This month's cover highlights the paper by Venkataraman, Du, Wilson, Hirsch, Zhang, and Moore (page 915). Using data bases of structural information, the authors have surveyed and cataloged the structures of a large number of coordination compounds of d-block elements. Their results are summarized in several tables of color-coded pie charts. Happily their findings confirm the qualitative observations that appear in most textbooks of inorganic chemistry, and their colorful charts may well appear in the next editions of many such books. On the Journal's Web site you will find the full paper in an interactive format where additional information is available by clicking on the pie chart of your choice. For personal classroom use you can incorporate the diagrams into overhead transparencies or computer-based presentations, but please contact the Journal for permission before using them beyond your own classroom or on your own Web site

In addition to our cover article, this issue contains several other papers of interest to inorganic chemists. Treptow (page 919) has examined the Born-Haber cycle in detail and provides a wealth of information about where the quantities we substitute into such thermochemical calculations really come from, their definitions, and how to convert them all to the appropriate enthalpy changes. In a paper on global metabolism of elements (page 926) Ochiai follows several elements through their biogeochemical cycles, dealing with the bioinorganic chemistry of their interactions with and transformations by the global environment. Carlton (page 939) has developed an innovative approach to the chemical reactions between solutions containing acids and bases (as opposed to the calculation of their equilibrium concentrations) that may prompt many to redirect the emphasis of their treatment of acids and bases in general and inorganic chemistry.

Proksa has developed a new way to show the reaction of metallic sodium with water (page 942). Proper choice of indicators allows this reaction to produce all the colors of the rainbow in a series of aqueous solutions.

Yukinori et al. follow up on an earlier demonstration that showed the attraction of a balloon full of oxygen to a strong magnet by demonstrating that a balloon filled with nitrogen is slightly repelled by a very strong magnetic field (page 943).

This month we bring you a large number of laboratory experiments (pages 952-1000). Space prohibits mentioning all of them, although all will complement some aspect of a chemistry lab program. Two involve guided inquiry. Mauldin (page 952) develops in detail the processes by which students can be induced and aided to apply scientific reasoning to data they collect on the mass, volume, and other properties of pennies, building on work previously reported in this Journal. Beginning on page 955, Bindel and Fochi show how the concept of specific heat capacity and the law of Dulong and Petit can be discovered by students in an introductory laboratory.

For cost-effective equipment, Shevlin et al. (page 958) show how to make a constant-temperature heating block and Ohno et al. (page 961) describes an inexpensive IR cell. There are several labs that illustrate principles and data handling associated with chemical kinetics. On page 972 Hemalatha and NoorBatcha describe an experiment involving first-order kinetic data. Ramachandran and Halpern describe on page 975 a tractable system from which students can obtain experimental data on the kinetics of the system A <=> B -> C, nicely complementing the usual text book treatment of such systems.

Given the ubiquity of modern information processing tools, the methods we use (and should be teaching students to use) for data analysis are changing rapidly. Vitha and Carr (page 998) describe a laboratory exercise that teaches appropriate statistical analysis of data the students have collected. Zielinski and Allendoerfer use Mathcad software as a tool by which students can analyze nonlinear data sets such as those obtained in chemical kinetics experiments; their methods and recommendations begin on page 1001. Lieb also describes analysis of nonlinear data (page 1008), this time using a simplex optimization.