Abstract: Provided in the present invention is a high-throughput material simulation calculation optimization method based on time prediction, relating to the field of materials science. The method comprises: first constructing a prediction model of task configurations and corresponding time predictions, and using the prediction model to generate the execution time of all of the tasks in a high-throughput material simulation calculation under different conditions; then generating an optimal scheduling plan for each model in the high-throughput material simulation calculation by means of directed graphs; and, according to the optimal scheduling plan for each model, sequentially executing all of the tasks until all of the tasks are completed. Further, a high-throughput computing simulation optimization apparatus based on a time prediction and a storage medium are provided.

Abstract: The present disclosure belongs to the technical field of extraction of fragrance substances, and specifically relates to Cymbidium goeringii balsam and a preparation method and use thereof. The present disclosure is implemented by cultivating multiple plants of Cymbidium goeringii with unravelling bloom collectively in a relatively small enclosed space, and enriching fragrance substances of Cymbidium goeringii in the air by lipid for adsorption. The method of the present disclosure can obtain Cymbidium goeringii balsam rich in a variety of fragrance components in a relatively short time. GC-MS detection indicates as many as 50 components. The present disclosure significantly improves the prior art in which only a small amount of fragrance components in Cymbidium goeringii can be extracted or even cannot be obtained. The present disclosure can be further used in extracting essential oils or applied directly.

Abstract: Provided in the present invention is a high-throughput material simulation calculation optimization method based on time prediction, relating to the field of materials science. The method comprises: first constructing a prediction model of task configurations and corresponding time predictions, and using the prediction model to generate the execution time of all of the tasks in a high-throughput material simulation calculation under different conditions; then generating an optimal scheduling plan for each model in the high-throughput material simulation calculation by means of directed graphs; and, according to the optimal scheduling plan for each model, sequentially executing all of the tasks until all of the tasks are completed. Further, a high-throughput computing simulation optimization apparatus based on a time prediction and a storage medium are provided.