PBE0 / TZVP ADMM / TZVP+tzp ADMM / TZV2P+tzp sTDA@PBE0 / TZVP sTDA@ADMM / TZVP+tzp bright fluorescence depending on either accordingly tuned linker molecules or the surrounding solvent. The CURATED COFs database provides cleaned-up DFT-optimized GS structures at GGA level of accuracy, obtained with PBE functional, D3(BJ) correction, and DZVP-MOLOPT-SR basis sets. We re-optimized these geometries using a corresponding ADMM-PBE0 GS reference and triple-zeta ccGRB-T primary and tzp auxiliary basis sets to ensure a consistent accuracy of both structural and electronic GS and ES properties. The re-optimized ADMM-PBE0 GS and ES geometries are provided as supplementary information. In all calculations a truncated Coulomb operator with a radius of 4 Å has been used. In Table , detailed timings for the first 3 ES geometry optimization steps are given for COF 05000N2 for ADMM-approximated and sTDA kernels in comparison to conventional PBE0 results with the latter relying on an exact analytical evaluation of the two-electron-four-center exchange integrals. The total computation time of ≈ 100 hours for a ccGRB-T basis with 2076 basis functions reflects that an analytical computation of exchange integrals within a large primary orbital basis cannot provide optimal efficiency for large periodic systems. The fact that 28% and 71% of the PBE0 computation time are solely attributed to the computation of electron repulsion integrals (ERIs) and derivative electron repulsion integrals (DERIs) emphasizes the need for approximations. Applying ADMM with a triple-zeta auxiliary basis and thus reducing the basis-set size by a factor of 2 to 1164 functions, accelerates the computation by a factor of ≈ 20 with a remaining total time of 3.8 minutes. The small auxiliary basis reduces the number of ERIs and, in combination with increased sparsity and thus more efficient Schwarz screening, the reduction of the basis size results in timings for the integral evaluation that are reduced by a factor of ≈ 10. More drastic is even the speed-up for the computation of DERIs due to the here applied density-matrix screening. In comparison to PBE0, the computation of DERIs is 300 times faster for ADMM-PBE0 and thus represents not 71%, but solely 6% of the total costs. Timings comparable to ADMM-PBE0 can also be achieved with the semi-empirical tight binding setup: sTDA reduces the total costs to 2.4 minutes, thus by a factor of ≈ 40 in comparison to conventional PBE0 and by a factor of ≈ 2 in comparison to ADMM. The speed-up with respect to ADMM is due to the faster ERI evaluation relying on the semi-empirical description of both Coulomb and exchange contributions when solving the ES eigenvalue problem. sTDA and ADMM timings are in the same order of magnitude, but further acceleration could be expected when switching to a complete semi-empirical setup for both GS and ES. We are also aware that absolute timings for the sTDA ES gradient computations could still be improved by further code optimization. To give an estimate on the required relative costs of ADMM and sTDA for the computation of broad-band absorption spectra and for the geometry optimization of low-lying excited states we report timings for all six COFs in Table . Computations were performed for the lowest 500 excited states and the geometry optimization of the first ES when selecting a manifold of 8 singlet states. The investigated system sizes range from unit cells of 84 to 300 atoms and include basis set sizes of 2076 to 7440 basis functions, respectively. Comparing the computational timings for the calculation of the lowest 500 excitation energies clearly shows the advantage of the semi-empirical setup. While computations using the ADMM kernel take ≈ 2 to 8.5 hours, sTDA is one order of magnitude faster with a maximum computation time of less than 24 minutes. With the current setup, the tight binding approach is however less favorable for ES geometry optimization. First, the number of required optimization cycles is increased for the two COFs 05000N2 and 05001N2. Second, the averaged computation time per optimization cycle is accelerated only by a factor of 2.5 to 4, so that ADMM-PBE0 and sTDA computation times are of the same order of magnitude and for the two COFs 05000N2 and 05001N2, the total sTDA timings even exceed the corresponding ADMM ones. For both ADMM-PBE0 and sTDA computations, timings of 5-30 minutes per optimization cycle and total timings of 1.5 -12 hours for an ES geometry optimization can thus be expected for periodic systems in the size range of hundreds of atoms and using the indicated computational resources. To compare the relative accuracy of ADMM-PBE0 and sTDA for periodic systems, the computed broad-band spectra are depicted in Figure . Corresponding vertical excitation, adiabatic excitation, and fluorescence energies, as well as Stoke's shifts are listed in Table . As highlighted by the six plots of Figure , sTDA and ADMM provide absorption spectra with qualitatively matching oscillator strengths. sTDA excitations are, however, in all cases shifted to smaller energies, with MADs for the first and the first ten vertical excitation energies amounting both up to 0.35 eV. Since the exchange mixing parameter a EX was set to the same value as for the molecular systems (a EX = 0.2), it remains to be investigated if this apparently systematic shift could be improved by adjusting the amount of exchange. However, even with this default setting, the MAD in adiabatic excitation and fluorescence energies is within the error range found for molecular systems. ADMM-PBE0 and sTDA energies differ by 0.42 or 0.31 eV, respectively. Corresponding Stoke's shifts are thus also predicted with a relatively small deviation of 0.13 eV.