and cost trade-off, data privacy, and incentive mechanism. The paper elaborates a case study of leading enterprises contributing multimodal data and expert knowledge to city safety operation management , including distributed deployment and efficient coordination of the federated learning platform, technical innovations on data quality improvement based on large model capabilities and efficient joint fine-tuning approaches. Preliminary experiments show that enterprises can enhance and accumulate intelligent capabilities through multimodal model federated learning, thereby jointly creating an smart city model that provides high-quality intelligent services covering energy infrastructure safety, residential community security, and urban operation management. The established federated learning cooperation ecosystem is expected to further aggregate industry, academia, and research resources, realize large models in multiple vertical domains, and promote the large-scale industrial application of artificial intelligence and cutting-edge research on multimodal federated learning

Design and synthesis of cabotegravir derivatives bearing 1,2,3-triazole and evaluation of anti-liver cancer activity

Based on the structure of the anti-HIV drug cabotegravir, we introduced 1,2,3-triazole groups with different substituents to obtain 19 cabotegravir derivatives and tested their activity against HepG2 cells. The proliferation of HepG2 cells was examined following treatment with derivatives. Most of the compounds demonstrated significant inhibitory effects, particularly compounds KJ-5 and KJ-12 with IC50 values of 4.29 ± 0.10 and 4.07 ± 0.09 μM, respectively. Furthermore, both compounds 5 and 12 significantly caused cell apoptosis, G2/M arrest, and DNA damage, and suppressed invasion and migration in a concentration-dependent manner. In addition, KJ-5 and KJ-12 could trigger apoptosis via the mitochondrial pathway by increasing the ratio of Bax/Bcl-2 and activating cleaved caspase-9, cleaved caspase-3, and cleaved PARP

Volatility of mixed atmospheric humic-like substances and ammonium sulfate particles

The volatility of organic aerosols remains poorly understood due to the complexity of speciation and multiphase processes. In this study, we extracted humic-like substances (HULIS) from four atmospheric aerosol samples collected at the SORPES station in Nanjing, eastern China, and investigated the volatility behavior of particles at different sizes using a Volatility Tandem Differential Mobility Analyzer (VTDMA). In spite of the large differences in particle mass concentrations, the extracted HULIS from the four samples all revealed very high-oxidation states (O : C > 0.95), indicating secondary formation as the major source of HULIS in Yangtze River Delta (YRD). An overall low volatility was identified for the extracted HULIS, with the volume fraction remaining (VFR) higher than 55% for all the regenerated HULIS particles at the temperature of 280 degrees C. A kinetic mass transfer model was applied to the thermodenuder (TD) data to interpret the observed evaporation pattern of HULIS, and to derive the mass fractions of semi-volatile (SVOC), low-volatility (LVOC) and extremely low-volatility components (ELVOC). The results showed that LVOC and ELVOC dominated (more than 80 %) the total volume of HULIS. Atomizing processes led to a size-dependent evaporation of regenerated HULIS particles, and resulted in more ELVOC in smaller particles. In order to understand the role of interaction between inorganic salts and atmospheric organic mixtures in the volatility of an organic aerosol, the evaporation of mixed samples of ammonium sulfate (AS) and HULIS was measured. The results showed a significant but nonlinear influence of ammonium sulfate on the volatility of HULIS. The estimated fraction of ELVOC in the organic part of the largest particles (145 nm) increased from 26 %, in pure HULIS samples, to 93% in 1 : 3 (mass ratio of HULIS : AS) mixed samples, to 45% in 2 : 2 mixed samples, and to 70% in 3 : 1 mixed samples, suggesting that the interaction with ammonium sulfate tends to decrease the volatility of atmospheric organic compounds. Our results demonstrate that HULIS are important low-volatility, or even extremely low-volatility, compounds in the organic-aerosol phase. As important formation pathways of atmospheric HULIS, multiphase processes, including oxidation, oligomerization, polymerization and interaction with inorganic salts, are indicated to be important sources of low-volatility and extremely low-volatility species of organic aerosols.Peer reviewe