Book recommendations for Combinatorial Designs I am well-acquainted to basic topics of experimental designs such as anova, ancova, crd, rbd, lsd, factorial design, robust design etc (as per the book of Dr. D. C. Montgomery). Now as per my recent ongoing research curriculum, I need to learn more mathematically oriented combinatorial design. The topics I need to learn are finite geometry, steiner systems, t-designs, resolvable designs, pairwise balanced design, directed design, pbd, tuscan squares, vector space design, packing, partial geometry, sequences with zero autocorrelation, D-optimal design etc and some other topics based on abstract and linear algebra. I have started with the book by W. D. Wallis but not all topics (such as equidistant permutation array, skolem sequences and many other topics aforementioned) are covered in this book. Also Wikipedia gives a list of references but I am not sure which one to pick beside the book I am using.
Would you kindly like to recommend books on combinatorial design that cover these topics? All suggestions and recommendations are valuable and appreciated.

Disclaimer: These are some of the materials that I came across, some of which I used profusely. While the resources don't cover all the things OP mentioned, these are worth to study.

Analysis and Design of Experiments, H. B. Mann, Dover, 1949

Author does an exceptional job in keeping the chapters short but detailed enough to not create any void in derivations. The book is not voluminous; though sometimes beating the bush to go to the main results but this is definitely not quaint: a sharp exposition. The highlights are the chapters on latin squares, Galois fields and Orthogonal Latin squares. More or less self-contained.
Mathematics of Design and Analysis of Experiments, M. C. Chakrabarti, Asia Publishing House, 1962
These are collection of lectures by the author. Not recommended for first reading. The materials are terse. I liked his treatment of confounded arrangements in split-plot designs, application of Galois fields and finite geometry in constructing the confounded designs, hypercubes of strength $d.$ But again, I reiterate it is not for first reading.
Constructions and Combinatorial Problems in Design of Experiments, Damaraju Raghavarao, Wiley, 1971
The author indeed has largely been successful in consolidating some of the important topics: construction of orthogonal arrays, products of orthogonal arrays, embeddings, MacNeish-Mann Theorem, duals of incomplete block designs, partial geometries. Essentially a formal treatment of the field: a good read.
Optimal Design: An Introduction to the Theory for Parameter Estimation, S.D. SILVEY, CHAPMAN AND HALL, 1980
My personal favorite. Silvey did an amazing job in writing such a beautiful treatise. If one knows nothing and wants to have an intuitive idea about information matrices, design criteria, $\mathcal D$ optimality, design algorithms, then without an iota of doubt, do read this classic.
Optimal Design of Experiments, Friedrich Pukelsheim, SIAM, 2006
This is a magnum opus in true sense for it delves deep, I mean way deep, in covering optimality theory. It thoroughly discusses information matrices, optimality criteria, the equivalence theorems, $\cal D,~A, ~E, ~T$ optimality, Bayes designs, invariant designs, Loewner and Kiefer optimality, rotatibility.
Design and Analysis of Experiments, M.K.Sharma, B. V. S. Sisodia, PHI Learning Pvt. Ltd., 2012
A beginner's book with a copious writing style and a tolerable pace develops the finite field theory, finite geometries, difference sets and their applications in constructing the requisite designs. Exercises are easy to moderate.
Robust Response Surfaces, Regression, and Positive Data Analyses, R. N. Das, CRC Press, 2014
The monograph provides a conspicuous elucidation of weak rotatibility, slope rotatibility, weak slope rotatibility, $\mathcal D$ optimal slope rotatibility, and also brief discussion of correlated structures. Although the main attention and emphasis are on robust response surfaces. It is replete with good applications.
