Edwin Soedarmadji

Solar fuel photoanodes prepared by inkjet printing of copper vanadates

Widespread deployment of solar fuel generators requires the development of efficient and scalable functional materials, especially for photoelectrocatalysis of the oxygen evolution reaction. Metal oxides comprise the most promising class of photoanode materials, but no known material meets the demanding photoelectrochemical requirements. Copper vanadates have recently been identified as a promising class of photoanode materials with several phases exhibiting an indirect band gap near 2 eV and stable photoelectrocatalysis of the oxygen evolution reaction in a pH 9.2 electrolyte. By employing combinatorial inkjet printing of metal precursors and applying both calcination and rapid thermal processing, we characterize the phase behaviour of the entire CuO–V2O5 composition space for different thermal treatments via automated analysis of approximately 100 000 Raman spectra acquired using a novel Raman imaging technique. These results enable the establishment of structure–property relationships for optical absorption and photoelectrochemical properties, revealing that highly active photoelectrocatalysts containing α-Cu2V2O7 or α-CuV2O6 can be prepared using scalable solution processing techniques. An additional discovery results from the formation of an off-stoichiometric β-Cu2V2O7 material that exhibits high photoelectroactivity in the presence of a ferri/ferrocyanide redox couple with excellent stability in a pH 13 electrolyte, demonstrating that copper vanadates may be viable photoanodes in strong alkaline electrolytes.

Worst-Case Routing Performance Metrics for Sensor Networks

Successful integration of pervasive sensor networks in mission critical applications depends on the ability of these networks to cope with and reasonably perform under the worst-case scenarios. One of the key performance measures is the networks ability to route information from the source node to the intended destination. This paper introduces a general framework with which worst-case routing performance of sensor networks can be evaluated and compared. Ultimately, our method can either be used as a design optimization tool, or a decision making tool to select and price contending sensor network designs

Optimal Worst-Case QoS Routing in Constrained AWGN Channel Network

In this paper, we extend the optimal worst-case QoS routing algorithm and metric definition given in [1]. We prove that in addition to the q-ary symmetric and q-ary erasure channel model, the necessary and sufficient conditions defined in [2] for the Generalized Dijkstras Algorithm (GDA) can be used with a constrained non-negative-mean AWGN channel. The generalization allowed the computation of the worst-case QoS metric value for a given edge weight density. The worst-case value can then be used as the routing metric in networks where some nodes have error correcting capabilities. The result is an optimal worst-case QoS routing algorithm that uses the Generalized Dijkstras Algorithm as a subroutine with a polynomial time complexity of O(V3).

CTHp1-5: Optimal Routing in the Worst-Case-Error Metric

This paper considers the problem of finding the path with minimum (zero) worst possible number of errors in a network with V nodes where (1) some nodes are capable of correcting up to a maximum number of xmax errors, (2) the nodes are connected by q-ary Symmetric channels a parametrized by their bit error ratios (BER) pi. We introduce (1) the BER and worst-case error (WCE) metrics and (2) an algebra that allows us to compute the path BER length from its edge lengths, and use them to measure network QoS. The WCE and BER metrics can be used with a generalized Dijkstras algorithm to compute the path of minimum WCE length. Finally, we present an algorithm that solves the above problem in the worst-case time complexity of O(V3).

Colorimetric Screening for High-Throughput Discovery of Light Absorbers

High-throughput screening is a powerful approach for identifying new functional materials in unexplored material spaces. With library synthesis capable of producing 10(5) to 10(6) samples per day, methods for material screening at rates greater than 1 Hz must be developed. For the discovery of new solar light absorbers, this throughput cannot be attained using standard instrumentation. Screening certain properties, such as the bandgap, are of interest only for phase pure materials, which comprise a small fraction of the samples in a typical solid-state material library. We demonstrate the utility of colorimetric screening based on processing photoscanned images of combinatorial libraries to quickly identify distinct phase regions, isolate samples with desired bandgap, and qualitatively identify samples that are suitable for complementary measurements. Using multiple quaternary oxide libraries containing thousands of materials, we compare colorimetric screening and UV-vis spectroscopy results, demonstrating successful identification of compounds with bandgap suitable for solar applications.

Worst-Case Routing Performance Evaluation of Sensor Networks

Successful sensor network applications depends heavily on the ability of these networks to reliably and reasonably perform under the worst-case scenarios, extreme and unusual events for which many such networks are designed to detect. One of the key performance measures is the networks ability to route measurement data from the sensor nodes to the destination node(s). This paper introduces a general framework with which worst-case routing performance of different sensor networks can be evaluated and compared. Our method can either be used as a design optimization tool, or a decision making tool to select and price contending sensor network designs and applications.

Finding the best path in a binary Block Interference network

A binary block interference channel (BIC) is model of binary channels with memory that allows for a mathematically tractable computation of channel capacity. One can easily imagine interconnecting such channels into a network that allows point-to-point communication between any two nodes in the network. Given a pair of network nodes, finding the path with the highest capacity is quite trivial if we can assume that all participating nodes in any path connecting the two nodes can perform coding at arbitrary complexity such that at each link capacity is achieved. However, even if the complexity assumption is not taken into account, in most real-life networks (such as the current Internet), only a minimum amount of coding is performed at the link layer. In most networks, coding is performed five or six layers up in the OSI network model, i.e., on either the presentation or the application layer. Under such realistic circumstances, finding the path with the highest capacity is no longer trivial. In this paper, we propose a solution based on a modified version of the Dijkstrapsilas Algorithm.

The Chinese Generals Problem

To achieve higher reliability, safety, and fault-tolerance, many mission-critical detection and decision systems implement consensus algorithms that force the systems underlying sensor networks to reach the states of consensus and unanimous decision among the sensor nodes. Most consensus algorithms presented in the literature utilize local averaging (for continuous values) and majority voting (for discrete values) operators combined with iterative message passing and other similar nearest-neighbor information propagation schemes. Although very simple to implement, such schemes can be very prone to noise because individual detection and decision errors can be amplified and propagated many times throughout the network. For this reason, in this paper we propose a novel consensus algorithm for binary systems that requires each sensor node to participate in message propagation only if its input exceeds a predetermined threshold. This algorithm is a solution to what we call The Chinese Generals Problem, a wide generalization of The Byzantine Generals Problem by Lamport et al [1]. The threshold function used in the algorithm leads to an adjustable network-wide threshold level that defines the minimum number of nodes initially reporting positive detection required in order for all the nodes to reach the correct consensus.

On generalized parity checks

An ordinary parity-check is an extra bit p appended to a block (x1, ..., xk) of k information bits such that the resulting codeword (x1, ..., xk,p) is capable of detecting one error. The choices for p are p0=x1+...+xk(mod 2) (evenparity) p1=x1+...+xk+1 (mod 2) (oddparity) In this paper we consider defining a parity-check if the underlying alphabet is nonbinary. The obvious definition is of course p=x1+...+xk+α(modq). We shall show that this obvious choice is the only choice for q=2, and up to a natural equivalence the only choice for q=3. For q ≥ 4, however, the situation is much more complicated.