A nonmonotonic dependence of standard rate constant on reorganization energy for heterogeneous electron transfer processes on electrode surface

In the present work a nonmonotonic dependence of standard rate constant (k(0)) on reorganization energy (lambda) was discovered qualitatively from electron transfer (Marcus-Hush-Levich) theory for heterogeneous electron transfer processes on electrode surface. It was found that the nonmonotonic dependence of k(0) on lambda is another result, besides the disappearance of the famous Marcus inverted region, coming from the continuum of electronic states in electrode: with the increase of lambda, the states for both Process I and Process II ET processes all vary from nonadiabatic to adiabatic state continuously, and the lambda dependence of k(0) for Process I is monotonic thoroughly, while for Process II on electrode surface the lambda dependence of k(0) could show a nonmonotonicity.

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.