No abstract

Reducing custom software development effort is an important goal in information retrieval (IR). This study evaluated a generalizable approach involving with no custom software or rules development. The study used documents "consistent with cancer" to evaluate system performance in the domains of colorectal (CRC), prostate (PC), and lung (LC) cancer. Using an end-user-supplied reference set, the automated retrieval console (ARC) iteratively calculated performance of combinations of natural language processing-derived features and supervised classification algorithms. Training and testing involved 10-fold cross-validation for three sets of 500 documents each. Performance metrics included recall, precision, and F-measure. Annotation time for five physicians was also measured. Top performing algorithms had recall, precision, and F-measure values as follows: for CRC, 0.90, 0.92, and 0.89, respectively; for PC, 0.97, 0.95, and 0.94; and for LC, 0.76, 0.80, and 0.75. In all but one case, conditional random fields outperformed maximum entropy-based classifiers. Algorithms had good performance without custom code or rules development, but performance varied by specific application.

Spent lithium-ion batteries (LIBs) typically contain a combination of both strategic materials and toxic chemicals that cannot be easily disposed. Nowadays, that are many different methods used to treat spent LIBs with the primary aim of critical metals recovery; nevertheless, as a result of the toxic chemicals within the battery waste, the chemical composition and potential danger of the off-gases generated during recycling process have become a serious concern. In an attempt to further understand the characteristics of the off-gases that are emitted from spent LIBs cathodes during thermolysis process, a system of thermogravimetry−differential thermal analysis coupled with mass spectrometry equipped with skimmer-type interface and with electron ionization (TG-DSC-EI-MS) has been employed to qualitatively analyze the generated off-gases. Based on the obtained observations, it was confirmed that inorganic gases of H 2 , H 2 O, CO 2 , gaseous hydrocarbons, and fluoride-containing gases were generated. Moreover, the off-gas species and relative yield of the individual gases formed were found to be significantly affected by the thermolysis temperature under different atmospheric conditions. From the combined results from TG-DSC-EI-MS, thermogravimetric differential scanning calorimetry analysis (TG-DSC), chemical analysis, X-ray diffraction (XRD), and scanning electron microscopy (SEM), the correlation between the evolution characteristics of the gas emissions and thermolysis behavior of the cathodes from spent LIBs has been established. The availability of this type of quantitative data is useful when undertaking environmental assessments and for the design of off-gas management systems for spent LIBs recycling processes.

This study proposes an innovative and environment-friendly method for recycling spent lead-acid batteries without SO2 generation. Iron-containing waste was employed as a sulfur-fixing agent to retain sulfur as ferrous matte, which eliminated the generation and emissions of gaseous SO2. This work investigated the thermodynamic and experimental feasibility and conversion mechanism of the method, and evaluated its industrial applicability. A bench-scale test showed direct recoveries of 93.5 % and 97.7% in crude lead and ferrous matte for lead and sulfur, respectively. The phase transformation mechanism study indicated that metallic lead from the lead paste was extracted mainly through the sequence of PbSO4 / → PbS 3 4 → PbO / → . Sulfur in PbSO4 was thus first transferred to PbS and finally fixed as FeS. An industrial-scale pilot campaign was also conducted to confirm the feasibility and reliability of the new process.

This study investigated the gaseous products evolution behaviors and the recovery performance of cathode materials from spent LiFePO 4 batteries by vacuum pyrolysis. The thermogravimetric-differential scanning calorimetry analysis coupled with electron ionization mass spectrometry (TG-DSC-EI-MS) results indicated that inorganic gases (H 2 O, CO, CO 2 ), alkane gases (CH