Capture and sequestration of CO2 from power plant flue gas have become an important issue in the discussion about global warming. Different concepts of capture are being pursued. The advantage of postcombustion processes, such as processes based on absorption and stripping, is the possibility of retrofitting a state-of-the-art power plant with a capture plant under reasonable effort. Capturing CO2 by using an absorption/stripping process requires energy in the form of electricity and steam both supplied by the power plant. The capture process thereby reduces the overall efficiency of the power plant by up to 13%pts (percentage points). Apart from the development of new solvents, alternative and novel configurations of the process can lower the energy requirements. Three alternative configurations are economically and technically evaluated and compared to a baseline process represented by a standard absorption/stripping process using monoethanolamine (MEA) as a solvent. Savings in cost of CO2-avoided of 2−5% were attained. Regarding the total power required, savings of 4−7% were obtained. The results showed that not the process with the highest energy savings has the lowest cost of CO2-avoided, but that the influence of rising investment costs of more complex configurations cannot be ignored. For a comprehensive analysis of different configurations it is essential to perform both an economic evaluation and a technical study.

A new microfluidic product for measuring fluid density, specific gravity and chemical concentration has been developed. At the core of this lab-on-a-chip sensor is a vacuum-sealed resonating silicon microtube. Measurements can be made with under a microliter of sample fluid, which is over 1000x less than is conventionally required. Since the product is MEMS-based the overall system size is a fraction of conventional density meters and it weighs much less than the traditional desk-top, temperature controlled, density meters. The syringe or pipette loaded system includes a dynamic temperature control system that operates between 0 degree C and 90 degree C with an accuracy of less than 0.01 degree C. Density measurement accuracies of 4 to 5 digits have been observed with aqueous solutions. Measurement examples and applications will be discussed.

We present an extension of our earlier work on adaptive quantum wavepacket dynamics [B. Hartke, Phys. Chem. Chem. Phys., 2006, 8, 3627]. In this dynamically pruned basis representation the wavepacket is only stored at places where it has non-negligible contributions. Here we enhance the former 1D proof-of-principle implementation to higher dimensions and optimize it by a new basis set, interpolating Gaussians with collocation. As a further improvement the TNUM approach from Lauvergnat and Nauts [J. Chem. Phys., 2002, 116, 8560] was implemented, which in combination with our adaptive representation offers the possibility of calculating the whole Hamiltonian on-the-fly. For a two-dimensional artificial benchmark and a three-dimensional real-life test case, we show that a sparse matrix implementation of this approach saves memory compared to traditional basis representations and comes even close to the efficiency of the fast Fourier transform method. Thus we arrive at a quantum wavepacket dynamics implementation featuring several important black-box characteristics: it can treat arbitrary systems without code changes, it calculates the kinetic and potential part of the Hamiltonian on-the-fly, and it employs a basis that is automatically optimized for the ongoing wavepacket dynamics.

One possible way to reduce our carbon footprint is using postcombustion capture (PCC) processes to remove CO 2 from flue gases. Because of the highly dynamic characteristics of such processes, real-time performance monitoring is a very complex task. This paper presents a method for monitoring the concentrations of CO 2 , SO x , and a CO 2 capturing agent (β-alanine) during a process in a PCC pilot plant. A partial least-squares (PLS) model was built to estimate these concentrations from Fourier transform infrared (FTIR) spectra of the capturing solvent during processing in a model PCC plant. The model predicts the species concentrations to within 0.05 mol/L, provided that the concentrations stayed within the calibration window of the model. Next to that, it is paramount that the solutions used for model calibration consist of the same solution matrix as the real process medium. The model was eventually used to monitor an emulated PCC process online during 24 h of processing. This demonstrated that events such as saturation of the capturing agent with CO 2 , water replenishment, and switching to safety protocols can be followed accurately. The combination of an FTIR spectrometer and a PLS model can be used to extract process information in real-time.