应我校能源学院赵军明教授邀请，俄罗斯沃沃夫斯基化学动力学与燃烧研究所（Voevodsky Institute of Chemical Kinetics and Combustion，ICKC）高级研究员、俄罗斯新西伯利亚州立大学（Novosibirsk State University）高级讲师Maxim A. Yurkin来我校能源学院访问讲学，欢迎感兴趣的师生踊跃参加，学术讲座题目、时间和地点安排如下：
报告题目：The discrete dipole approximation for light-scattering simulations
Light scattering is widely used in remote sensing of various objects ranging from metal nanoparticles and macromolecules to atmospheric aerosols and interstellar dust, being in some cases the only available approach to characterize their geometric or optical properties. Moreover, the structure of electromagnetic fields near a particle is also of major importance for other phenomena, such as surface-enhanced Raman scattering or electron energy-loss spectroscopy. All these applications require accurate simulations of interaction of electromagnetic fields with particles, which is not trivial for particles of arbitrary shape and internal structure with sizes comparable to or larger than the wavelength. The discrete dipole approximation (DDA) is one of the general methods to handle such problems. In this talk I will provide an introduction to the DDA, including both the basic underlying physical picture and rigorous derivation starting from the integral form of Maxwell’s equation for the electric field. The latter shows that the DDA is a numerically exact method and a special case of volume-discretization method of moments. Apart from the standard problem of far-field scattering by single isolated particles, the DDA can also be applied to particles in complicated environments (e.g. on substrate) and to other electromagnetic physical phenomena. I will also discuss computational aspects, including the latest efficiency improvements, and briefly review the existing open-source DDA codes, which made the method so popular in the light-scattering community.
报告题目：Characterization of single particles from light-scattering profiles
Measurement of angle-resolved light-scattering profiles (LSPs) of single particles provides unique capabilities for detailed and accurate characterization of disperse media. In this talk I will review our results of developing characterization methods for various kinds of particles, mostly focusing on parametric inverse light-scattering problems, i.e. when the particle model is specified up to a few free parameters. The first class of particles (homogeneous and concentric spheres) allow for fast solution of the direct problem (using the Mie theory). The characterization is then based on the direct fit (non-linear regression) using a global optimization technique, which also provides standard errors of estimated characteristics. It has been successfully applied to polystyrene beads, milk fat globules, extracellular vesicles, and lymphocytes. Unfortunately, such approach is not practical for other particle shapes that require slower solution methods (e.g., the discrete dipole approximation). For this class of particles, we developed a method based on the nearest-neighbor interpolation using a database of simulated LSPs. It also provides standard errors of characteristics and can be accelerated using hierarchical clustering of the database. This general approach has been successfully applied to blood platelets, erythrocytes, vesicles aggregates, and E. Coli bacteria. The applications of the developed methods are all based on measurements of LSPs of single particles in water using a scanning flow cytometer. However, the same methodology can be applied to other experimental set-ups.
Maxim A. Yurkin是俄罗斯沃沃夫斯基化学动力学与燃烧研究所（Voevodsky Institute of Chemical Kinetics and Combustion，ICKC）高级研究员，同时也是俄罗斯新西伯利亚州立大学（Novosibirsk State University）的高级讲师，分别于阿姆斯特丹大学和ICKC取得计算科学和生物物理学双博士学位。迄今为止，发表学术论文200余篇，SCI引用1000余次。目前研究方向包括有DDA、体积分法光散射和光散射反问题。Maxim A. Yurkin研究员是著名开源离散偶极子光散射计算软件ADDA的主要开发者，曾获得包括Elsevier电磁光散射青年科学家奖及欧洲科学院俄罗斯青年科学家奖在内的多个国际学术奖项。